Testomat.io changes this equation. This artificial intelligence driven test management system turns Jira into a full testing command center rather than a decent project tracker. Instead of forcing your agile team to adapt to rigid workflows, it adapts to how modern software development actually works.

The Hidden Cost of Fragmented Test Management

Before diving into solutions, let’s acknowledge the real problem. Your current testing process is likely to resemble the following: the test cases are stored in spreadsheets, the actual testing is done in a different tool, test results are hand copied into Jira issues, and the test progress is unknown until something fails.

This fragmentation costs more than efficiency. It costs quality. When testing activities exist in isolation from your core development workflow, critical information gets lost. Developers can’t see which tests cover their code changes.

Product managers can’t track test coverage against user stories. QA teams waste time on manual reporting instead of actual testing. The best test management tools solve this by becoming invisible, they enhance your existing workflow without disrupting it.

Installing Testomat.io Jira Plugin

Most Jira test management plugins require complex configuration. Testomat.io takes a different approach as the right tool for modern QA teams.

This comprehensive test management solution transforms your Jira instance into a powerful test management tool.

1. Navigate to the Atlassian Marketplace
2. Generate Jira token on Atlassian Platform
3. Go to Testomatio’s settings dashboard from the TMS side to authorize the connection to enable native Jira integration, using this token and your Jira project URL Jira
4. Click “Save” and wait for confirmation
5. Verify bi-directional sync between test cases and Jira issues
6. Confirm Jira triggers are active
7. Test real-time test results display within your Jira user interface

What Teams Miss: Advanced Configuration

The plugin activation is just the beginning of our journey toward integrated test management in Jira. The power comes from how you configure the connection between your Jira project and Testomat.io workspace.

This Jira software testing tool offers different ways to enhance your testing process, making it a good test management tool for small agile teams and enterprise organizations alike.

Connecting Projects: The Admin Rights Reality

Here’s where many test management for Jira implementations fail. The person configuring Jira integration must have admin rights, not just for initial setup, but for the ongoing two-way sync that makes this test management for Jira valuable.

Required Prerequisites:

• Admin rights in your Jira instance
• Access to Testomat.io project settings
• Proper authentication credentials
• Understanding of your Jira project structure

API Token/Password Configuration:

• Follow Atlassian’s official token generation process
• Never skip this step or use workarounds
• Proper authentication prevents 90% of integration issues
• This enables test automation and test execution features

Integration Benefits Unlocked

A successful connection enables:

• Test case management in Jira with full traceability
• Automated test execution triggered by Jira issues status changes
• Real-time test results and execution status reporting
• Enhanced test coverage visibility across test suites
• Streamlined testing activities for continuous integration
• Custom fields integration for better testing data management

This Jira qa management approach transforms how agile software development teams handle software testing, providing an intuitive user interface that scales with your number of users and test sets.

Multi-Project Management: Scaling Beyond Single Teams

The small, agile teams may have a single Jira project, but larger organizations require flexibility. Testomat.io can support a number of Jira projects in relation to a single testing workspace – a feature which differentiates between serious test management tools and mere plug-in.

Repeat the connection procedure with every Jira project in order to tie up other projects. The most important perspective: you can group test cases by project, by feature or by test type and stay connected to several development streams.

This is especially effective in organizations where the Jira projects related to various products, environments or teams are isolated. Your test repository remains centralized and execution/reporting occurs within the context of particular Jira issues.

Direct Test Execution: Eliminating Context Switching

The real breakthrough happens when you can execute tests without leaving Jira. The traditional test management involves frequent swapping of tools, requirements can be checked in Jira and back to Jira to report. Such a context switching destroys productivity and brings up errors.
Testomat.io integrates the execution of your tests within your Jira interface.

It is a brilliant integration in the persistent integration processes. As the developers change code in specific Jira issues, it is possible to set the system so that it automatically initiates appropriate test sets. Does not need manual coordination.

Test Case Linking: Creating Traceability That Actually Works

Most test case management systems claim traceability, but few deliver it in ways that help real development work. Testomat.io creates direct links between test cases and Jira issues, not just for reporting, but for operational decision-making.

Link individual test cases to user stories, bug reports, or epic-level requirements. When requirements change, you immediately see affected test coverage. When tests fail, you can trace back to the specific features at risk.

The two-way integration means changes flow in both directions. Update a test case in Testomat.io, and linked Jira issues reflect the change. Modify requirements in Jira, and the system flags affected test cases for review.

This creates what mature qa teams need: living documentation that stays current with actual development work.

BDD Scenarios and Living Documentation

BDD scenarios are most effective when they remain aligned to real needs. Testomat.io aligns the scenarios in BDD with Jira user stories, the relationship between acceptance criteria and executable tests is preserved.

Write scenarios in natural language within Gherkin. They are converted into executable test cases, test data proposed automatically based on the context of stories and the situations are connected to the test automation frameworks by the system.

When business stakeholders update acceptance criteria, test cases update automatically. When test execution reveals gaps in scenarios, the system flags the parent user stories for review.

Advanced Automation: Beyond Simple Test Execution

This is where the AI possibilities of Testomat.io stand out against the conventional Jira test management software. The system learns the patterns on which you test and proposes optimizations.

As a developer transfers a story to Ready to be Tested, any pertinent testing automation structures are activated automatically. Regression test suites are run in response to a bug being marked “Fixed,” and against a component of the bug.

The AI monitors your testing history in order to determine indicators of gaps in your test coverage, propose test case priorities, and anticipate potential quality problems based on code change conditions and past test outcomes.

Criteria of test execution in Jira are custom fields. Testomat.io can utilize this information to pre-set test environment and execution parameters, in case your team monitors browser compatibility requirements, environment specifications or user persona details in Jira custom fields.

Integration with Confluence

Teams using Confluence for documentation can embed live test information directly in their pages. Use Testomat.io macros to display test suites, test case details, or execution results within Confluence documentation.

This integration serves different stakeholders differently. Product managers see test coverage against feature requirements. Developers see which tests validate their code changes. Support teams see test results for reported issues.

The documentation updates automatically as tests change, eliminating the manual maintenance that kills most documentation efforts.

Reporting and Analytics: Data That Drives Decisions

Standard test management reporting focuses on execution status and pass/fail rates. The AI of Testomat.io further allows you to understand which test cases are the most valuable to maintain, if test coverage is missing, and what correlation exists between the speed of testing and the quality of release.

Create bespoke reports in Jira, which aggregate testing data and project measures. Monitor test execution in relation to your sprints, test execution trends across the various environments and see the bottlenecks in your test process with Jira Statistic Widget.

The system identifies the patterns of your team testing to recommend improvements. Perhaps there are types of tests that will always show problems late in sprints. Perhaps certain test automation systems offer a superior ROI compared with others. These insights are exposed automatically by the AI.

Troubleshooting: Solving Common Integration Issues

Most integration problems stem from permissions or configuration errors. In case the test execution is not activated by Jira, make sure that the service account is correctly authorized in both systems. When test results do not show up in issues in Jira, ensure that the project connections are using the right project keys.

The problem with the API token can tend to depict an indication of expired credentials or inadequate permissions. Create tokens using the official Atlassian process instead of workarounds.

Testomat.io support team offers tailored integration plans by our experts, professional recommendations regarding setup, such as proxy and firewall setup.

Best Practices: Lessons from Successful Implementations

Teams that get maximum value from Jira test management follow several patterns.

• They start with clear test case organization using consistent naming conventions and meaningful tags.
• They establish automated triggers for common workflows rather than relying on manual test execution.
• They use custom fields strategically to capture context that improves test execution and reporting.

Above all, they do not consider test management as an independent practice. Requirements change together with test cases. Execution of test occurs within feature development. The results of tests make decisions on immediate development.

Choosing the Right Tool for Your Team

The market offers many Jira test management plugins: Zephyr Squad, Xray Test Management, QMetry Test Management, and others.

Testomat.io stands out with the power of AI-based optimization and genuine bi-direction integrations. Whereas other tools demand teams to adjust to their workflows, Testomat.io follows the way contemporary agile software development really operates.

The intuitive user interface will be quickly valuable to small agile teams, and native Jira integration is not so overwhelming. At the enterprise level, the multi-project management and the advanced analytics grow to the level of larger organizations.

The free trial provides full access to test management features, allowing teams to evaluate fit before committing. Most teams see value within the first week of use.

Making the Investment Decision

Implementing advanced test management in Jira requires investment in tool licensing, team training, and workflow optimization. Quantity of your existing adhesive method: time lost handing over the tools, developer time lost to unclear test feedback, costs caused by quality problems that seep to production. These hidden costs make investment in integrated test management worthwhile in a matter of months as it is applicable to most teams.

The trick is to select the option that will improve your current process but not to change it. Your team already knows Jira. The correct integration of the test management makes them more efficient without having to learn totally different systems.

Testomat.io develops Jira into a quality management system. Your testing activities become visible, trackable and optimized. Your group wastes less time testing and less time managing tools.

That’s the difference between adequate test management and advanced techniques that actually improve software quality.

The post Test Management in Jira: Advanced Techniques with Testomat.io appeared first on testomat.io.

Thanks to complete regression testing in Agile methodology, they can catch critical bugs that significantly influence the performance much earlier. In the article below, we are going to review the importance of regression testing and how to run it in Agile teams, highlight the regression testing lifecycle, showcase benefits, and introduce the best software regression testing practices.

What is Regression Testing?

As a type of testing, regression testing allows development and testing teams to make sure that newly introduced updates in the codebase don’t break or change the existing application functionality. For example, these code changes could include adding new features, fixing bugs, updating a current feature, or incorporating changes in the test environment. In other words, during regression testing, they re-execute test cases that have been cleared in the past against the new version to make sure that the app functionality continues to function well after modifications. Furthermore, regression testing is a series of tests, not a single one, performed whenever you add new code.

Smoke and Sanity Testing: What Are They?

However, when teams perform regression tests, it is important to mention the smoke and sanity ones.

Smoke Tests. In the QA process, smoke tests are the first line of defense, which are run early in the SDLC to catch major issues while development is still in progress. These initial tests pinpoint any major bugs, which have been discovered during development. Only after these checks are passed does sanity testing begin.

Sanity Tests. Performed on stable builds with recent code changes, this type is used to confirm that recent updates haven’t disrupted key functionality and that the build is ready for more extensive regression testing.
When smoke, sanity, and regression are used together, they create a more stable and secure release process. While smoke testing verifies functionality in isolation, skipping sanity and regression means that teams might miss larger problems, which often appear only when different components of the software interact.

On the other hand, depending only on sanity or regression testing can result in inefficient cycles of tests. Teams might waste valuable time validating recent features and re-verifying old ones, and lack the quick effectiveness that smoke testing offers at the start. Knowing that, QAs should combine all three methods to carry out a faster QA process and provide more certainty with each new release.

Regression Testing in Agile: How It Works

Agile is a flexible approach which can be applied in the management and organization of tasks. When you use it for QA activities, you should consider all the requirements and new changes throughout the process. With regression testing in Agile process, you can break down big, complex tasks into smaller and more manageable ones. Thanks to this dominant feature of this approach, all functionalities work under the given requirements in an agile environment. Regression testing in Agile development is made up of the following parts:

1. Preparation. Teams get together to create Agile test plans, which include automated and manual regression testing strategies, and discuss the scope of features that need to be implemented and tested.
2. Daily Scrum meeting. Teams communicate daily to track the progress of testing, draw reports, and provide re-estimation of all the tasks due to possible problems, changes, or improvements.
3. Review. Teams analyse the progress of the software testing process and compare expected results with the real outcome.
4. Release Readiness. Teams decide which features are ready for customers or end users and which ones are not.
5. Impact Analysis. Teams find areas which can be improved. They discuss their overall performance and the tools used to find actions they can take to make the QA process more effective in future iterations.

It is important to mention that to conduct effective regression testing in agile, teams should build a regression test suite right from the initial stages of software development and then keep building it with each coming sprint. Before creating a plan for regression testing, a few things to consider the following:

• Deciding which regression test cases need to be run.
• Determining which test-case enhancements need to be made.
• Deciding when regression testing should be done.
• Describing what and how the regression test plan needs to be automated.
• Examining the regression test results.

Based on experience, the Agile approach for testing takes much time on planning, but this upfront investment prevents team members from bigger problems down the line and reduces the need for extensive bug fixes and task revisions.

Benefits of Regression Testing in Agile

Below, you can read about essential advantages that impact the finished product. Here are some benefits you need to know.

Early Bugs Identification

With the constant release of new features, Agile regression testing helps teams identify the improvements or error-prone areas earlier and target them. When teams detect new bugs early in the development cycle, Agile regression testing can help them reduce excessive rework and release the product on time.

Quicker Turnaround

While there are a lot of testing tools available, regression tests can be automated. So that Agile development teams can get quicker feedback, accomplish more rapid cycles, and make releases more confident and quick.

Ongoing Functionality Monitoring

Since Agile regression testing usually takes into consideration various aspects of the business functions, it can cover the entire system by running a series of similar tests repeatedly over a period of time, in which the results should remain stable. For each sprint, this helps test new functionality and makes sure that the entire system continues to work correctly and the business functionality continues down the line.

Confidence Booster

Adding new features to an application can be slow due to the many factors involved. However, the Agile approach simplifies this by promoting incremental changes and improving this method with regression tests, which confirm that the new functionalities haven’t unintentionally disrupted or “broken” and verify that the new features haven’t negatively impacted existing ones.

Isolated Changes Support

Development teams can make changes without fear, no matter how big or small, thanks to Agile regression testing. With the assurance that regression tests will identify any areas of the codebase impacted by their recent changes, teams can focus on the new functionality scheduled for a sprint.

Minimized Errors

The emphasis on quick release cycles in an Agile development environment naturally reduces the window for mistakes. Every step of the release process includes a series of regression tests to ensure the product stays stable and free of bugs. This greatly improves the software stability and its quality.

User Satisfaction

With regression testing in an Agile environment, teams make sure that changes won’t unexpectedly disrupt service and that updates improve the application without introducing new problems. Thus, they can deliver a functional and user-friendly software product which achieves a positive user experience and enhances user satisfaction.

Challenges of Agile Regression Testing

Below, you can review common challenges which demand careful and strategic solutions:

Too Many Changes

In the course of developing software, stakeholders frequently ask for changes or alterations to the requirements. These changes have the potential to introduce instability, which can, in turn, have a negative impact on the success of the test automation strategy. To prevent the need to recreate test scripts halfway through a project, execution within CI/CD pipelines is required, so that no features break.

Expansion Of Test Suites

With each sprint, the scale of regression tests increases. In the case of large projects, it is really difficult to manage tests. Knowing that, QA teams should automate and review tests on a continual basis, because ineffective tests must be removed or optimized. To simplify the process, they can use a test case management system like Testomat.io.

Poor communication

There should be an effective communication channel and proper strategic communication taking place between the QA teams, developers, business analysts, and business stakeholders, which will ensure that the Agile regression testing process is streamlined. Through effective communication, specific features, which have to undergo regression tests, can be correctly determined.

Time-Intensive Maintenance Process

It takes a lot of time to maintain and update the test suites when software evolves, because test cases need continual updates to stay relevant with current application functionality. That’s why you need to conduct regular reviews to keep the test suite relevant, to use modular test design, and implement version control for test scripts to track modifications to test scripts as well as maintain a clear history of changes.

When Teams Need to Perform Regression Testing in Agile

For early issue detection and consistent stability, you need to incorporate regression tests throughout the critical steps of the Agile cycle:

• End of each sprint. Teams conduct a sprint review and retrospective to validate that new features haven’t broken existing functionality. For example, your online banking portal currently requires users to log in only via a username and password. A new feature would be the implementation of two-factor authentication via SMS.
• Before the sprint demo. Before the sprint’s work is shown off in a demo or review, the team runs tests to make sure the product is stable and still meets all the requirements for both the new features and everything that was already there.
• After bug fixes. Teams confirm the fix to make sure that related areas remain unaffected. For example, when a tester finds a login button that isn’t working, it should be retested after developers have implemented a fix. It is important to mention that tests are also performed on all related login features to make sure they continue to work correctly.
• Before release or deployment. Teams conduct tests to verify that the product is prepared for the production environment and to prevent new issues after it goes live.
• After code integration or merges. Teams test for regressions or unexpected behaviors, which the new code changes might have caused. For example, when a CRM system is connected with an email marketing platform to automatically sync contact lists.
• After major UI or backend changes. Teams make sure that workflows and user experience remain intact.
• Parallel with development. Regression tests are often run in parallel with ongoing development activities in order to uncover and fix bugs promptly, maintain a balance between development speed and software quality.

Agile Regression Testing: Process

Generally, the Agile regression testing process often comprises the following stages:

1. Identify critical functionality. To get started, teams should choose core workflows of changes, new features that have been implemented, or high-risk areas for quality assurance.
2. Select tests for automated regression testing. You need to choose test scenarios for automation. However, not every test case should be automated. You need to focus on test case prioritization using mind maps to visually see which tests are important and which ones can be delayed if necessary, to decide which test scenario will benefit most from automation.
3. Select the right test automation tool. The type of product you’re developing and the needs of your team will determine which of the many options available to you for automating regression testing is best. When selecting a tool, consider the technical expertise of your team, whether you’re running tests on a desktop, mobile, or web application, and how well the tool will integrate with your current development environment.
4. Use CI/CD tools. Integrating automated regression tests into your Continuous Integration/Continuous Delivery (CI/CD) pipeline is crucial if you want to fully reap its benefits. This will cause automated tests to launch automatically each time a new build is released or new code is added to the repository. This ensures that every modification is thoroughly tested before going live. Automating these test runs as part of your build process is made easier by tools like TravisCI, CircleCI, and Jenkins.
5. Run tests regularly. You need to schedule regular runs of your automated regression suite to run overnight or during off-hours to save valuable sprint time and trigger them after every code change or sprint to maintain stability.
6. Monitor and Refactor. You need to continuously refine test cases to align with product changes. As sprint cycles demand quick turnarounds, you need to make sure test cases evolve to avoid inefficiencies in quality assurance flows. Without periodic refactoring, test suites can become overloaded with outdated or flaky tests, which contribute to increased execution time, higher maintenance costs, and reduced confidence in testing outcomes.

Best Practices for Maintaining Regression Testing in Agile

We have gathered 9 quick wins to better maintain regression testing in Agile and make sure you are getting the most out of it.

1⃣ Start Small

To scale strategically, you need to start with smoke tests that cover your absolute must-work scenarios. Once these are solid and running reliably, you should increase test suites for core features and shouldn’t test everything at once. It’s an ideal initial point for regression tests in mature and long-standing projects.

2⃣Regular Regression

When your team fixes one bug, it might create another one. In other words, after changes, there are features that were previously working but are now broken. This means that even minor updates or changes can introduce “hidden defects.” To avoid these defects in production and keep them fixed before release, teams should focus on running daily regression tests before every release to decrease the need for emergency fixes.

3⃣Shift-left and Continuous Testing

Shift left testing is about checking your software early in development, especially in Agile projects, checking smaller components with less complexity. In the shift-left testing approach, QA teams can catch the defects early, and development teams can rectify those at the component level. When shift-left testing is a part of the continuous test strategy, it allows testers to generate more comprehensive tests with functional data. The combination of shift-left and continuous testing ensures that it is leveraged early on and during the product development pipeline.

4⃣Test Automation is a Priority

If you aim to maintain efficiency and comprehensive coverage, you need to focus on automating regression tests, which are faster than manual testing. As new features are developed, automated tests should be created for the core functionalities and any bug fixes to be aware that the most critical and fragile areas of the application are continuously tested throughout the development process.

5⃣Risk-based Test Selection

When opting for risk-based testing, you can assess and prioritize tests based on potential risks associated with different features or functionalities. Thus, you can focus QA activities on areas with higher risk exposure and optimize resources for comprehensive regression testing.

6⃣Modular and Reusable Test Design

With a modular test design method, you can create automated test suites that provide full functional test coverage using individual functional modules. Testers design new test cases by dividing an application into functional areas with modules based on complexity. Modular test design builds reusable test case modules that are understandable and enhance productivity and ease of maintenance. This saves time and effort as well as accelerates the test creation process to guarantee that any modifications to the test data are reflected in all related tests.

7⃣Mind Mapping

With the mind map testing technique, teams can get an overview of the whole product and use it as a roadmap for the testing journey. Mind maps allow testers to visually organize and represent test scenarios and relationships between components. They cover all of the use cases and scenarios and draw connections in a way that is challenging to represent in a list. Being the source of truth for the team and stakeholders, mind maps establish an integrated perspective on testing to let testers strategize, plan, and execute tests more effectively.

8⃣Reusable Test Data Source

Preparing data for testing can be very time-consuming and requires a lot of a tester’s time, which is spent on searching, maintaining, and generating data. Instead of writing a new test for each piece of data, you can use a test data management tool so that test data can be managed in a repeatable way. Furthermore, when test data becomes more complex, this tool will help you better deal with data aging and data masking.

9⃣Collaboration Between Developers and Testers

Effective communication is crucial for quality assurance engineers. They must clearly explain issues so both product owners and developers understand them. Beyond that, it’s vital to encourage b communication within the QA team to ensure everyone is aligned and working together smoothly.

How Test Management System Helps in Agile Regression Testing

One of the biggest benefits of regression-testing in an agile context is the ability to get fast feedback about how your latest build impacts existing features. The best way to get this feedback is to use a test case management system as Testomat.io, which allows you to:

• Store all test cases, plans, and results in one place and guarantee that everyone on the team has access to the most current and relevant information about tests.
• Monitor the progress of their test cycles, get information on the test status to make timely decisions.
• Link test cases directly to user stories and defects to see exactly which tests cover it and what its current status is.
• Get reports with latest test runs, defect rate, and defects clustering, and filter them.
• Send notification about finished test regression runs with test results and share instant access to results in real time.

Bottom Line

In Agile software development, you can move fast, iterate quickly, and fix faster to ensure new changes do not break existing application functionality. Teams are keen on it because it lets them launch features faster and respond to changes without delays. However, every time you move fast, there’s a risk you’ll break something.

With Agile regression testing, teams can avoid shipping critical bugs to production by confirming the most important parts of an app are still working every time new code is pushed. If you aim to learn more about the impact Agile regression testing can bring to your software applications, do not hesitate to drop us a line.

The post Agile Regression Testing Explained: Process & Best Practices appeared first on testomat.io.

What is Gherkin?

Gherkin is a simple, human-readable plain language, composed in such a way that anyone can understand the written statements, even those with a limited scope of programming knowledge. Gherkin is used in Behaviour-Driven Development (BDD). In other words, Gherkin is the heartbeat of BDD.

It helps development teams write clear scenarios that describe how software should behave from the user’s perspective, actions are equal – Steps.  This allows both technical and non-technical people to work together and stay on the same page, making collaboration easier and ensuring documentation stays accurate.

Cucumber is the most widely used BDD framework. Some popular ones are Behat, Behave, JBehave, CodeceptJS and Codeception.

Why Grerkin Matters in Behavior-Driven Development (BDD)

• Gherkin encourages test-first thinking. Gherkin encourages writing scenarious early, guiding teams to define expected behavior before writing code. It prevents bugs, not just catches them.
• Shared Understanding Across Teams. Rather than relying on lengthy technical manuals or ambiguous user stories, Gherkin provides a formalized way to describe system behavior through conversational language. This simplicity enables teams to align expectations early on, especially who is involved in the development process — not just engineers, but also product owners, business analysts, and QA specialists. It occurs during the Three Amigos sessions, where developers, testers, and business stakeholders collaborate to define what the Definition of Done(DoD) looks like.
• Living Documentation. Gherkin plays a vital role in Behavior-Driven Development by transforming complex requirements into simple, structured documentation.
• Enhancing collaboration. Gherkin, by acting as a living specification, reduces misunderstandings, improves test coverage, and keeps requirements tightly coupled with automated validation. It bridges the gap between business intent and technical implementation, making BDD not just possible but practical.

In short:

Gherkin makes BDD practical — aligning business goals with technical implementation through clear, collaborative, and testable language.

Gherkin in Agile & BDD Workflows

Gherkin focuses on teamwork, taking small steps, and getting regular feedback. This method fits well with Agile practices.

In Agile teams, Gherkin helps connect business and tech teams. It helps everyone understand user stories and acceptance criteria together. This way, Agile teams can deliver value bit by bit and adjust to new needs quickly. Gherkin serves well in Agile and BDD workflows:

• User stories → drive features
• Scenarios in Gherkin → describe behavior of these features
• Automation tools like Cucumber, SpecFlow, or Behave → link Gherkin to real tests

This creates a shared understanding between PO, Dev, and QA. Let’s break it down more:

For example, BDD with Gherkin could also be implemented like this in the Agile Cycle:

As you can see from our visual, the main differences between BDD Agile Workflow and traditional imperative testing are:

→  More traditional Agile testing workflow is more focused on execution rather than behavior.
→  BDD uses Gherkin, a declarative DSL that emphasizes specific behaviors.
→  BDD Agile promotes a shift-left approach. With Gherkin-based acceptance criteria defined upfront, teams embed quality into development before it starts.

Basic Structure of a Gherkin Scenarios

A Gherkin .feature file is structured to describe software behavior using scenarios. It begins with a Feature keyword, followed by a description of the feature. Each scenario within the feature outlines specific examples of how the feature should behave, using keywords like  Given, When,  Then to define the context, actions, and expected outcomes. Here is a breakdown of the structure:

For example, the User Login feature describes how users access the system through the login page. If they enter the correct username and password, they’re taken to the home page. If the login details are incorrect, the system shows an error message to let them know something went wrong.

Feature: User Login
As a user, I want to be able to log in to the system.

  Scenario: Successful Login
    Given the user is on the login page
    When the user enters valid credentials
    Then the user should be redirected to the home page

Features and Scenarios Explained

At the center of Gherkin are Features and Scenarios. A Gherkin feature points out a specific ability of the software. It comes with related test cases and explains how a feature should work in different situations.

• Scenarios serve as test cases.
• Each feature has different scenarios.
• These scenarios imitate how real users behave.
• They explain certain actions and the results you should expect.
• They offer a simple guide on how a system should react to various inputs or situations.

To avoid repeating tests for similar tasks with different data, Gherkin uses Scenario Outlines These are like templates. They allow testers to run the same scenario many times with different data. This way, testers can check everything well while keeping the code simple and effective.

Step Definitions: Given, When, Then

Gherkin syntax uses a simple format called Given-When-Then. This format helps to describe the steps for each test case. It makes it easy to understand the setup, the actions taken, and the expected results in a scenario.

• Given shows where the system starts. It describes what the system looks like before anything happens. This step makes sure the system is prepared for what follows.
• When  tells us about the action that makes the system respond. It includes what the user does or what takes place in the system that changes how it works.
• Then shows what should happen after the action in the When step. It explains how the system should behave after that action, so we can check if it works as intended.

* Take a closer look at this extended code snippet — note how we marked Given, When,  Then as Facts, Past, Present, or Future statements for a better understanding of context.

# Login Functionality

Background:
Given the following user registration schedule:
  | Username | Password | Status   |
  | user1    | Pass123  | Active   |
  | user2    | Test456  | Inactive |
And user1 is a Frequent Flyer member     # <-Fact    

Scenario: Successful login with valid credentials
Given user1 has purchased the following credentials:          # <-Past 
  | Username | Password |
  | user1    | Pass123  |
When the user submits the login form                   # <-Present
Then the user should be redirected to the dashboard     # <-Future

What is an Effective Gherkin Test?

Creating good Gherkin tests isn’t just about understanding the syntax. You also need to follow best practices. These practices make the tests clear, simple to update, and dependable.

It is important to write tests that are short and clear. These tests should show how real users interact with the system. Use simple words and avoid technical terms. Focus on one part of the system for each test. This way, your Gherkin tests will be better and easier to handle.

Advantages of Using Gherkin

Gherkin is a powerful communication tool that brings developers, testers, and business stakeholders onto the same page. By describing behavior in plain language, Gherkin helps teams define, automate, and validate application functionality with less friction and more clarity. Below are the key advantages of using Gherkin in modern Agile and BDD workflows.

Better Communication Across the Team

Since Gherkin uses plain English, everyone, whether they are technical or not, can understand what the software is supposed to do. This helps developers, testers, and business stakeholders stay on the same page and reduces the chances of misunderstandings. It also keeps the focus on the user experience, which leads to more useful related features.

Documentation That Stays Current

Gherkin scenarios are tied directly to automated tests, which means they reflect the software’s real behavior, not just how it was supposed to work. You are not stuck with outdated documents, and your team always has a reliable reference point. These scenarios are version-controlled and stored with the code, so everyone can access and update them easily.

Faster Development and Better Testing

Because Gherkin scenarios can be turned into automated tests, they help speed up testing and give quick feedback during development. Writing tests before building features also helps catch issues early. Since Gherkin fits well with Agile practices, it supports frequent changes and constant improvement.

Long-Term Efficiency and Better Test Coverage

Gherkin scenarios are easy to update as requirements change, which helps lower the time and cost of maintaining tests. They also encourage teams to think through different use cases and edge cases, improving overall test coverage. The structured format allows you to reuse steps across different tests, reducing repetition and making your test suite easier to manage.

BDD Test Case Writing Pitfalls to Avoid: How To Solve Them?

Gherkin makes it easier for you to write tests. However, there are a few common mistakes to remember. These mistakes can make your test cases less effective

By avoiding these mistakes and using these Gherkin strategies, you can build better and more reliable Gherkin tests. This will improve your testing as well as the quality of the software.

How Is Gherkin Linked to Automated Test Code

The main connection of the language with automated test code is through its syntax. It uses a plain text format, operating such keywords as  Given, When, and  Then which are linked to the corresponding automated code that executes all the required steps. Thanks to it, the language stays abstract and readable, which allows non-technical users to understand the scenarios and technical users to maintain the test code.

Popular Testing Frameworks with Gherkin Support

Gherkin is paired with testing frameworks that interpret and run them — the most well-known being Cucumber, which turns real system behavior into automated BDD tests.

Together, Gherkin and these BDD frameworks simplify test automation, improve collaboration, and create living documentation that evolves with your product. Below is a comparison of popular frameworks that support Gherkin syntax:

Framework	Language(s)	Description
	Java, JavaScript, Ruby, etc.	The most widely used BDD tool; executes Gherkin scenarios directly.
	Python	Lightweight BDD framework for Python projects; uses Gherkin syntax.
	.NET (C#)	Native BDD framework for .NET; integrates tightly with Visual Studio. Unfortunately, now it is not supportedrted already.
	Multiple (Java, C#, JS)	Developed by ThoughtWorks; supports markdown-style Gherkin + plugins.
	JavaScript	End-to-end test framework with Gherkin plugin; integrates with WebDriver.
	JavaScript/TypeScript	Combines Jest’s test runner with Cucumber support for BDD testing.

Requirements for the Test Management System:
What Do True Testers Need?

Every test automation with a language has its own set of requirements in order for the analysis to succeed. Everything starts with defining the Agile roles in BDD. Every project must include a team that consists of:

• QAs
• Dev team
• BA (business analysts)
• PM (project managers) or PO (product owners).

Then, there are technical requirements that must be met by the system for integrating Gherkin naturally. The basic criteria include:

• Gherkin-Friendly Editor. The system should let users write, edit, and manage Gherkin feature files with syntax highlighting and support for key elements like Given, When, Then, tags, backgrounds, and scenario outlines.
• Seamless BDD Tool Integration. It should work smoothly with popular BDD tools such as Cucumber or Behave, making it easy to plug into existing testing workflows.
• Automation & CI\CD Support. The platform should connect with CI\CD tools (like Jenkins or GitLab), allow automated test execution, and display test results directly in the system.
• Test Management & Result Tracking. The system should let you track which scenarios are passing, which ones failed, and how they map to defects or bugs, offering a full picture of test coverage.
• Team Collaboration Tools. It should support multiple users working on the same features, with options for comments, approvals, and version history to review what changed and why.
• Reporting & Dashboards. The platform should offer easy-to-read dashboards that show test progress, coverage, and trends, with filters for tags, features, or test status.
• Gherkin also helps with living documentation. This means that the tests will update when the software updates. This is important for development that happens in steps. Because of this, Gherkin is a great tool for teams that want to be flexible and create high-quality software frequently.

Once these requirements are met, the team can proceed with setting up the testing environment and running the very first check using Gherkin.

Test management system testomat.io meets the needs of modern teams in Behavior-Driven Development (BDD) and makes the testing process more practical and powerful by seamlessly integrating Gherkin-style test cases into your workflow. Testomatio’s BDD-friendly UI supports an advanced Gherkin Editor.

Steps Database allows the reuse of steps and shared scenarios, making collaboration easier across distributed teams. Smart, generative AI analyses existing BDD steps across your project and suggests new ones based on them.

Starting with us, you can easily turn your manual test cases outside with a script into BDD scenarious in a minute.

Drop us a line today to learn how we can help you enhance your BDD testing processes that meet the highest standards, contact@testomat.io

How Do Gherkin Scenarios Work with Continuous Integration (CI) & Continuous Delivery (CD)?

Gherkin scenarios integrate smoothly with Continuous Integration (CI) and Continuous Delivery (CD) pipelines, helping Agile teams deliver high-quality software faster. When used with CI\CD, Gherkin scenarios automatically run each time code is pushed, ensuring that new changes do not disrupt existing functionality. This provides early detection of issues, minimizes risks, and ensures that only stable, verified features are deployed. Here is how Gherkin enhances CI\CD practices:

• Automated Test Execution. With Gherkin scenarios written in a BDD framework like Cucumber, tests can be automatically executed as part of the CI pipeline. When developers push changes, the pipeline runs these scenarios, validating that new code aligns with predefined acceptance criteria and doesn’t introduce regressions.
• Immediate Feedback Loop. CI\CD practices emphasize frequent deployment and testing to provide immediate feedback. Gherkin’s clear, business-oriented scenarios allow both technical and non-technical team members to understand results, facilitating prompt discussions and decisions.
• Living Documentation in Real Time. Gherkin scenarios act as living documentation within a CI\CD environment. As the software evolves and scenarios pass or fail, the documentation reflects the latest behavior of the system. This keeps the whole team aligned on current functionality and prevents outdated documentation from leading to misunderstandings.
• Continuous Quality Assurance. By integrating Gherkin-based tests into the CI\CD pipeline, teams can enforce continuous quality checks. Each build goes through comprehensive Gherkin-based testing, ensuring that any issues are detected early and resolved before deployment.

Conclusion

Gherkin is very important as it helps teams work together better and be more efficient. Gherkin has a simple structure and is closely connected with Cucumber, but it is not the same. This connection allows teams to speed up their testing and improve BDD, which means Behavior-Driven development.

Writing clear Gherkin tests and using good practices is key to avoiding common mistakes. This helps make software projects successful. There are many examples in the real world that show how helpful Gherkin can be. It is flexible and is valuable in several industries. You should use Gherkin to make your testing better. Keep learning and creating!

The post What is Gherkin: Key to Behavior-Driven Development appeared first on testomat.io.

This breakthrough became possible thanks to the key role Agile testing plays in ensuring accuracy and rapid adaptation to changes. That is why it has become an integral part of the modern development process. To move confidently in the new programming environment, it is important to understand the impact and value of this approach.

What is Agile Testing?

Agile testing is a software testing method based on the principles of Agile development. The testing process involves not only Agile testers but also all team members, including analysts, developers, and other specialists within their areas of responsibility. Unlike the classical approach, where testing is a separate phase, here it is integrated at all stages – from requirements gathering to design, writing new code, and creating test scenarios.

This approach is characterized by flexibility and continuity: testing is conducted throughout every cycle of the software product development. Its main goal is to meet the customer’s needs, which is achieved through constant verification of the product’s compliance with end-user expectations.

Agile testing is usually informal, conducted regularly within each iteration of the software development life cycle, and aimed at maximally considering user requirements at every stage.

The concept of Agile Testing Methodology

Agile testing methodology refers to the approach and set of practices applied to test software in an Agile development environment. In this approach, testing is not separated as a distinct phase but is organically integrated into all stages of the software product life cycle.

Its principles are outlined in the Agile Manifesto. It focuses on collaboration, adaptability to change, and continuous feedback.

Agile testing, in its essence, is a testing process conducted in the context of the Agile environment. While many types of testing — such as regression or functional testing — are also common in other development approaches, in Agile teams, the very methodology of their execution changes. This includes how testing is planned, integrated into the release cycle, and how its effectiveness is assessed.

Traditional Testing Method VS Agile Software Testing

To avoid situations where software breaks during real user operation, testers are the first to try to identify all its weak spots — and pass them on for improvement.

In the classical waterfall model of software development, the process looks like a sequential chain:

Requirements Gathering → System Design → Implementation → Integration and Testing → Deployment → Maintenance.

In this approach, each subsequent stage begins only after the previous one is completed. Because of this, the QA team receives the product for testing only at the final stages of development. Errors detected at this stage are much harder and more expensive to fix than during earlier phases.

When testers are involved only at the end of development, they do not have the opportunity to ask important questions or conduct full-scale testing, as they receive almost no feedback from either the clients or the rest of the team. Sometimes, they are even perceived as an external element. In such cases, testers simply wait until the product reaches them through the production line, and only then do they test it — having limited tools to determine whether it should be sent back for revision.

In Agile development, the approach is completely different: the test plan accompanies the entire product creation cycle. Each time the code is updated, the test team immediately gains access to it, checks it, and provides feedback directly to the developers. These short testing cycles may also include automated testing and the participation of real users, which allows for the quick detection and correction of flaws. Let’s total briefly with a table, compare the Waterfall Model and Agile once again:

	Waterfall	Agile
Requirements	Clearly-defined	Can change
Client involvement
Type	Straightforward	Complex projects
Time frames	Strict	Loose
Team collaboration	Moderate	Intensive

Implementing Agile testing methodology requires focus and responsibility; however, the results can significantly improve product quality. At the same time, a careless application of the Agile approach without evaluating its appropriateness can do more harm than good — leading to an unstable and unreliable system.

Here are situations when it is worth considering whether Agile testing is truly appropriate:

Clearly defined project scope

If the project requirements are final and not subject to change, the dynamic nature of Agile may not provide additional value.

A single influential customer

In projects where one person or a small group makes all decisions, the collaborative model of Agile may conflict with centralized decision-making according to customer requirements.

Insufficient level of competence

Since Agile testing demands broad knowledge and the ability to work at a fast pace, teams without adequate preparation may find traditional approaches more comfortable.

Customer insists on waterfall

If the client expects a traditional development and sequential staged approach (waterfall model), Agile may cause resistance and misunderstanding.

Agile Testing Principles

Twelve principles were formulated after the creation of the Agile Manifesto. They serve as a practical guide for teams that aim to work in accordance with the Agile philosophy. These principles help evaluate how well the team’s current actions align with the spirit of Agile and demonstrate how this approach should be implemented in everyday work.

Here is a brief summary of the key principles:

1. Early and frequent testing. The earlier errors are detected, the easier they are to fix. That is why testing should start as early as possible—even during the requirements gathering phase.
2. Test automation. Creating automated scripts allows for faster verification of changes. However, it is important not to overestimate the capabilities of automation and not to expect a higher level of automation than is realistically achievable.
3. Continuous feedback. A tester’s task is not only to find bugs but also to ensure fast communication of test results between the client and developer to quickly improve the product.
4. User value comes first. Although this is not the first item on the list, focusing on delivering value to the client is the main goal of the entire development and testing process.
5. Live communication. Testers should interact directly with developers and users — this reduces the risk of errors and misunderstandings.
6. Simplicity is efficiency. A tester should perform only necessary checks, but not overlook any critical ones. In product work, simple solutions are preferred if they provide maximum benefit.
7. Continuous improvement. Agile professionals constantly seek new ways to make their work better and more productive.
8. Adaptability to change. Agile teams quickly adapt to new conditions — whether it’s changing requirements, user feedback, or market dynamics.
9. Self-organization. Testers do not wait for instructions—they independently identify where their involvement is needed and unite the team around solving the problem.
10. Focus on the end user. People are the priority. Communication, convenience, and practicality are critical.
11. Daily collaboration with the business. Developers and business representatives should work side by side every day to better understand customer needs and quickly implement changes in the product.
12. Regular reassessment of work. The team should periodically reflect on their approach, seek improvements, and adjust behavior to achieve greater effectiveness.

Agile Runs on Continuous Feedback

Customer Feedback and Close Collaboration with Them – Above All!

The agile approach to testing values customer needs above the company’s internal requirements.

Testing throughout the entire development process results in a higher-quality product and ultimately greater customer satisfaction.

Instead of the client receiving a pig in a poke at the end, where problems may arise that are difficult (or even impossible) to fix, the agile approach allows the detection of failures and issues as they occur.

The customer plays a much more active role throughout the entire development process. The role of collaboration with clients in agile testing is much more significant than just negotiating contract terms. They can provide their suggestions and feedback at every stage. This allows tailoring the product to the customer’s needs and expectations, which leads to a much better outcome.

Agile methods may either include the end user as a full member of the team (who attends all meetings and monitors goal achievement) or involve them periodically for product demonstrations. Although some clients may not care how exactly your product is created, absolutely everyone expects a result that satisfies them.

Thus, the agile process provides transparency that no other approach can ensure since clients are involved in the development process from start to finish.

Agile Testing Life Cycle

The Agile Testing Life Cycle (ATLC) is the process QA teams follow to plan, implement, and execute testing in Agile software development environments. Agile testing is continuous and iterative, happening in each sprint.

The Agile testing life cycle consists of five main stages:

1. Impact analysis, Requirements Gathering. This initial stage is also known as the feedback phase. Opinions and feedback from users and stakeholders are collected. This allows testers to clearly define the goals for the next testing phase.
2. Agile test planning, test design. At this stage, the testing efforts of developers and testers are combined with the input from customers and stakeholders to create a detailed plan: the testing schedule is discussed, the frequency of meetings is determined, and the expected results are defined.
3. Release readiness check. At this stage, testers analyze the implemented features to determine if they are ready for launch. Functionality that does not meet quality criteria is sent back for revision to the previous development phase.
4. Test Execution. As development proceeds, tests are run continuously — both manually and automated tests through CI pipelines. Automated regression, functional, and unit tests are executed with each code change.
5. Daily stand-ups (Daily Scrums). Every morning, the team holds brief meetings to align on the current testing status and set goals for the day. This helps to respond quickly to changes and improves coordination.
6. Agile test evaluation. The final stage includes weekly meetings with stakeholders, during which progress is analyzed and actual results are compared to the planned objectives.

Agile Testing Strategies tailored for AI-assisted testing

If you are confident that Agile testing aligns with your development team’s goals, client expectations, and product characteristics, follow these recommendations:

Choose the appropriate methodology

Determine which of the Agile approaches (e.g., Scrum, Kanban, or Extreme Programming) best suits the needs of your project.

Build an effective testing strategy

Focus on the four testing quadrants to cover all key aspects of product verification. We are talking about it ahead.

Define objectives with AI in mind

Identify areas where AI can provide the most value — like generating test cases automatically or test data, optimizing regression tests, maintaining tests, detecting flakiness or blind spots in your testing project. Select AI-powered test platforms or AI testing agents.

Ensure team collaboration and avoid tester isolation

• QA team should work closely with developers. Constant communication facilitates quick responses to changes and helps form a unified vision.
• Adhere to iteration-based work. Collaboration at each stage helps establish effective interaction from the very beginning of the project.
• Define a human-AI collaboration approach. Clarify how human testers work alongside AI — reviewing AI-generated tests, approving AI suggestions, or AI-generated insights of release readiness.
• Provide feedback. Tester comments and suggestions are important for both developers and customers. This enables two-way communication and improves the final product.

Here is a structured breakdown of the key steps within a testing strategy, which can be applied to implement Agile successfully:

#1: Iteration 0 

This is the very first step in the testing process, during which the foundation is laid for all further work. At this stage, the testing environment is configured. This phase includes performing preparatory tasks:

• searching for test participants
• preparing the necessary materials and resources for usability testing
• justifying the project from a business perspective
• defining boundary conditions and the overall scope of work
• formulating key requirements and usage scenarios
• outlining one or more possible project architecture options
• outlining how and when tests will be executed—manual, automated, scheduled in pipelines
• planning the initial project budget and estimating costs
• choosing testing tools
• identifying potential risks.

#2: Construction Iteration 

This is the second phase of the testing process, which is the main and most labour-intensive. It consists of a series of repeated cycles (iterations) aimed at gradually building and refining the software product. This process is divided into two types of testing:

First, Confirmatory Testing — verifies that the system meets stakeholder requirements as communicated to the team at that time. It is performed by the development team itself and is further divided into two subtypes:

• A. Agile Acceptance Testing. This is a combination of acceptance and functional testing. It can be conducted either by the development team or the stakeholders. On this stage, testers often work following test design techniques like boundary value analysis, equivalence partitioning, state transition, or BDD scenarios.
• B. Developer Testing. This is a combination of unit and integration testing that checks both the software code and the database structure.

Second, Exploratory Testing identifies problems that were missed or overlooked during confirmatory testing. In this type of testing, the tester identifies potential problems in the form of defect stories. It focuses on areas such as integration testing, load testing, security testing, and stress testing.

#3: Analysing Testing Efforts

Define defect tracking, reporting, and analytics tools, including AI-powered anomaly detection tools; how issues will be triaged, prioritized and notified to the team.

#4: Release End Game

This phase is also known as the transition phase. It includes full system testing and acceptance testing. To complete the testing stage, the product undergoes even more thorough checks than during the development iterations. Testers work on fixing identified defects. This phase includes the following activities:

1. Training end users.
2. Preparing support and operations staff.
3. Marketing activities related to the product release.
4. Backup and data recovery procedures.
5. Finalization of system and user documentation.

#5: Production

This is the final phase of Agile testing. At this stage, the product is finalized after all identified defects and issues have been resolved.

Agile Testing Quadrants

Agile testing is divided into four quadrants, each covering a separate area of the software verification process.

Quadrant 1 (Automated)

This stage focuses on the internal quality of the software code. Technically-oriented test scenarios are created and executed here, primarily automatically by QA testers. The main goal is to ensure the technical stability of the code.

Types of testing performed at this stage include:

• Unit Testing – checking individual functions or code fragments for correct operation.
• Component Testing – analyzing larger blocks of functionality that combine multiple parts of code working together.

Quadrant 2 (Manual and Automated)

At this stage, the emphasis is on business requirements, which testers receive from the customer both before and during development. User-oriented scenarios are created and executed either manually or through automation.

This quadrant includes the following types of testing:

• Pair testing – two specialists test the software simultaneously, exchanging ideas for faster error detection.
• Scenario and workflow testing – verifying whether the program’s behavior aligns with business requirements.
• Verification of user stories and prototypes – assessing whether they meet the expectations of future users.

Quadrant 3 (Manual)

The third stage provides feedback for the first two. Testing is conducted in several iterations, after which the team improves the code. Although this stage is often associated with preparing for automation, the process itself is mostly manual.

This quadrant includes:

• Usability Testing – evaluating the intuitiveness and ease of use of the interface.
• Collaborative Testing – close interaction between testers, the development team, and stakeholders.
• User Acceptance Testing (UAT) – verifying whether the product meets the expectations and needs of end users.
• Pair Testing with Customers – working side by side with clients to quickly gather feedback.

Quadrant 4 (Tools)

The final stage focuses on verifying the non-functional characteristics of the product, particularly its reliability, security, and performance. Specialized tools are used here for in-depth analysis.

This quadrant includes:

• Security analysis
• Scalability testing
• Infrastructure verification
• Data migration assessment
• Non-functional testing – including load, stress, and performance testing.

These four quadrants allow for coverage of both functional and non-functional aspects of development, ensuring comprehensive testing in an Agile environment.

5 Key Types of Testing in Agile

Several approaches have been developed for implementing Agile testing, each offering its own advantages depending on the context of the project. Below are four of the most popular methodologies actively used today. Although none of these methods are universally applicable, they serve as an effective foundation for building a custom-tailored testing strategy.

Test-Driven Development

In this approach, test cases are created before writing the main code. The methodology includes three sequential stages:

• defining what exactly needs to be tested
• forming a user story
• creating a unit test
• writing the code that allows the test to pass;
• refactoring

This process ensures that every part of the code is tested and improved gradually in clearly controlled steps.

TDD is typically applied to unit and component testing, which is often automated using specialized tools. This approach helps ensure that the functionality is implemented correctly and meets the requirements.

Acceptance Test-Driven Development

ATDD is a variation of the TDD (test-driven development) approach, which enhances team collaboration in an Agile environment. Here, clients, developers, and testers jointly define acceptance tests, focusing on customer needs. Only after these tests are created does the team proceed to develop functionality, which ensures a clear understanding of requirements and minimizes the risk of errors. Afterward, functional tests are conducted.

Acceptance testing highlights:

• requirements are very clearly analyzed without any ambiguity
• acceptance tests serve as a guide for the entire development process
• encourages collaboration among cross-functional team

In addition, this approach simplifies the creation of test scenarios and allows developers to better understand user expectations, reducing misunderstandings in the process.

Behavior-Driven Development

This is a logical continuation of the TDD and ATDD approaches, focusing on achieving expected business outcomes. At the core of this method is describing system behavior in language that is understandable to all project participants. Testing is performed according to described user behavior scenarios.

The BDD process includes five main steps:

1. Formulating expected behavior.
2. Writing the scenario steps.
3. Running the test with the expected failure.
4. Implementing the functionality to pass the test.
5. Retesting until success is achieved.

Uncover specifics

• The Ultimate Guide to Acceptance Testing
• ATDD vs TDD: Understanding the Key Differences
• Behavior-Driven Development (BDD): Meaning, Benefits & Best Practices
• Exploring TDD vs BDD: Which is Right for You?

Exploratory Testing in Agile

This approach involves continuous learning during testing: the tester simultaneously creates and executes tests, analyzes the results, and plans further actions based on them. Exploratory testing is not based on predefined scripts — instead, it allows for a creative approach to discovering bugs that traditional testing might miss. This method makes it possible to flexibly assess the product’s working condition and how it will behave in real use.

Session-Based Testing

This approach extends and structures exploratory testing by providing it with clear boundaries. To avoid chaos, each testing session begins with defining a clear objective (a charter), after which the tester focuses solely on its completion for a limited time.

The results of each session are documented, and the tester reports to the lead afterward. Such structure ensures that no part of the product is overlooked and allows for effective progress management in testing.

Agile Testing Supports Continuous Testing

Agile testing is based on the idea that continuous verification is an integral part of development and is as important as writing code. Within Agile methodologies, testing is tightly interwoven with the development process, allowing bugs to be identified at early stages and on a regular basis. This approach enables testers to detect issues throughout all stages of product development, significantly speeding up its release readiness.

By combining continuous integration and continuous delivery with flexible testing approaches, development teams can ensure that their software product is always ready for release and can easily adapt to any changes or new market demands.

Agile-focused testing practices – building resilience and optimizing team output.

Thus, the continuous testing inherent to the agile method allows creating a product that is both high-quality and fully meets the customer’s expectations.

Advantages of Agile Testing

Implementing Agile testing brings three simple yet significant benefits: a satisfied team, a higher-quality product, and faster time-to-market. This Ideal Trio is a strong argument for building an effective Agile testing strategy.

1⃣ Higher-Quality Product

Thanks to continuous feedback, Agile allows errors to be detected early in development. Testing is launched simultaneously with code writing, so bugs are eliminated immediately rather than accumulating until the final stage. Each product iteration undergoes a complete cycle of testing and improvement. Continuous verification and close collaboration among stakeholders facilitate a better understanding and the development of a truly high-quality solution.

2⃣ Fast Delivery

Unlike the waterfall model, where months or even years can pass between development and launch, Agile allows this gap to be significantly reduced. The product is gradually improved during the development process, guided by regular user feedback. This helps to quickly adapt to market needs and deliver the solution to end users in the shortest possible time.

3⃣ Happier Team

The final principle of Agile testing is job satisfaction. Constant interaction among team members creates an atmosphere of collaboration, trust, and mutual support. This approach not only boosts productivity but also makes the workflow more comfortable and inspiring.

As Lisa Crispin and Janet Gregory noted:

“A team that guides itself with agile values and principles will have higher team morale and better velocity than a poorly functioning team of talented individuals.”

Transition to Agile Testing

Remember, every company is its own separate world, so the path to agile thinking will be unique for each. Therefore, don’t be afraid to improvise and adapt everything to suit yourself!

Communication within the team and working side by side – that’s everything for us!

In Agile philosophy, the main thing is people. It is they, living people, who respond to business needs and essentially steer the development process. Therefore, if we want to cultivate agile thinking for testing, it is extremely important that everyone’s voice is heard.

Agile is all about ensuring the client is satisfied by receiving software that works without long pauses.

And for that, testers need to learn not to stay silent but actively communicate. Because the goal is the same for everyone – to create a truly great product and provide users with best practices.

Forget about those times when departments sat in their own “cubicles” and everyone was on their own. If we choose the Agile path, communication is alpha and omega. Agile requires the team to work as a single organism, not that each tester is by themselves or each department works alone.

Quality is the shared responsibility of the entire team, not just the tester.

When everyone is together as one team, this not only helps to achieve the main goal – to deliver a valuable product to the user – but also protects against delays in work.

Moreover, such an approach allows squeezing the maximum from the process: to find product defects faster and, most importantly, to work proactively, preventing problems rather than just fixing them afterward.

What Agile Teams Need to Run Like Clockwork?

• Have clear common goals and intelligently distribute work among teams (if there are several). This provides autonomy and ensures that no one duplicates the same work, creating unnecessary dependencies.
• Remove walls between departments. To succeed in the agile transition, it may be necessary to reconsider the usual communication culture and even the company structure to support teamwork.

If you manage to successfully transition to agile rails, there will be many advantages. And by developing an agile mindset and implementing agile processes, these advantages can be fully realized.

What might come in handy to establish an Agile testing process?

→ Tools for collaboration and integration.
→ Visual boards (so everyone can see what’s going on).
→ Short Daily Stand-ups between teams.
→ Joint release planning for all teams.

Learn to Change and Develop Agile Quickly

Training

Perhaps the best way to smoothly transition to agile rails is to undergo proper training. If you want yourself and your team to develop the right agile mindset for testing, good training will help a lot here.

Unlike what testers of the “old school” might be used to, agile testing is not about final checks before release or just bug hunting. It happens continuously, is woven into the development process itself, and does not wait for the finished product.

Why so? Because agile testing is primarily a tool for preventing problems, not just detecting them. It helps improve individual parts of the product and the testing approaches themselves. Therefore, training will be useful for everyone who wants to move to Agile.

Fast feedback

The agile process also relies on fast feedback, which we have known already. Since the product is tested continuously, testers need to learn to respond instantly and adapt – this is the key to a successful transition.

Continuous testing requires changes: in people, in processes, in technologies. Therefore, cultivating an agile mindset to implement these changes is extremely important.

As part of development, automated tests that provide quick feedback considering risks are critically important in Agile. When testing is integrated into the development process, the team can be more confident that the user experience is reliably protected.

Focus On a Working Product, Not Mountains of Documentation

Usually, when software products are created, there is an attempt to document them thoroughly for development and delivery.

Creating all this paperwork can take a lot of time because the list of necessary documents is quite large: technical specifications and requirements, interface design documents, documentation and testing plans.

The time and attention consumed by this documentation often cause delays in development. Although documentation is still needed in Agile, the approach to it is simplified to avoid such slowdowns.

Besides, the tester can focus more on the software itself and on those actions that truly add value and, as a result, make clients happy.

Smart documentation plays an important role in agile testing, allowing the focus to remain on the end product.

In agile projects, the test plan is usually very concise, so it is recommended to supplement it with a strategy describing exactly how the system should be tested. This follows from how agile projects function, especially the fact that testers work in short cycles (iterations).

Documents commonly used in Agile testing may include:

• Test strategy (how we will test the system)
• Test plan (concise)
• Checklists for setup and regression testing
• Test specifications.
• Ideas for exploratory testing
• Test logs and lists of found issues

Responsibilities of an Agile Tester

An agile environment requires that a typical Agile testing professional has to meet the following traits:

Conclusion

The Agile methodology has gained wide popularity as an effective approach to project management not only in software development but also in many other fields. Its natural flexibility and ability to respond promptly to changes make this model one of the most relevant in today’s world.

With proper implementation and sincere commitment of the team to its principles, Agile can provide numerous benefits and allows teams to remain flexible, resilient, and productive even under challenging conditions.

The post Agile Testing: Methodologies, Real-World Practices & Performance Insights appeared first on testomat.io.

Suppose you have created an e-commerce application, but didn’t test its performance, UX, and other aspects thoroughly enough. With a good marketing strategy, many users will likely download and install your app. However, according to statistics, 90% of users will delete it right after experiencing a negative user experience. This includes slow loading speed, bugs and crashes, an inconvenient user interface, etc.

To avoid such a situation, you need to make sure you build a strong QA team where everyone works toward achieving quality standards according to their responsibilities. In turn, these responsibilities are defined by the roles of the team members in the project. Let’s look at the main ones.

What is QA Role And What Are Its Key Types?

Usually, when it comes to the quality assurance process, it is common to refer to the position of a QA tester. However, it is obvious that a single specialist is not able to perform absolutely all tasks in the project — from writing test cases to test automation and managing the workflow.

That is why, in every project, quality assurance responsibilities are divided among several Quality Assurance specialists.

What Is the Role of a QA Engineer?

A quality assurance engineer is a member of the testing team whose direct responsibility is to perform automated and manual testing. Based on the results of software tests, they must identify potential issues in the software product and report them to the software development team.

A key feature of this role is close collaboration with developers, analysts, and project managers. This is necessary to thoroughly verify the implementation of the functions of the digital solution.

QA Role in Software Testing and Responsibilities

• developing and executing test cases
• identifying, reporting, and verifying defects
• performing automated and manual testing
• collaborating as a team to maintain the highest quality standards.

Necessary Skills for the Role of a QA Engineer

• Experience with test automation tools (Playwright, Selenium, Cypress, Cucumber, etc.), bug tracking systems (e.g., Jira), and other platforms used in the workflow.
• Knowledge of best practices of manual testing.
• Years of experience in test automation.

Test Analyst: QA Role Description

These specialists focus on analyzing business logic and software product requirements. Based on these, test scripts are subsequently created. One could say this is the cornerstone of QA processes. After all, clearly formulated requirements are the key to verifying whether the final product meets user and business expectations.

The role of a software quality analyst is usually most significant in the early stages of the software development life cycle. It is at the beginning of product development that it is important to define the requirements.

The Role of QA Analyst: Responsibilities

• understanding business requirements
• writing test scripts based on them
• performing functional and non-functional testing
• creating a test plan.

Necessary Skills QA Analyst

• The ability to apply critical thinking and analytical skills to precisely identify user and business needs.
• Technical expertise (experience using defect tracking tools and TMS, working with user stories, skills in test design and documentation, etc.).
• Teamwork skills for effective communication with the development team and other software testers.

What is the Role of a QA Lead?

Like any leader, a QA Lead must manage. Due to the specifics of the industry — they manage the work of QA team members. A lot depends on this specialist in a project. Will the deadlines be met? How well will the team manage to optimize testing efforts? Will tasks be distributed correctly? They also act as a link between software testers and stakeholders.

QA Lead Responsibilities

• managing the QA team
• optimizing testing activities
• assigning tasks
• mentoring junior team members
• controlling the alignment of testing strategies with project goals
• informing stakeholders about the testing progress.

Necessary Skills

• Experience in developing testing strategies.
• Technical skills in running automated and manual tests.
• Strong leadership qualities.
• Time management skills.

QA Manager Role

A QA or test manager is a specialist responsible for literally all aspects of the testing process. They develop strategic planning for quality assurance activities. What does this include? It involves overseeing the entire team’s work, managing the budget, evaluating the readiness of the application for release, and much more.

The quality of the QA manager’s work determines how well the quality assurance goals align with the business requirements.

QA Manager Responsibilities

• defining overall quality assurance processes
• managing the project budget
• allocating resources
• coordinating actions with cross-functional teams
• developing internal quality standards
• conducting audits.

Necessary Skills

• Project management skills.
• Experience in building an effective QA team.
• Deep understanding of various types of testing.
• Knowledge in the field of test management.

Test Architect – A Key QA Role in Agile

Their task is to create and maintain a unified testing ecosystem. This specialist is directly involved in selecting optimal test execution tools, automation frameworks, CI\CD platforms, and more. The scalability of the testing ecosystem in a project largely depends on the test architect. Their focus also includes maintainability and efficiency.

Thanks to this team member’s deep technical expertise, they serve as a true mentor to other specialists, such as automation engineers.

Test Architect Responsibilities

• ensuring a reliable testing infrastructure in the project
• selecting tools and technology stack
• supporting the scalability and efficiency of systems
• implementing best practices in QA processes.

Necessary Skills

• Experience working with popular frameworks, test management systems, and other tools.
• Understanding how CI\CD pipelines work and the ability to integrate test automation into them.
• Skills in designing test architecture.

Software Development Engineer as a Role of QA in Agile

A Software Development Engineer in Test, or SDET, is a specialist in software engineering engaged in test automation. What are their responsibilities? Let’s break it down. First, the SDET writes and maintains test code. Second, they develop testing tools. And finally, another area of responsibility is unit and integration testing.

These QA team members actively participate in the development process. Often, they automate tests and verify the code even before the user interface is created.

SDET Responsibilities

• development of automated tests;
• creation of testing tools;
• collaboration with the software development team for code-level testing;
• participation in unit, integration, and API testing.

Necessary Skills

• Expertise in test automation across various types of testing.
• Collaboration with the quality assurance team to ensure the final product meets high standards.
• Deep knowledge of scripting languages.
• Experience with test automation tools, testing frameworks, etc.
• Understanding of the intricacies of the software development life cycle.
• Creating a Premium Product and QA Role in It

In the previous section, we discussed the significance of each QA role on a project. However, they all share a common goal: they all strive to develop high quality digital solutions.

So, what aspects of the project are under their responsibility?

Core Areas of Responsibilities for QA Testers

Regression testing

Regardless of the QA role, every member of the testing team must ensure that changes made do not break existing functionality. For this, it’s important to:

→ refresh regression test sets promptly
→ perform this type of testing after every build
→ prioritize areas for testing based on changes in the codebase.

Performance testing

How does the application perform under expected load? And under peak load? The QA team must address these questions through performance testing. In this process, they should:

→ develop performance test scenarios
→ use specialized test execution tools
→ identify and analyze bottlenecks in the system.

User acceptance testing (UAT)

Each team member, whether a test engineer or manual tester, must support users in verifying the digital solution’s alignment with their expectations. Specialists can help by:

→ preparing UAT test scripts and environments
→ familiarizing users with test cases
→ gathering feedback.

Exploratory testing

If predefined test cases do not produce results, the QA team should conduct testing based on their expertise. This helps uncover edge-case issues. To do this, they should:

→ schedule exploratory tests during sprints
→ identify areas most prone to errors
→ clearly document the results obtained.

Non-functional testing

To be considered a high-quality digital product, simply implementing the required functionality is not enough. It is also important to verify its availability, security, scalability, etc. For this, testers should:

→ check the application’s behavior under various network conditions
→ perform security testing
→ conduct accessibility checks, etc.

Communication with developers

The responsibilities of a QA professional go beyond identifying defects; they must promptly inform developers to resolve the issues quickly. Afterward, they have another task — to verify the fix. To ensure effective communication on the project, it is important to:

→ actively participate in daily standups and other meetings
→ provide quality defect reports
→ provide timely feedback.

Creating reports

How should the testing process ideally be? Transparent to all stakeholders. They should be able to track the progress of testing, the status of detected defects, and the readiness of the application for release. To ensure this, it is necessary to:

→ thoroughly document testing results (for example, preparing a test summary report)
→ provide stakeholders access to dashboards
→ use specific metrics (e.g., the percentage of successful tests, defect density, etc.).

Application testing best practices

This includes using the best test execution tools, automation frameworks, TMS, CI\CD tools, etc. The QA team must also select the most appropriate testing methodology and techniques for the project. For this, it is important to:

→ ensure traceability between requirements and tests
→ set up CI\CD integration
→ use version control for test artifacts.

Planning and executing tests

All members of the testing team must contribute to planning and executing tests according to the development methodology followed on the project (Agile, Waterfall, etc.). To achieve this, the following steps are necessary:

→ develop test plans
→ execute tests according to software development stages
→ monitor progress and modify the test plan as needed.

Interaction with all stakeholders

Besides developers, the tester — regardless of their QA role — must act as a liaison between technical and business groups. This ensures that all departments understand the quality assurance challenges. Achieving this requires the following:

→ maintain communication with all stakeholders
→ hold various meetings, including retrospectives
→ communicate technical defects in a format understandable to non-technical specialists.

QA Tester Role at Each Stage of the SDLC

It is a mistake to think that software test engineers, test analysts, QA lead, and other quality assurance professionals only participate in the testing process. Disagree? Let us quickly prove our point.

Conceptual Blueprinting

The work of a QA specialist begins at the very early stage of SDLC (Software Development Life Cycle) when planning and designing the software product. What activities does the QA specialist participate in? First of all, it involves defining business requirements and acceptance criteria. Then, they review the specifications and design documentation. This helps identify issues at the very start of the process.

Additionally, their responsibilities include identifying potential risks and creating a test plan based on the defined requirements.

Build Execution

Even at the coding stage, QA professionals are needed. They must closely collaborate with the development team. Thanks to this collaboration, the tester can understand the implementation details and ensure that the requirements are properly transformed into code.

Since testing in Agile runs parallel to development, test cases should already start being prepared at this stage. It is also recommended to verify the coverage of unit tests to ensure comprehensive testing of the core functionality.

Quality Validation

This is the actual quality assurance process. It involves performing various types of testing, followed by registering detected defects, reporting them to developers, and controlling the implemented fixes.

If the project has test automation, this is also added to the QA specialist’s responsibilities – in particular, the quality assurance engineer.

Solution Launch

The release of the digital solution is possible only after thorough verification of its readiness for deployment in the production environment. For this, testers perform smoke testing.

It is also important to create rollback plans in case critical failures are detected.

Operational Assurance

Even after the software product is released, the work of the QA specialist on the project does not end. After the launch, they should monitor the application’s performance, collect user feedback, and analyze various incidents.

This approach helps identify the root cause of the problem and, subsequently, update test cases to cover missed scenarios.

TOP Skills Required for Each QA Role

To build a career in quality assurance, even beginner software testers must work on improving certain skills and abilities.

Technical Expertise

A QA specialist will not be able to perform their direct duties without understanding the basics of software development. What should you be knowledgeable about?

• Popular programming languages. Practice coding in Java, Python, or JavaScript – this will be useful when writing and executing test scripts. If you are just starting your career path, pay attention to the most common languages. For example, study the ranking according to the TIOBE Index:

• Development methodologies. It is important to understand what the work of the development team means in methodologies like Agile, Waterfall, etc. How will QA processes differ? This will help adjust the testing strategy to the characteristics of the working environment.
• Specific tools. Learn to work with Jira and CI\CD pipelines. These are used not only in development but are also actively applied in testing. Such skills also enhance communication on the project.

Testing Skills

By developing the necessary skills for performing direct professional duties, you will be able to confidently advance in your career. These include:

• Experience with popular testing tools. This includes test execution tools, TMS, and automation frameworks.
• Knowledge of various testing methods and types. A qualified QA specialist should be able to test both functional and non-functional aspects of an application. It’s also important to understand the crucial role of performing different types of tests – from unit tests at early stages to integration and regression tests.
• Expertise in test automation. Today, the focus in QA is on test automation. This helps accelerate test execution, improve accuracy, and reduce required resources. Therefore, experience in creating and running automated test scripts is essential.

Soft Skills

Lastly, alongside technical knowledge and experience, it’s important to have certain personal qualities. These include:

• Communication skills. Without these, collaboration within the team, with developers, and with stakeholders is impossible.
• Problem-solving ability. A QA specialist must react quickly to problems and help resolve them in a timely manner.
• Time-management skills. If you cannot organize your time (and for some specialists, the team’s time), regardless of your QA role, the project deadlines are at risk.
• Critical thinking. A tester must be able to critically assess the product being created. When necessary, they should challenge existing assumptions and make well-founded conclusions.

Let’s summarize: What is the role of QA in software testing?

The role of the QA specialist is the key to creating a software product that meets high standards of quality. A qualified QA engineer specializes in performing manual testing and its automation. A test analyst gathers product requirements and ensures their implementation. QA Lead and QA manager are responsible for organizing and coordinating work processes.

Description of QA role means that the test architect and SDET are also important on the project. The first works on creating the testing ecosystem, while the second focuses on test automation.

Together, they create a seamless mechanism that contributes to the development of a high-quality final product.

The main point is, don’t forget. You always have room to grow. By continuously working on your knowledge and skills, you can progress in your career from a QA tester to management roles.

The post The QA Role in Modern Software Development Lifecycle appeared first on testomat.io.

At the same time, software development accelerates and becomes more iterative and user-centric due to the growth of Agile methodologies and Artificial Intelligence (AI). The test pyramid remains a key tool for effectively organising test automation efforts. Each QA team can adapt this approach to better align with their ongoing Software Development Cycles (SDLC) and Continuous Integration (CI\CD) processes.

Let’s explore the principles of the testing pyramid in today’s dynamic software development landscape in more detail

Understanding the Testing Pyramid Definition

The test pyramid, which many link back to Mike Cohn, is an important idea in software testing to show how to match requirements, along with the different types of tests in a robust software testing strategy.

The testing pyramid suggests using a layered method to distribute testing work across various levels. Following the pyramid, development teams can create a strong test plan that helps them stay balanced and improve efficiency. Namely, it is one such approach to balancing Automated Testing.

Pay attention to the arrows in the picture! The pyramid is built to highlight the importance of evaluating testing costs. Testing is generally “cheaper” closer to the base layer.

Setup highlights the need to find bugs early in the development cycle, as test cost is lower and test speed is higher. Similarly, Unit tests focus on smaller components and are easier to write faster tu run and cheaper than E2E and manual testing efforts. This is considered a best practice that gives us the best ratio of time spent in testing and debugging versus the likelihood of finding bugs. By combining different testing levels, like unit tests and UI tests, we can ensure good test coverage. This is also one of the pillars of product quality.

Testing Pyramid Importance in Modern Development

→ Enables a smart approach to automated testing.
→ The pyramid’s structured layers help to utilise resources wisely.
→ It emphasises the necessity for automated testing, particularly at the lower levels.
→ Provides quick feedback, enabling teams to identify and resolve issues early in the process.
→ Prevents bugs from progressing to later development stages, resulting in a reduced need for slow and costly manual testing later on.

The Layers of the Testing Pyramid Explained

At the very beginning, before starting automation, we should conduct minimal statistical analysis at the requirements level to be sure that our application will work exactly as end users expect.

At the bottom are automated tests. It focuses on unit tests. These are the building blocks of a solid testing strategy. They check individual components, by themselves, ensuring each code unit works correctly as expected in isolation.

Next, we go up to integration tests. These tests check how different modules of the software work together. They make sure that all the parts function well when combined, and the data from the API flow successfully between different units or modules without errors.

At the top of the pyramid, we find UI tests. These tests validate how the system works from the user’s point of view. UI tests act like a user touching the screen to see if everything behaves as it should and provides a smooth experience.

According to the testing pyramid, the most tests are on the unit-level, fewer tests on the integration level and the least amount of tests on the system level.

— Does that mean that we should write tests for all levels?
— No! We just should select carefully which functionality is tested on which level.

If we can show a problem with a unit test, we use a unit test. Only if a problem cannot be shown with a unit test we go one level upwards by using an integration test or even a system test.

For failing tests we work our way up the testing pyramid. First, all unit-tests need to pass before it makes sense to start debugging either the integration or system tests.

Using this flow, you can debug and fix issues most effectively and efficiently.

Generally, there is a trade-off between speed and confidence, so you can’t skip any level of testing. Gradually, move up; however, you can decide how much focus to place on the different levels. Essentially, it’s about finding the right balance between your time investment and the optimal return in terms of confidence in your software application. That’s what the different shapes of testing signify.

Implementing the Testing Pyramid

Implementing the testing pyramid is a step-by-step process. During this process, it’s important to choose the right tools and technologies. They should help support your automated testing efforts. A strong testing system is very important to ensure your testing is efficient and reliable. 

Everything sounds good in theory. But in real life, it is a bit complicated, so let’s go deeper into the testing pyramid levels.

Unit Testing: The Foundation of the Pyramid

Unit testing is the foundation of the testing pyramid. It starts with creating a strong base of unit tests. This process tests the smallest parts of an application, focusing on individual components or modules. Then, we will go higher and combine these pieces, checking how they work together. The goal is to make sure they work as expected. It is important for creating reliable and easy-to-maintain software.

By checking the behavior of these individual units of code, developers can find and fix bugs early in the development cycle. At this stage, issues are easier and cheaper to fix. A good test suite that covers all parts of a unit’s functionality helps developers change code confidently. They will know that any unexpected problems will be found early.

The advantages of strong unit testing go beyond just finding bugs. It also helps create clean code design. Developers are motivated to write modular and loosely connected code, making it simpler to test and maintain. A solid foundation of unit tests is key for any software project. It ensures that developers can make changes and improve the system without worrying about causing new problems.

Integration Testing: The Middle Layer

While unit tests look at single parts, integration tests check how these parts work together and share information. Integration tests are essential for finding problems that happen when separate units join to make bigger modules or when they connect with outside services or databases.

A key part of integration testing is using real test data that mimics how people actually use the system. This approach helps to find issues with data consistency, how well components communicate, and how they manage outside dependencies.

By finding and fixing integration issues early, development teams can avoid expensive repairs later in the software development life cycle (SDLC). At that point, bugs are harder to find and fix, and they can lead to bigger problems.

UI Testing: The Apex of the Pyramid

At the top of the testing pyramid is UI testing. This type of testing looks at how the application behaves and how users experience it. UI tests imitate what users do, like clicking buttons, filling out forms, and moving between different screens. This helps make sure the application works well and gives a smooth user experience.

Setting up UI tests is often more complicated than unit and integration tests because they check everything from start to finish. They need special tools and frameworks that work with the application’s user interface. This makes them more sensitive to changes, which can cause them to break easily.

Even so, UI tests are crucial for checking important steps of user interaction. They help ensure the application meets the expected quality standards. A good UI test suite can address many parts of the user experience, including usability, accessibility, and how well the application works on different browsers and devices.

How Agile Methodologies Influence Testing Approaches

The rise of Agile methods has changed software development and how QA teams test it. Traditional ways, which followed a straight path, have been replaced by iterative and step-by-step methods, and now testing happens all the time during the development cycle. This change highlights the need for early and regular testing during development.

Agile teams know that testing early and often helps find and solve problems fast. They mix testing into the development process from the start. This way, they keep a steady pace in development. Instead of only doing manual testing at the end, Agile teams use automated tests throughout the process. This gives them more confidence when releasing software.

Test automation is key in Agile testing. It plays a very important role in getting fast feedback, managing quick changes and frequent releases.

By automating tests that take a lot of time to run, teams can spend their energy on exploratory testing, usability testing, and other important work that needs human insight and creativity.

In addition, new Agile methods focus on teamwork. This breaks down old barriers and encourages everyone to share the responsibility for quality. Developers, testers, and business people work closely together on all layers of the testing pyramid. Working together like this allows for finding and fixing problems sooner, leading to quicker feedback and better software quality. This teamwork helps everyone stay on the same page about the project’s quality goals, leading to better and more efficient testing efforts.

Shift-Left Testing Strategy within the Testing Pyramid

Shift-Left Testing emphasizes moving testing activities earlier in the software development lifecycle, even before the start of the code stage. When applied to the Testing Pyramid, it focuses on investing more in unit and integration tests — the lower layers of the pyramid — where it is expected.

In Agile settings, the testing pyramid is still an important tool. Anyway, its formulation undergoes.

Evolution of the Testing Pyramid in Agile Environments

The testing pyramid has changed to support Agile ideas. Thus, in addition to the classic testing pyramid, sometimes Unit, Integration, E2E testing are presented in alternative forms like the Trophy, Hexagon, Diamond, and others have also emerged to represent different testing strategies and priorities.

However, it is important to fit these interpretations into the ongoing workflow.

Challenges and Solutions in Applying the Testing Pyramid

The testing pyramid is a helpful guide, but using it can be tough. It is important to know the common mistakes and follow good practices to work through them. You need to balance the different testing levels to get the best test coverage.

To tackle these issues, you must really understand your application and what testing it needs. Your testing strategy should focus on being flexible and improving all the time.

Common Pitfalls and How to Avoid Them

• Using too many UI tests. It is a common mistake. While UI tests are important, having too many can make the testing process weak and slow. Since UI tests are at the top of the pyramid, they should be fewer and more focused than integration or unit tests.
• Ignoring integration testing. This type of testing is important to make sure different parts of the system work well together. If you skip this step, some bugs may not show up until the application is nearly finished. This can lead to expensive corrections.

To avoid these problems, start with a strong group of unit tests as the base of your testing efforts. A balanced testing strategy is essential for good test coverage and for creating high-quality software.

There are challenges to face, like common mistakes, but using the right tools can make testing better.

Tools and Technologies for Effective Automation Testing

The ever-evolving landscape of software development offers a plethora of tools and technologies designed to streamline and enhance the testing process. Leveraging these tools is essential for software developers to maintain the efficiency and effectiveness of their test automation pyramid.

Selecting the appropriate tools depends on various factors, including the programming languages used, the application’s architecture, and the specific testing needs of the project.

Trends Shaping the Testing Landscape

Leading trends are changing software development. They are affecting how we will test and ensure software quality soon.

• The rise of AI and machine learning presents new challenges for testers. Testing AI-powered applications needs special techniques and tools. We need these to check their behavior and make sure they work well.
• More people are using cloud computing. This adds new challenges in the testing process. We must think about things like scalability, reliability, and security in cloud-based environments.
• As development and operations start to blend with DevOps, testing is becoming a key part of the continuous integration and continuous delivery (CI\CD) pipeline.

This means we must shift to automated testing from the earliest stages. It also encourages teamwork between developers, testers, and operations teams. This way, we can ensure fast and smooth software delivery.

The Future of Testing Pyramid Usage

As software development moves forward, the testing pyramid’s future, as we considered on top, will focus on improving test automation. Agile teams need quick feedback, which means an advanced test reporting and analytics dashboard with reach test metrics set on different testing levels, like unit tests and UI tests, we can ensure good test coverage.

In today’s software development, the testing pyramid plays a key role by putting test automation at the base. They should also use manual testing for complicated cases. Agile teams must find a good balance to make the testing process smooth and keep the software quality high.

Adapting the Testing Pyramid for New Technologies

New technologies ask us to change how we test things. As technology becomes a bigger part of software systems, we need our testing strategies to adapt as well.

Changing the testing pyramid for new technologies means we should mix old testing methods with new tools. This helps us handle the special challenges that come with new tech.

If we keep learning about new trends and stay flexible, the testing pyramid can still help us deliver great software, even with all the changes in technology.

Conclusion

In the quick-moving future, keeping up with new AI trends will be key to shaping testing practices. The Testing Pyramid will remain very important in future software development, ensuring speed, flexibility and quality in Agile environments.

The post Test Pyramid Explained: A Strategy for Modern Software Testing for Agile Teams appeared first on testomat.io.

— Why is this approach to development so in demand among various teams?
— What makes it unique?

Let’s break it down further

What is Application Lifecycle Management?

ALM is an approach to the development process that covers all its stages, from initial planning to the final deployment of the application. However, saying that ALM is simply an approach to application development is not enough. It is a whole philosophy embedded in Agile methodologies, which allows teams to create high-quality digital solutions.

It’s common to equate ALM with software development. Yet this simple approach is too limiting; ALM is much more than this. In fact, an application’s lifecycle includes the entire time during which an organization is spending money on this asset, from the initial idea to the end of the application’s life

David Chappell,
the Principal of Chappell & Associates

Note. ALM should not be equated with Product Lifecycle Management (PLM). What is the difference? The former focuses solely on the lifecycle of an application, while PLM is a more comprehensive concept that covers not only software development but also other aspects of the product lifecycle, such as hardware, manufacturing, product marketing, etc.

Watch the expert’s video to learn more: What is Application Lifecycle Management (ALM)?

Difference Between ALM VS SDLC

Another common misconception is the software development lifecycle (SDLC). Let’s explore why:

What conclusion can be drawn from this? SDLC is a narrower concept that pertains exclusively to the creation of a digital solution. It can be considered a part of ALM.

Phases of Application Lifecycle Management

— What do you think the entire lifecycle of the application begins with?
— Right, With the idea
— So, Why not create something that helps achieve a specific goal? The phased work on creating a digital solution starts from its inception.

As seen in the table above, in most cases, ALM includes five phases. Let’s talk about them in more detail…

#1: Requirements Specification

At the first stage, it is necessary to economically justify the idea. That is, to answer the question: what do we want to achieve from this application? All stakeholders should participate in the discussion. Their expectations form the basis for the future product requirements.

Next, it is important to clearly formulate these requirements.

Often, the requirements specification has a hierarchical tree structure. That is, each requirement has its own sub-requirements.

However, teams that have implemented application life cycle management tend to prefer another approach. For example, it may be more convenient to:

• categorize the requirements (by specific functionality, module, etc.);
• structure them by priority (what should be implemented first, what can be done later).

This approach is more in line with Agile methodologies.

#2: Development Phase

Once the requirements are gathered, development of the software application can begin. At this stage, a distinctive feature of ALM will be total collaboration – different teams participate in the application development.

For example, ALM Processes participant’s responsibilities:

→ Project Manager handles financial matters, estimating the duration and cost of the project.
→ Development team members formulate key tasks for design and coding.
→ Testing team determines the scope of work for quality verification, preparing test cases.
→ Marketers and Customer Representatives ensure that the product meets the target audience’s requirements.

Also, before development begins, planning for the sequence of releasing new features is carried out.

#3: ALM testing

Testing and development of the software product go hand in hand in ALM. Testers check the quality of the solution after the release of each new feature or update. Any detected errors are immediately sent to the development team for resolution, after which the QA specialist runs the tests again.

To speed up and increase the accuracy of this process, it is advisable to use ALM testing software.

#4: Deployment

This stage involves releasing the digital solution to end users. How this will be implemented depends on the type of software product.

For instance, it could be a SaaS solution. It needs to be deployed on internal servers. Local applications require deployment, installation, and configuration on the client’s server. Mobile and hybrid products are distributed through app stores. There are other deployment methods as well, but we will not go into detail about them in this material.

#5: Maintenance of the Software Product

At this stage, the team faces one main task — ensure that the application meets user expectations after release! This involves performing the following actions:

• Timely detection of errors and their quick resolution.
• Planning future updates to improve the digital solution.
• Implementing new functionality based on user feedback.
• Discontinuing the use of the product (or its current version) and releasing another application/version using new relevant technologies.

The last activity is called the Retirement of the Product. It is a vital part of ALM.

Benefits of ALM

Thus, why implement ALM if you can continue working according to the familiar SDLC? If you’ve had this question, let us quickly present the key benefits of application lifecycle management.

Improved Communication on the Project

Mismatch between the final product and business requirements, missed deadlines, low team morale, etc. Admit it, you’ve probably faced these issues on projects at least once in your life. One of the reasons for each of them could be poor communication within the team and beyond.

Well, ALM helps prevent such difficulties and their consequences. Each application lifecycle management tool serves as a single platform for collaboration between developers, quality assurance engineers, project managers, and relevant stakeholders. Anyone involved with the product can participate in its creation: track progress, monitor project status, make suggestions, and more.

This helps prevent misunderstandings and contributes to achieving project goals.

Effective Project Planning

Proper planning of the software product’s work is the key to successful development. Clear project plans allow:

• proper prioritization
• accurate project time estimates
• effective resource allocation
• avoiding cost overruns
• tracking progress
• timely identification of issues
• promptly addressing emerging problems.

In other words, ALM allows teams to create a clear project roadmap, which they will then follow to maintain the correct development course.

Reliable ALM Software Testing

As you remember, quality assurance is an integral part of application lifecycle management. Moreover, QA processes in this approach are characterized by clarity and structure. This is facilitated by the use of ALM testing tools. These platforms allow test case creation, have features for managing test data and support test automation.

Risk Minimization

Is the development of the application associated with risks? The answer is clear. Yes. These risks can be caused by technical debt, poor requirements gathering, changes in business priorities, and more. All these risks can be effectively managed using an application lifecycle management tool. Typically, such platforms have enough functionality to identify, assess, and mitigate risks.

Continuous Process Improvement

Specialized tools allow the collection and analysis of many metrics. For example, users have access to project documentation, detailed test reports, and development time data. By tracking various indicators, team members can promptly identify issues with source code and other bottlenecks in the project. What’s the result? Increased team efficiency and improved the quality of the final product.

ALM in Software Testing

The role of ALM in testing is hard to overestimate. This approach ensures smooth integration of QA efforts into the broader lifecycle of an application. In other words, it guarantees that tests will be executed at each development stage.

The following components of ALM for testing are highlighted:

• Requirements Management. Application Life Management helps clearly define requirements and ensure their precise alignment with test plans. Common practice is linking requirements in Jira with the ALM test management tool to track their traceability.
• Test Planning. This activity involves developing a clear testing strategy and its objectives. The teams will need to determine which types of testing to use and create test plans. These plans are easy to document and track in an ALM tool for testing.
• Test Design. It’s time to write test cases and test scripts. Ready? Now you can check whether the application works properly.

• Test Execution. Managing test runs, monitoring their execution, and analyzing results — all of this is available in the ALM test management tool.

• Defect Management. Did you find a defect during testing? ALM implies documenting it, determining its priority, and providing recommendations for resolution.

• Test Automation. ALM supports the use of automated testing tools. This speeds up the process and improves the accuracy of quality assurance results.

• Continuous Testing. ALM perfectly aligns with Agile development principles. This approach fosters continuous testing throughout the development process.

• Reporting and Metrics. Detailed reports help teams identify areas for improvement by studying various metrics. These include test coverage, test execution status, defect trends, and more.

• Release Management. ALM QA testing ensures that all tests (including acceptance tests) have been conducted and that the digital product is ready for market release. Post-release testing is also possible. This allows tracking potential issues.

What is ALM Testing Tool?

An ALM testing tool is a platform that allows optimizing QA processes on a project. These tools help plan, track, and execute tests, as well as provide advanced test Reports and Analytics

In other words, it is a unified platform that combines all the functions necessary for testing teams: requirements management, test case creation, defect tracking, and reporting.

The Role of ALM Test Management Tool in Development

The tools used in application lifecycle management offer users comprehensive functionality. They help optimize all activities on the project.

Key aspects of development in which ALM platforms are indispensable:

• Requirements management. As you can see, this process is important not only for creating relevant test cases. It is crucial for the entire development process.

• Planning and scheduling. Detailed project planning is half the success. ALM tools allow you to create project plans, develop a schedule for implementing tasks, and allocate resources effectively.

• Version control. These tools easily integrate with version control systems. This is very convenient because you can revert to the desired version of the source code at any development stage.

• Test management. We’ve already discussed the role of ALM in testing. So, we will just remind you — the AML test management tool helps optimize test planning and execution. This guarantees high-quality final products.

• CI\CD practices. Tools allow you to automate the process of building, testing, and deploying code. This leads to faster development, early detection of defects, and reduced risk of errors during software delivery to end-users.

What else to expect from ALM tools? They help manage the release of digital products, ensure regulatory compliance, and are used for monitoring after deployment.

ALM Tools: What to Consider When Choosing?

If you need to choose an AML test management tool, ask yourself the following questions

• What is the size of my team? Larger or remote teams may require tools focused on collaboration, detailed reporting, and good scalability.

• What kind of project are we working on? Choose a tool based on your development methodology. For Scrum or Kanban workflows, you will need a more flexible platform. For a waterfall project, traditional planning and reporting will be more suitable.

• What infrastructure does the ALM tool need to integrate with? Assess whether the tool can be integrated with the CI\CD pipeline, version tracking system, and other services already used in the project.

• How much time will training and adaptation take? An AML test management tool with a steep learning curve is not the best choice, as it may slow down development.

• What features does the tool offer? Remember that ALM is a comprehensive approach covering all aspects of the application life cycle. Make sure the tool has sufficient capabilities, especially in areas such as test automation.

• Does the tool provide built-in reporting and analytics? Detailed test reports and data analytics are essential for informed decision-making. If they are not available, you may have to rely on third-party services, which is inconvenient.

• What if problems arise? Prioritize tools with a well-developed community and comprehensive documentation.

Next, we present a list of the best ALM tools that best meet the criteria mentioned above.

Top 5 ALM Testing Tools

We have selected five tools whose capabilities allow teams to effectively implement application lifecycle management in their projects.

Testomatio

The testomat.io test management system helps teams optimize their testing efforts throughout the entire lifecycle of an application. The platform bridges the gap between manual and automated testing, allowing users to run various types of tests in one place. It offers the following key features:

 Testomatio ALM test management tool key features:

• Test Case Management. The tool supports both manual and automated test cases, enabling users to create, organize, and manage them efficiently.

• Test Automation Integration. With just one click, manual tests can be converted into automated ones. Additionally, the TMS allows importing test cases from other testing tools.

• Defect Management. The system enables defect tracking from detection to resolution. Users can filter, cluster, and monitor defect severity for individual test runs or the entire project.

• Reporting and Analytics. Need to track testing progress? Use real time reports. Looking for insights after test execution? Comprehensive reporting is available. Users can also leverage live documentation and an analytics dashboard to monitor key metrics.

• CI\CD Support. Testomat.io seamlessly integrates with popular CI\CD tools like GitLab or GitHub, CircleCI, Jenkins and AzureDevOps enabling continuous test execution, real-time monitoring, and defect notifications.

• Collaboration. Human-readable reports, BDD support, data visualization, and integrations with tools like Slack enhance team collaboration on projects.

Jira

Jira is a highly demanded project management and bug tracking system among IT teams. It is most commonly used by development teams for working with requirements, defect management, and task execution control. And although the system does not offer a test automation function, this issue can be easily resolved by integrating it with a test management tool — for example, with Testomat.io.

Jira key features, as alm tool in testing:

• Test Case Management. Thanks to seamless integration with Testomat.io, users can easily manage test cases using a familiar tool. All they need to do is link them to user stories and Jira issues.

• Test Execution. Jira supports the management and tracking of manual tests. Automation is only available through third-party integrations.

  And many ALM test management tool providers give this opportunity.

• Defect Tracking. The platform allows users to track defects and integrate them with test cases. This enables control over the development process throughout the application life cycle.

• Agile Integration. As one of the most popular project management tools, Jira supports Agile development methodologies (Scrum, Kanban). Teams can link testing with sprints or user stories.

• Reporting and Traceability. The tool provides users with built-in reports that help track test coverage, test execution, and defect status.

Microsoft Azure DevOps

Microsoft Azure DevOps, formerly known as Visual Studio Team Services, is a set of tools for development teams that have implemented DevOps practices in their project. It allows managing source code, supports continuous integration, QA, and is used for release management.

Azure DevOps key features:

• Agile Project Management. Supports Scrum and Kanban for planning and tracking workflows.

• Test Management. The platform holds a top position as an ALM test management tool within the QA community worldwide. It allows managing manual tests, with the possibility of integration with testing tools for test automation.

• CI\CD Support. Automates pipelines for building, testing, and releasing software.

• Version Control. Enables code repository management through integration with version control systems.

• Defect Tracking and Reporting. The tool provides users with access to monitoring dashboards. With their help, you can track key project metrics and identify defects.

IBM Rational Team Concert

IBM Rational Team Concert (RTC) is a solution for collaborative management of an application’s lifecycle. The functionality of the tool meets the needs of teams at all stages, from planning to post-release support.

Key features RTC AML testing software:

• Collaboration. The platform offers users discussion boards and team rooms for collaboration. Notifications about changes or new comments also play an important role.

• Version Control. You can use the built-in version control system or integrate with an external service.

• Source Code Management. Users have access to the Code Reviews feature and integration with other IBM tools for source code analysis.

• Quality Management. Interested in comprehensive test management? Consider RTC as a tool for your project. However, it goes beyond a traditional namely ALM test management tool. With it, you can plan and execute tests, as well as track the progress and results of testing.

Tricentis

The Tricentis platform is a comprehensive solution for continuous automated testing. It is often used by teams due to its versatility. Here, different types of tests can be run, test cases can be managed, and results can be analyzed.

• Continuous Testing. The tool supports agile methodologies and DevOps. What does this mean in the context of QA? You can test individual functions or the entire application throughout the entire development cycle.

• Test Automation. To accelerate QA, you can automate your tests with Tricentis. Importantly, these can be any type of tests, such as functional, regression, and performance testing.

• Test Management. With the right AML test management tool, you will have complete control over QA processes. What can not say about Qtest from Tricentis. Plan and executing tests, identifying defects, tracking compliance with requirements, and generating detailed reports are quite curly with the Tricentis testing tools, admit their customers.

• Collaboration. Tricentis easily integrates with third-party services (such as Jira or Jenkins). As a result, testers gain access to real-time analytics, dashboards, and other collaborative features.

• Risk-based Testing. This approach to testing is fully justified. It allows you to prioritize test cases and focus on the most critical areas of the application.

You’ll find this valuable:

Comprehensive comparison of Qtest & Testomat.io test management system

Conclusion

ALM is an approach to creating digital products that covers far more aspects than the classic SDLC. Use it for clear planning, automation, and tracking of the entire lifecycle of an application, including testing.

Investing in a more advanced ALM test management tool is sensible if the company is on the way to a large-scale enterprise project and plans its long-term development with ALM as a single source of truth for the entire team, following the best practices of Quality Assurance.

The post What is ALM Test Management Tool, its Benefits | Top 5 of the Best appeared first on testomat.io.

— What is BDD in software development?

— How to focus on behavior effectiveness?

Understanding BDD

BDD software development is gaining increasing popularity due to its collaborative and all-encompassing approach.BDD, as an Agile development technique, involves the entire team in the process for a shared understanding of the project – developers, testers, and the business team, in other words 3 Amigos. This makes it possible to efficiently find and apply functionality that satisfies the requirements of every market participant and the flow of value.

Within BDD behavior driven development, a key point is defining the behavior of the system before the development process begins. This helps eliminate ambiguities in the requirements and synchronize the digital product creation process with specific business goals. The popularity of BDD frameworks like Cucumber or Behave can be explained by the fact that they allow for the development of pre-executable specifications.

BDD frameworks clarify the requirements for technical and non-technical team members, fostering test automation and a collaborative approach. Aligning business objectives with technical execution guarantees high-quality software, meeting set standards and expectations. This improves both the reliability and efficiency of the development process. Thus, BDD business-driven development is realized.

This methodology is an evolution of Test-Driven Development (TDD), but its main focus shifts from high test coverage to defining the behavior of the application.

Let’s define: What is BDD behavior driven development? and How does it work? Discover our visualization of the BDD development process below

Also, you can know the difference between TDD | BDD software development and the best qualities of the latter:

You might be interested in the topic:

• ATDD vs TDD: Understanding the Key Differences

Key benefits of BDD testing:

1. Improved communication.
2. Clarity of requirements.
3. Automation of acceptance testing.
4. Early detection of issues.
5. Better test coverage.
6. Stakeholder involvement.
7. Clear and maintainable test cases.
8. Alignment with business goals.

In the next parts of the article, we will explore these points in greater detail and more comprehensively — keep reading!

Behavior-Driven Development Process

Now we continue considering the main BDD development phases of the Software Development Life Cycle. This one encompasses three main phases:

1⃣ Discovery phase

During the discovery phase, the product owner establishes acceptance criteria for epics and user stories. In collaboration with the Agile team, they refine these during backlog refinement and clarification sessions, adding necessary details. This iterative BDD process ensures the comprehensiveness of the acceptance criteria and their alignment with the product requirements understood by the team.

2⃣ Formulation phase

The formulation phase begins when backlog stories near implementation. The team and product owner jointly create clear BDD scenarios (acceptance tests) to reduce uncertainty.

3⃣ Development phase

During the development phase, when backlog stories move into iteration, the scenarios undergo further refinement with detailed specifications. These tests are executed and verified within the same iteration.

The BDD (behavior-driven development) methodology places special emphasis on automating BDD scenarios. They are often automated, can be included in smoke and regression test sets, seamlessly integrating into the CI\CD pipeline. This approach promotes early detection of issues and their rapid resolution.

Let us group all the process details according to the phases where they are executed

BDD Automation Implementation

We suggest the following implementation steps that will help you get started with automation using behavior driven development BDD:

1. 1. Create a feature file with BDD scenarios. It is written in plain language and consists of a description, background, scenario title, and its steps. You can create a new test case in the TCMS Testomatio by selecting the appropriate template. The feature file should clearly define the scenario steps, including conditions Given actions When and expected results Then, ensuring a shared understanding of requirements. Here’s an example of the structure of a simple feature file written in Gherkin syntax:
   2. Automate feature file within steps definition. This file acts as an automation script that interacts with the software to check its behavior. During execution, each step defined in the feature file is carried out in the step file. You can either integrate existing automation scripts into testomat.io or develop new ones. This enables the automatic execution of test scenarios to ensure the software’s behavior is correct. All of them are initially generated with a skeleton structure by the command line prompt, containing exceptions for non-existing implementations, ensuring that tests fail until implementation. Then, methods for each step are developed to interact with the software. Assertions are added to verify the validity criteria of the scenario to confirm the correctness of the system’s behavior.
   3. Implementation of hooks. Implement hooks to perform setup before and cleanup after function and scenario execution to improve the overall reliability of automated tests. These hooks, defined with @Beforeand@After annotations, ensure better support, reusability, and consistency during test execution.
   4. Collaboration on dependencies. Work with the development team to identify and resolve any dependencies during the implementation of step definitions. This ensures that BDD scenario automation is aligned with the development implementation, leading to smoother integration and validation of software functionality.
   5. Integration with CI\CD pipeline. Testing using already automated feature files in TCMS testomat.io can be integrated through the interface settings with CI\CD platforms. This ensures the automatic execution of tests with every build, allowing for quick verification of new features after each code change.
   6. Execution of BDD acceptance tests. Verify that the software satisfies all required acceptance criteria. These tests should pass, ensuring that the defined scenarios are executed correctly and user requirements are fulfilled.
   7. Monitoring and reporting. You can also use the capabilities of TCMS testomat.io for tracking test execution and generating reports. The integrated reports will provide insights on whether the tests passed, helping quickly identify errors or gaps in development.
   8. Team collaboration. By testing with BDD, developers, testers, and business stakeholders continue their collaboration with weekly meetings to verify product requirement compliance, ensuring accuracy and efficiency in the validation process.

Following these steps will enable you to successfully implement feature files, organize automated BDD testing and ensure effective and accurate test execution:

From the very start, you need to initialize the Playwright project, which can be done by running the next command:

npm init playwright@latest

After that choose the programming language as Javascript when asked in the command line.

Next, you need to add project dependencies and establish configurations for test runners. Install Cucumber and REST Assured dependencies for application programming test interface.

npm i @cucumber/cucumber

Add the Cucumber extension to your VSCode, here you can see what choose our team:

Configure your cucumber.json file with the next settings:

{
  "default": {
    "formateOptions":{
      "snippentInterface": "async-await"
    },
    "paths": [
      "tests/features/*.feature"
    ],
    "publishQuite": true,
    "dryRun": false,
    "require": [
      "tests/steps/*.js"
    ],
    "format": [
      "progress-bar",
      "html: cucumber-report.html"
    ]

  }
}

Steps and Feature definitions:

Of course execute this test you can with CMD command:

npx playwright test

Recommended video on how to set up and build your first Cucumber, Playwright framework with an example and plain language of login functionality, Hooks implementation of web App scenarious.

The BDD integration with our test management solution allows you to track your test process efficiently at each stage:

For the implementation of BDD driven development automation, the following popular BDD frameworks are also actively used:

• Cucumber. One of the most widespread tools, using the Gherkin syntax for writing tests. It is compatible with various programming languages (Java, Ruby, Python). It offers wide integration with Visual Studio.
• SpecFlow. (WarningSpecFlow framework will no longer be available after December 31, 2024, it is their owner Tricentis’s position)A framework specifically developed for .NET platforms, allowing developers to create BDD scenarios for testing applications in C#.
• Behave. A tool for Python, enabling the creation of simple and understandable BDD scenarios, significantly simplifying test automation.
• JBehave. A framework oriented towards Java, developed to support BDD that allows writing scenarios in a natural language format. It provides integration with other automation tools, expanding its capabilities.
• Gauge. A flexible tool that enables the creation of BDD-style scenarios and facilitates test execution across various programming languages.

All of the above frameworks easily integrate with CI\CD systems, allowing test automation at each stage of the BDD development process.

Integration with CI\CD Pipeline

CI\CD automates the processes of code integration (CI) and deployment (CD), enabling teams to continuously add new code, execute tests, and deploy applications to production environments. Incorporating behavior driven development (BDD) into this workflow facilitates automated acceptance testing, identifies defects early, and accelerates the delivery of reliable software.

Role of BDD in CI\CD

What is BDD development and in CI\CD? BDD (behavior driven development) provides automated specifications that are executed and check the behavior of the application. When these specifications are integrated into CI\CD, every new code change is automatically tested to ensure it doesn’t break existing features or introduce bugs. This is particularly important for Agile teams, where speed and continuous delivery are key.

Why integrate BDD into CI\CD pipelines?

• Continuous quality control. With CI\CD integration into the BDD testing process, code quality is checked with every commit. Automated BDD tests confirm the correctness of the business logic implementation and approve regressions in the code. Running these tests in the pipeline helps identify errors before changes make it to production.
• Faster feedback. Developers immediately learn if a feature’s behavior does not meet the specifications, allowing quick resolution of issues. This reduces the time needed for detecting and fixing errors, accelerating the development process.
• Improved communication. Behavior Driven Development (BDD) ensures alignment among all participants in development projects with different roles – business analysts, developers, and QA team (3 Amigos). By integrating BDD scenarios into CI\CD, the whole team gains transparency on whether the software meets the expected requirements at each stage of development.

How to integrate BDD into CI\CD pipelines:

Integration into the CI\CD pipeline. Set up the pipeline to run BDD tests as part of the build process. BDD tools are compatible with such CI\CD platforms as GitHub actions, Jenkins, GitLab CI, and Azure DevOps. They allow automation of the execution of automated BDD tests after each commit. This ensures continuous and automated testing of behavioral scenarios.

After each commit, the code is run through the CI\CD pipeline, which checks whether the program meets the defined specifications. This automation ensures continuous validation of the application’s functionality, improving its quality and stability.

Launching your test scenarios provide YAML file in root of your project. Here you can see an example of a cucumber.yml file designed for a Playwright + JavaScript setup, assuming you are using @cucumber/cucumber and Playwright for browser automation:

default: --require-module ts-node/register \
         --require features/support/*.ts \
         --require features/step_definitions/*.ts \
         --format progress \
         --publish-quiet

ci: --require-module ts-node/register \
    --require features/support/*.ts \
    --require features/step_definitions/*.ts \
    --format json:reports/cucumber.json \
    --publish-quiet

html_report: --require-module ts-node/register \
             --require features/support/*.ts \
             --require features/step_definitions/*.ts \
             --format html:reports/cucumber-report.html \
             --publish-quiet

rerun: --require-module ts-node/register \
       --require features/support/*.ts \
       --require features/step_definitions/*.ts \
       --format rerun:@rerun.txt \
       --publish-quiet

debug: --require-module ts-node/register \
       --require features/support/*.ts \
       --require features/step_definitions/*.ts \
       --tags "@debug" \
       --format progress \
       --publish-quiet

Timeliness Within Agile Sprint Planning

What is BDD software development? BDD offers a methodology that enables teams to fully integrate an agile approach into the software development process. It enhances and fine-tunes standard Agile practices like sprint planning, user stories, and acceptance criteria, improving their effectiveness.

This approach helps teams focus on developing truly important features, reducing the amount of rework and time loss, and accelerating the delivery of value to users.

What are the key features of BDD that complement your Agile practices?

• Collaboration through live communication. BDD fosters effective communication among key participants in the software development process, reducing the likelihood of misunderstandings.
• Priority of working software. Thanks to BDD, all stakeholders can identify potential errors or inconsistencies early on, helping the team build exactly what is needed.
• Focus on common requirements – ease and visualization. BDD describes end-user behavior using test scenarios written in simple and understandable language.

It is important to remember that dialogue is key in development, as software is created by people. Ultimately, the bottleneck in the process is often not testing but ignorance and uncertainty.

BDD is one approach that helps overcome these challenges!

BDD Best Practices

Teams working with the Agile software development methodology can maximize the benefits of BDD by following these best practices when writing scenarios:

• Clear and concise language. Avoid ambiguity and confusion in scenario descriptions.
• Single Responsibility Principle. Each scenario should focus on a single specific behavior or outcome, making it easier for shared understanding of the problem and support.
• Use of Gherkin syntax. This helps structure the scenarios using Given, When, Then. It ensures consistency in understanding requirements and readability.
• Scenarios with data variations. Use Scenario Outline for these, which reduces duplication and improves maintainability.
• Meaningful scenario titles. Titles should accurately reflect the behavior being tested.
• Avoid technical details. Focus on user actions and expected results.
• Examples and edge cases. Include them to ensure comprehensive coverage and verify system behavior under various conditions.
• Collaboration in writing. Encourage collaboration among team members — software developers, testers, and product owners — to ensure that scenarios accurately reflect user requirements.
• Regular review and refinement. This helps continuously improve scenarios to keep them relevant and aligned with changing requirements.
• Testability. Break down scenarios into smaller, independent parts for easier testing.
• Use variables instead of fixed values. This enhances flexibility, reusability, consistency, and reduces the likelihood of errors.
• Define a common background for related scenarios. This reduces duplication and improves maintainability.
• Use business language. For understanding and implementing stakeholder expectations and accurately reflecting user needs.

By following these practices, you will elevate the quality of your BDD development.

Summary

It is crucial to implement BDD alongside modern approaches to test management, such as Agile Test Management. This allows for the proper identification and testing of requirements at early stages, minimizing the risks of significant delays and costs.

What is behavior driven development (BDD)? It is an effective method for ensuring high-quality software through productive collaboration, clear communication, and focusing on testing behavior from the user’s perspective. By following the principles and best practices outlined in this comprehensive guide, you will be able to enhance your BDD testing skills and create software that fully meets user expectations. Integrate BDD testing into your development process and experience significant improvements in both the quality and speed of software delivery.

The post Behavior-Driven Development (BDD): Meaning, Benefits & Best Practices appeared first on testomat.io.

Brands, working across numerous industries, are eager to optimize smartphone apps in order to improve user experience and prevent app deletion from the phone by users.

However, before the mobile app release, it should be tested on a variety of devices, each with different screen resolutions, processors and operating systems. In reality, it is a real challenge, especially when it should be done manually. With AI in mobile testing in place, teams can automate this process, test scenarios more precisely, and catch bugs early. A recent survey of the Kobiton testing tool platform highlights information that 48% of quality assurance specialists have already used AI for mobile testing, while 21% of them only plan to implement artificial intelligence tools.

In the article, we are going to overview what is AI mobile testing, why teams need it, and what strategies to use to make it effective.

AI in mobile testing: What Exactly Is It?

When it comes to AI in mobile testing, we mean the applying of artificial intelligence technologies, such as ML, NLP, in fact ChatGPT and other AI techniques in the mobile testing process. Ai-backed tools have the following options:

→ Automating repetitive tasks
→ Generating test scripts
→ Detecting bugs
→ Predicting areas that are at risk of failures
→ Monitoring app performance under different conditions
→ Suggesting optimizations for a better user experience.

Why use AI in Mobile Testing?

With AI testing tools, automation engineers and developers can make the mobile testing process automated and less time-consuming. Here are other reasons why teams should apply AI in mobile testing:

• With AI, teams can improve the accuracy and relevance of test results by carrying out thorough testing across various scenarios they have never thought before.
• Teams can generate diverse test cases without the need for manual scripting by AI.
• Teams can monitor and detect hidden bugs and vulnerabilities that may go unnoticed through traditional testing methods.
• With AI, teams can maximize the effectiveness of testing by prioritizing tests in order of their failure potential or impact on the UX, so that quickly detect urgent issues and solve them before they arise.
• AI can pick anomalies and pinpoint potential bugs or performance bottlenecks so that teams can resolve problems faster.
• By using AI-based tools, teams can test across multiple devices and OSs to reduce the cost of purchasing and managing multiple real-life devices.

 To sum up, if you combine the strengths of artificial intelligence with human expertise, you will be able to launch apps which meet the growing expectations of today’s users!

And now look at this table , it highlights the difference between testing WEB and Mobile Apps, namely where AI-based mobile testing in comparison with traditional methods delivers smarter, faster, and more efficient outcomes:

AI-based Mobile Testing: How to Use It Effectively

Enhancing of AI automating start from creation of Test Strategy after than move within the some steps we visualized in our infographic, learning from each test cycle and constantly improving its performance.

Below, we are going to overview some of the most effective AI-driven mobile testing strategies so that you can incorporate them into your processes:

Automated Test Script Generation

By using AI, teams can get automatically generated test scripts based on functionality changes, new app feature implementation, or specific mobile app testing requirements. If consider requirements and previous data of user interactions, the AI model can be learned and then generate relevant test cases required for mobile automation testing.

The process looks like the following:

• You need to define your requirements. For example, you want to make a transaction in your banking app or add items to the cart.
• You need to represent these requirements to the AI model.
• Once the AI model understands your requirements, it will generate test cases.
• After test cases have been generated, you should review them, provide feedback to the AI model, and create instructions on what should be improved.
• You need to repeat the process until the AI model generates test cases that cover all your requirements.

Bug Detection with AI

With AI-based testing systems, you can predict where bugs are most likely to occur and address potential issues quickly. It will work as predictive maintenance for your mobile app – AI will analyze historical test data and identify patterns that might point to potential issues/anomalies.

Let’s reveal how it works:

• AI gathers historical information from your previous test runs, including test case data, test results, etc.
• You need to be ready for data cleaning and preprocessing which can be done by handling missing values, transforming numerical data into a common format/range, converting categorical data, etc.
• You need to train an AI model on your previously prepared data so that it will learn to spot data anomalies that could signal potentially risky areas in the mobile app.
• If trained properly, you can try it in newly generated test data and analyze results.

AI-based Real-time Reporting and Test Result Analysis

• Implementing AI-based real-time reporting speeds up the mobile testing process. These tools are able to analyze the results of tests in real time and deliver feedback immediately.

How to do it:

• You need to choose an AI tool based on your requirements and integrate it into your testing framework.
• You need to execute test cases as you normally and automatically track and analyze your test results in the integrated AI tool.
• Once finished, you can review the AI-driven insights and discover information about flakiness rates, failure counts, problematic tests, etc. for further decision-making.

Test Data Management with AI

With AI in test data management, teams can generate synthetic test data that mimics real data based on patterns learned from existing datasets. AI algorithms can also automatically anonymize sensitive data within test datasets while both protecting data and meeting testing purposes. It can help in:

• AI tools can generate realistic test data – both positive and negative one that closely resembles real scenarios.
• Teams can generate the data based on demand rather than keeping massive datasets beforehand.
• Teams do not need to create test data manually and can use fresh and just-generated datasets.

Usability testing with AI

With mobile testing by AI, you can analyze user behavior, preferences, and feedback. It will help teams to optimize the user experience based on suggested improvements. The teams can also discuss and improve areas where the app may fail to satisfy user expectations. Let’s overview what you need to perform it:

• You need to look for an AI-backed mobile testing tool that includes the required functionality and meets your requirements.
• Once found, you can integrate this tool into the testing process to provide insights into user actions.
• With this information at hand, teams can exchange their ideas and find ways on how to improve the app usability.

Tips for Using AI Mobile Testing

AI is changing the way how testers carry out the mobile test automation process, making it more advanced and effective. Let’s consider these tips to make the most of AI mobile testing:

• You need to select the right AI tools that align with your app’s requirements and can be used for different tasks.
• You need to remember that AI in mobile testing does not replace quality assurance teams, but it may drastically change the way they do their jobs by speeding up and enhancing the mobile testing process.
• You need to opt for a combination of AI and manual testing. Just because there are situations where the intuitive judgment of a skilled specialist is crucial for better outcomes.
• You shouldn’t generate test cases or scenarios from AI only. Your testing teams should take part and mix their skills and AI to produce good results.
• Teams should also use visual AI capabilities to detect UI and layout inconsistencies in various devices.

What about Integrating AI in mobile app testing?

AI mobile testing is no longer a concept. It is becoming a crucial component of modern mobile development. With artificial Intelligence technology, teams can teams scale their testing efforts, accelerate release cycles, and launch smartphone apps of higher quality at reduced costs. On the other hand, users can enjoy a bug-free and seamless user experience. Drop us a line if you have any questions or need consultations with our specialists.

The post AI Mobile Testing – How To Use It Effectively appeared first on testomat.io.

Let’s discover more details about defect management best practices and tips in the article below

Defects in Software Testing

In software testing, a defect is any error or failure occurred in the software applications as a result of code errors, incorrect logic, inadequate implementation, or unexpected issues between various software components. These errors lower the practical value of software which leads to unpredictable results as well as poor and slow performance. You can also learn the key difference between defects and bugs here.

Let’s imagine the following scenario of testing E-shop:

1. Internet user wants to make a purchase
2. User adds items to the shopping cart
3. User presses a button to Buy
4. Fill in his payment data and follow the instruction

While testing the shopping cart, the team discovers a bug:

1. User enters payment information
2. The payment becomes unsuccessful, he can see a message a server errors

It has happened due to issues related to the gateway connection.

Finding true defects is always challenging. It is vital to dig deeper during the defect management process. This avoids misinterpretations and assures that the software meets users’ needs.

Mykhailo Poliarush, CEO, Testomat.io

Common types of defects

Categorizing these defects helps testers and developers address them effectively. Look into distingushing the different types of issues that may be encountered during the software testing process:

• Functional defects. These defects are issues in the software. They block the program features from working as expected and meeting its specs. Depending on the defect’s source, they can be logical, interface, or data errors.
• Non-functional defects. These defects are issues in the software. They hurt performance, security, usability, stability, and compatibility. Non-functional defects are categorized into performance, security, reliability, usability, and compatibility issues.
• Logical defects. These defects are errors in the software’s logic. They arise from flawed algorithms, incorrect assumptions, or poor design decisions. They lead to incorrect results or unexpected behavior. Common types of logical issues are calculation, data processing, and algorithm errors.
• Design defects (UX/UI). These defects are flaws in a UI or UX design. They hurt the user experience and reduce interaction efficiency.
• Data defects. These defects are known as problems with data. They reduce its quality and reliability. They come from various sources, like data entry errors and system failures. Also, there are faulty integrations.

Defect management in software testing

In testing, defect management is the systematic process that helps teams detect and eliminate software issues to deliver software products of high quality. By identifying, documenting, prioritizing, tracking, and resolving software issues, teams can guarantee that the final product meets project requirements and user needs.

While the goals of implemented defect management process can vary from one QA team or project to the next, the approach must be the same for every team. Every team should answer where to report, who to involve, how to fix and track, etc.

With well-organized issue management, development teams can maintain the software’s quality and reduce costs.

Why Defect Management Matters

We all know that high-quality software and happy users are a requirement for all kinds of businesses. And every business is trying to achieve this goal. Most companies end up with defect management practices. Here is why the management of issues is crucial for your business:

• It enables teams to quickly identify and address issues as well as enhance the speed and effectiveness of defect resolution.
• It encourages cross-team collaboration by helping QA, development, and testing teams work together smoothly to resolve issues.
• With a focus on prioritizing and fixing issues quickly, it allows teams to deliver high-quality software faster.
• It supports a structured, systematic approach and contributes to more reliable and stable software.
• Analyzing and understanding the root causes of defects helps teams proactively prevent similar issues in the future and reduce the risks upfront.
• With issue management in place, companies can adopt a culture of quality by prioritizing defect management and focusing on quality as a consistent priority across the project.

Best Practices and Tips for Effective Defect Management

Implementing defect management best practices allows organizations to significantly improve software quality. End up if they adhere to these guidelines, development teams can streamline their defect management processes, reduce development costs, and meet user needs in the final software product.

Software issues don’t come cheap. We know that someone pays for them. When adopting defect management best practices, we can prevent or minimize these costs.

Here’s a breakdown of the key stages of the process and defect management best practices for optimizing the process and achieving success:

#1: Identification

At this step, teams have a main focus on identifying as many errors as possible early in the software development process. They perform various types of testing – unit testing, integration testing, and acceptance testing. They also attempt to fix the bugs quickly and minimize potential future expenses related to the resolution process. What helps teams detect and identify issues more effectively is:

• Applying a comprehensive testing approach. When combining various testing types, teams can test as the whole App as well its individual components, check how components work together, and validate the entire system to find mistakes early at different stages of the development lifecycle.
• Opting for automated testing tools. With automation in place, teams can speed up testing and increase test coverage. They can also integrate automation tools into the CI\CD pipeline in order to perform frequent testing and detect issues early.
• Using test case management systems. Teams can use test case management systems like testomat.io. These tools can integrate with issue tracking systems and enable teams to easily link tests and test suites to specific tickets. They can also create defects directly from failed test results – whether from automated runs or manual testing. Test management system testomat.io seamlessly integrates with Jira, Linear, AzureDevOps, GitHub issue systems.
• Incorporating a quality-first culture. You should provide a culture where team members can train and educate on different QA principles and testing techniques. Also, you can encourage regular code review processes and tracking key performance indicators. If combined, this will foster early issue identification, efficient resolution, and the delivery of high-quality software.

#2: Logging

At this step, QA testing teams aim to document and record issues identified during the development process. They will use this defect information to prioritize and assign errors for further fixing. With detailed information, they can make sure that anyone in the team can recreate the issue. That’s why it is important not only to describe the expected outcome and the actual behavior but also to attach visual evidence – screenshots or log files for better understanding. It needs to specify the operating system, browser, and other relevant system details as well. Here is a simple example of a standardized issue reporting template, you can do it with an xls table in a Google spreadsheet:

#3: Triage

In this stage, the teams and all stakeholders involved aim to evaluate and prioritize issues. They classify issues based on severity (critical, major, minor, trivial) and priority (low, medium, high or urgent). This helps them make sure that human resources are focused on resolving the most critical issues first. For a more efficient and hassle-free triage process, the following defect management best practices and tips may help you:

• Scheduling regular meetings with representatives from development, testing, and product management to review and prioritize errors is important.
• Everybody in the team should use a standardized form to document issue details, severity, priority, and assignment.
• Utilizing issue tracking tools like Jira, Bugzilla, or Azure DevOps will help you better track and manage errors.

Test management system testomat.io supports the Advanced Defect Management analytics widget and issue defect linking options.

#4: Assignment

At this step, each logged issue is assigned to a specific developer or team. Assigned teams or team members will be responsible for fixing them. To resolve defects more efficiently, you need to do the following:

• Considering expertise, workload, and severity of issues. You need to consider factors such as developer expertise, workload, and severity of issues before assigning. It is essential to remember that experienced developers should fix critical bugs to guarantee a timely and effective defect resolution process.
• Balancing workloads. You need to regularly review the developer’s workload and assign issues accordingly to prevent burnout and maintain productivity.
• Automating notifications and reminders. You need to implement automated notifications and reminders to ensure the timely resolution of assigned issues among teams.

#5: Resolution

At this step, the development team prioritizes defect resolution based on severity and starts fixing them, marking it a critical phase in the defect management process. By using automated testing tools and frameworks, they resolve bugs more quickly and efficiently. They also utilize collaborative tools for more seamless communication between developers and testers. To improve the effectiveness of defect resolution, consider the following defect management best practices for this stage:

• Prioritizing based on severity and impact. You know that high-severity issues should be resolved first in order to maintain system stability. Only by prioritizing critical issues can you support software quality and reduce potential risks.
• Employing collaborative tools. With these tools in hand, you provide real-time communication between teams. This helps streamline defect verification and leads to efficient and effective defect resolution.
• Documenting fixes and updating statuses. You need to document each bug fix and update its status in the tracking system. This keeps all team members informed and allows testers to validate the fix as soon as possible.

#6: Verification

At this step, testing teams verify that the resolved defects have been fixed correctly and without introducing new issues. To make this process more effective, you should focus on the following defect management best practices:

• Thorough retesting. Once the defects have been fixed, you need to perform comprehensive retesting of the fixed to make sure they are resolved correctly and function as expected.
• Regression testing. To maintain overall system stability, you need to detect any unintended side effects of the fix on other parts of the system with regression testing.
• Test case design. To cover all relevant scenarios, you need to create appropriate test cases to confirm that the issue has been fully resolved under various conditions.
• Issue status and documenting results. You need to remember to update the issue’s status in the tracking system and document the results of the verification process.

#7: Closure

At this step, verified issues are formally closed. The team confirms that all necessary checks have been completed and the issue is fully resolved. To close defects effectively, you need to consider the following defect management best practices for this stage:

• Gathering final approvals. It is essential to get confirmation from all relevant stakeholders, – testers and quality assurance leads to verify that the issue has passed all necessary retesting and regression testing and meets closure criteria.
• Updating documentation and issue status. Do not forget to update the issue status in the tracking system and related documents.
• Reviewing the issue. After an issue is fixed, you need to take a quick look to see if it reveals anything that could help in future process improvement.

#8: Reporting

At this stage, you can get valuable insights into the overall software quality and reveal areas for improvement within the development and testing processes. With a well-structured defect report, you can identify trends and root causes as well as discover areas for process optimization.

Here is a breakdown of how issue reporting in the defect management best practices contributes to continuous improvement:

• Identifying quality trends. When it comes to categorizing defects based on their frequency and severity, you can reveal patterns in recurring issues by analyzing where these defects occur. Whether it is in the UI, database, APIs, or specific features, this analysis helps teams identify potentially vulnerable areas and focus future testing on high-risk zones.
• Performing root cause analysis. When conducting a root cause analysis, teams can uncover reasons for design flaws, coding errors, or insufficient test coverage. With shared regular feedback, development, and testing teams can better identify and address recurring issues to reduce the likelihood of similar defects in future releases.
• Evaluating testing strategy. If many bugs are identified during later phases of testing (e.g., integration or user acceptance testing), it may indicate gaps in the earlier stages of testing. That’s why teams need to reassess the test strategy for better coverage and early issue detection in future cycles.
• Defect tracking. By tracking metrics such as defect density and leakage rates, teams can quantify software quality and identify areas for improvement. You can analyze defect resolution times to highlight bottlenecks (slow response times from the development team or inefficient workflows) in the defect management process and optimize it.
• Preparing for release. With defect reporting, teams can evaluate whether the software is ready for release by tracking the status of issues against the release criteria. If certain defects can not be fixed in time, teams must decide whether to release or delay.

If your issue management does not work properly, it can lead to inefficiencies, misunderstanding among teams, and even missed product releases. Not to mention all the extra time and dollars you will spend on fixing the bugs. That’s why you need to adopt defect management best practices to better track, assign, and resolve issues. The more efficient the process is, the faster you can deliver the final software products.

Defect Metrics to Monitor

Metrics are a valuable tool in defect management best practices that are worth investing time and effort. To answer day-to-day questions about the health of an issue process, you need to use appropriate metrics. Here we are going to overview the most popular metrics used during the defect management process:

Defect Density

This quality metric is used to measure the number of issues per unit of functionality. It helps assess code quality and pinpoint areas for improvement. You need to remember that lower defect density signifies higher quality.

Defect Detection Percentage (DDP)

This metric is used to calculate the percentage of issues found during testing vs. after release. By measuring the effectiveness of testing processes, a higher DDP signals earlier bug detection and reduced risk of production issues, contributing to overall software quality.

Escaped Defects

This quality metric is used to measure defects found after software release. It monitors the number of defects that were not identified during the testing phase.

Defect Leakage Rate

This metric is used to track the percentage of issues that escape into production. It measures the ability of the QA process to identify and prevent defects.

Defect Rejection Rate

This metric is used to evaluate the level of misclassification in defect reporting. It shows the efficiency of the issue reporting and triage process.

Mean Time to Detect (MTTD)

This metric is used to monitor the average time to identify a defect. It measures the time taken to identify and report defects.

Mean Time to Resolve (MTTR)

This metric is used to track the average time to fix a bug. It assesses the efficiency of the development team in resolving defects.

There’s a lot to consider when monitoring, so teams should use numerous metrics to gain a deep yet broad understanding of code quality, testing effectiveness, and issue resolution times, so to meet more metrics you can in the next pages of this testing blog:

• Guide to the Basics of Software Testing Quality Metrics
• Key Software Testing Metrics & KPI’s

Benefits of Defect Management

Here we are going to present the benefits you can realize with the defect management process:

• You can develop and launch software of high quality and catch issues before they escalate by finding and fixing issues early in the process.
• You can speed up defect resolution and accelerate software releases thanks to streamlined issue tracking and well-organized communication and collaboration across teams.
• With a well-polished process, you can minimize costly and late-stage bug fixes by optimizing resource use and lowering expenses on the project.
• Delivering reliable, high-quality software builds trust with users and increases customer satisfaction.
• You can learn from past issues and spot trends so that teams can refine their processes and prevent recurring errors.

Limitations of Defect Management

While defect management offers numerous advantages, it is not without its limitations. Let’s review them below:

• If you do not handle the defect management process correctly, the software development cost will rise.
• If you do not manage issues early, the defects can cause more damage.
• If the process is not done correctly, your company could lose revenue, customers, and brand reputation.
• If you overload your teams with a high volume of bugs, it can lead to decreased productivity and burnout.
• If bugs remain unresolved, you face performance issues, security vulnerabilities, and dissatisfied users.
• If you do not carefully fix bugs, there is a risk of introducing new issues and a more complex and time-consuming issue resolution process.

Bottom Line: Ready to use Defect Management Best Practices?

Only by properly managing this process, teams can keep projects on track. That’s why they should adopt defect management best practices and useful tips to enhance their workflow and improve the overall process. Following these defect management best practices not only boosts software quality but also helps reduce development costs and launch reliable and error-free software products. Enhancing your defect management process is possible with the powerful capabilities of our test management tool:

If you have any questions about implementing defect management best practices together us and our test management solution, drop us a line without hesitation.

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