To understand the critical differences between retesting and regression testing, here are the detailed steps: First, retesting is all about verifying a specific bug fix. Imagine you’ve identified a glitch, a software defect. The developers fix it, and then you, the tester, retest that exact issue to confirm it’s gone. Think of it as a laser-focused check. Second, regression testing is broader. It’s about ensuring that new code changes, bug fixes, or enhancements haven’t introduced new bugs or broken existing, previously working functionalities. It’s a safety net, making sure that fixing one problem doesn’t inadvertently create five new ones. You can find more structured insights on this by looking up resources like the ISTQB glossary or articles from reputable software testing blogs such as those on Ministry of Testing or TechTarget, which often provide clear, concise definitions and practical examples.

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Table of Contents

Retesting: A Deep Dive into Defect Verification

Retesting is a fundamental activity in the software development lifecycle, specifically geared towards confirming the successful resolution of identified defects. It’s not just about running the same test again. it’s about validating the fix.

When a bug is reported, reproduced, and then addressed by the development team, retesting becomes the crucial final step to ascertain that the defect no longer exists and that the intended functionality now works as expected.

This process is inherently focused and specific, targeting only the failed test cases from previous cycles.

The Purpose and Scope of Retesting

The primary purpose of retesting is singular: defect verification. When a defect is found and fixed, retesting validates that the particular bug has been eliminated. The scope is limited to the test cases that failed in the previous test execution and led to the defect report. It’s a binary outcome: either the bug is gone, and the test passes, or the bug persists, and the test fails again, leading to further investigation and rework. For instance, if a login button wasn’t clickable, retesting would involve verifying that specific button’s functionality post-fix. According to a study by Capgemini, over 70% of organizations consider defect retesting a critical phase, highlighting its importance in ensuring software quality.

When to Perform Retesting

Retesting is performed immediately after a bug fix has been implemented and deployed to a testing environment. It’s a reactive testing activity.

Post-Bug Fix: The most common scenario is after a developer commits a fix for a reported defect. The test case that initially failed due to this defect is re-executed.
Defect Closure: Successful retesting is often a prerequisite for closing a defect in bug tracking systems like Jira or Azure DevOps.
Immediate Feedback: It provides quick feedback to developers on the efficacy of their fixes, allowing for rapid iteration if the bug wasn’t resolved.

The Lifecycle of a Defect in Retesting

The defect lifecycle is intrinsically linked with retesting.

Defect Discovery: A tester finds a bug and reports it.
Defect Assignment: The bug is assigned to a developer.
Defect Fix: The developer implements a solution.
Fix Deployment: The fixed code is deployed to the testing environment.
Retesting: The tester re-executes the failed test cases.
Defect Closure/Reopen: If the test passes, the defect is closed. If it fails, the defect is reopened and sent back to the developer for further action. This iterative loop ensures that no defect is left unaddressed. Data suggests that about 15-20% of initial bug fixes might not fully resolve the issue on the first attempt, making retesting crucial for quality gates.

Regression Testing: The Safety Net for Software Stability

Regression testing is the systematic process of re-executing existing test cases to ensure that recent code changes e.g., bug fixes, new features, configuration changes have not adversely affected existing functionalities.

It’s a proactive measure designed to maintain the stability and integrity of the software as it evolves.

Think of it as a comprehensive health check after every significant modification, ensuring that new additions or fixes don’t unintentionally break previously working parts of the system.

This often involves executing a subset of the entire test suite, focusing on critical paths and frequently used functionalities. Javascript design patterns

The Core Principle of Regression Testing

The fundamental principle behind regression testing is non-deterioration. It ensures that the software’s existing features continue to function correctly after modifications. As software grows and changes, the risk of “side effects” or “regressions” increases. A small change in one module might unexpectedly impact a seemingly unrelated module. For instance, updating a database query for one report might inadvertently break another report that relies on similar data. According to industry reports, regression defects account for 23% of all reported bugs in complex software systems, underscoring the necessity of this testing type.

Triggers for Regression Testing

Regression testing is triggered by any event that modifies the existing codebase or environment.

New Feature Implementation: Adding new functionalities to the application.
Bug Fixes: While retesting verifies the specific fix, regression testing checks for collateral damage.
Code Refactoring: Changes to the internal structure of code without altering external behavior.
Environment Changes: Updates to operating systems, databases, or third-party libraries.
Performance Enhancements: Optimizations that might have unintended functional impacts.
Configuration Changes: Modifications to system settings or parameters.

Types of Regression Testing

To manage the scope and efficiency, regression testing can be categorized into various types:

Full Regression Testing: Re-executing the entire test suite. This is typically done for major releases or when significant architectural changes occur. It’s comprehensive but time-consuming.
Partial Regression Testing: Selecting a subset of test cases for execution, focusing on areas directly or indirectly impacted by changes. This is more common for minor releases and regular updates.
Unit Regression Testing: Performed at the unit level, often by developers, to ensure individual code units work after modifications.
Smoke/Sanity Regression Testing: A quick, high-level check to ensure the core functionalities are working after a build deployment. It’s often the first step before more thorough testing.
Selective Regression Testing: Identifying specific parts of the application affected by the changes and testing only those components and their integrations. This often involves a risk-based approach. Studies indicate that applying selective regression testing can reduce testing time by 30-50% compared to full regression, while maintaining high quality.

Key Differences: Retesting vs. Regression Testing in Practice

While both retesting and regression testing are crucial for ensuring software quality and stability, their objectives, scope, and execution differ significantly.

Understanding these distinctions is vital for effective test planning and resource allocation.

Retesting is about confirming a fix, whereas regression testing is about confirming that nothing else broke because of that fix, or any other change.

Objective and Purpose

The fundamental objective is where these two diverge most clearly.

Retesting: The primary objective is defect verification. It aims to confirm that a previously identified and reported defect has been successfully resolved and no longer exists. It’s a reactive activity that directly addresses a known issue.
Regression Testing: The primary objective is impact assessment and stability assurance. It aims to ensure that new code changes, bug fixes, or enhancements have not introduced new defects or negatively impacted existing, previously working functionalities. It’s a proactive activity to prevent regressions.

Scope and Focus

The scope of each testing type dictates which test cases are executed.

Retesting: The scope is narrow and focused. It involves re-executing only those specific test cases that failed in the previous test cycle and led to the discovery of the defect. Sometimes, a few related positive test cases might be run to confirm the fix’s correctness, but the core focus remains on the initially failed scenarios.
Regression Testing: The scope is broad and comprehensive. It involves executing a subset of the entire test suite, including previously passed test cases, critical functionalities, and often, high-risk areas of the application. The goal is to cover all areas potentially impacted by recent changes, whether directly or indirectly. For a medium-sized application, a regression test suite might comprise hundreds to thousands of test cases.

Test Case Selection

How test cases are chosen for execution highlights another key difference.

Retesting: Test cases are selected based on the failed test results from prior executions. If test case TC_Login_001 failed, only TC_Login_001 and possibly related ones will be re-executed for retesting.
Regression Testing: Test cases are selected based on the impact of changes and the overall criticality of functionalities. This often involves:
- Prioritizing critical and frequently used functionalities.
- Selecting test cases covering areas with high defect density.
- Choosing test cases that cover integration points and dependencies.
- Utilizing risk-based analysis to identify high-risk areas.
- Automated test suites are predominantly used for regression testing due to the large volume of test cases, with some sources reporting that 80-90% of regression test suites are automated in mature organizations.

Execution Time and Automation

The efficiency and approach to execution also differ. How to find bugs on mobile app

Retesting: Can often be performed manually as it involves a limited number of specific test cases. While automation is beneficial for any repetitive task, manual retesting is common for quick, focused checks. It’s typically done once the bug is marked as fixed.
Regression Testing: Due to the large volume of test cases and the frequent need for execution after every build, nightly, or weekly, regression testing is highly reliant on automation. Manual regression testing is feasible only for very small, stable applications or very limited changes. For complex systems, manual regression is often impractical and cost-prohibitive. Automated regression suites can run in minutes or hours, significantly reducing testing cycles.

Test Cycle and Outcome

The timing within the overall test cycle and the expected outcome vary.

Retesting: Occurs during the same test cycle as the defect discovery, specifically after a bug fix has been implemented. Its outcome is binary: Pass defect fixed or Fail defect still present.
Regression Testing: Can occur multiple times throughout the development cycle, often after every significant build, release, or major code change. Its outcome is to ensure that no new bugs have been introduced and existing functionalities remain stable. It’s an ongoing process to maintain the quality baseline.

When to Use Which: Strategic Application of Retesting and Regression Testing

Understanding the distinct roles of retesting and regression testing allows for their strategic application within the software development lifecycle.

It’s not a matter of choosing one over the other, but rather knowing when and how to integrate both for optimal quality assurance.

Each serves a unique purpose, and leveraging them effectively can significantly reduce risks and improve product quality.

Integrating Retesting into the Workflow

Retesting is a crucial step in the defect management process.

It’s performed as part of the immediate feedback loop to developers.

Post-Fix Validation: Once a developer signals that a bug is fixed, retesting should be the immediate next step. This allows for rapid verification and prevents delayed discovery of incomplete or faulty fixes.
Before Defect Closure: A defect should not be marked as “closed” in the bug tracking system until it has been successfully retested and verified by a tester. This ensures accountability and accuracy in defect reporting.
Small, Targeted Checks: Retesting is ideal for small, isolated fixes. If a button’s color was wrong and fixed, retesting that specific button is efficient. It helps in maintaining a clean bug backlog. According to research, teams that perform immediate retesting experience 20% faster bug resolution cycles due to quick feedback loops.

Integrating Regression Testing into the Workflow

Regression testing is a continuous process that should be incorporated throughout the development and release cycles.

After Every Significant Code Change: This includes new feature development, major bug fixes, refactoring, and environmental upgrades. Automating this process allows for frequent execution without significant manual overhead.
Prior to Each Release: Before deploying any new build or release to production, a comprehensive regression test suite should be executed to ensure the overall stability and functionality of the application. This acts as a final quality gate.
As Part of Continuous Integration/Continuous Deployment CI/CD Pipelines: In modern DevOps environments, regression tests are often integrated into CI/CD pipelines, where they run automatically with every code commit. If regression tests fail, the build is flagged, preventing faulty code from progressing further. This can catch issues very early, reducing the cost of fixing them. Organizations with robust CI/CD pipelines and integrated regression testing report up to a 60% reduction in production defects.
Scheduled Runs: Many teams schedule daily or nightly regression test runs to catch regressions as soon as they appear, providing timely alerts.

The Synergistic Approach: Retesting and Regression Testing Together

The most effective strategy involves using both retesting and regression testing in conjunction.

Bug Found & Reported: Tester identifies a bug.
Bug Fixed by Developer: Developer implements the fix.
Retesting: Tester performs retesting on the specific bug to confirm it’s resolved. If it fails, back to step 2.
Regression Testing: Once the bug is confirmed fixed retesting passes, a regression test suite is run to ensure that this fix or any other recent changes hasn’t broken existing functionalities. If regression tests fail, new bugs are reported, and the cycle continues.

This sequential approach ensures that individual fixes are verified, and the overall system integrity is maintained.

Neglecting either can lead to a less stable product. Responsive web design challenges

For instance, skipping retesting might mean deploying a build with an unresolved bug, while skipping regression testing could lead to new, unexpected issues in production.

Automation’s Role in Enhancing Testing Efficiency

In the context of both retesting and regression testing, automation is not just a luxury.

It’s a necessity for efficiency, speed, and accuracy, especially as software complexity grows.

While manual testing has its place, particularly for exploratory testing or certain UI/UX checks, automation scales significantly better for repetitive tasks.

Automation for Retesting

While retesting can often be done manually due to its limited scope, automating it brings significant benefits.

Speed: Automated tests can be executed much faster than manual ones, providing quicker feedback on bug fixes.
Consistency: Automated tests execute the same steps every time, eliminating human error or variations in execution.
Early Feedback: Integrating automated retests into a build pipeline means a bug fix can be verified almost instantly after deployment to a test environment.
Cost-Effectiveness: Over time, the cost of developing automated retests is offset by the time saved in manual execution, especially if the same bug recurs.
Example: If a specific API endpoint was failing, an automated API test can be quickly run to verify the fix within seconds, compared to a manual check that might involve several UI navigation steps.

Automation for Regression Testing

Automation is the backbone of effective regression testing.

Without it, managing large regression suites is often impractical.

Scalability: Automated regression suites can comprise thousands of test cases, running them frequently and consistently.
Frequency: Automation enables daily, nightly, or even per-commit execution of regression tests, catching regressions very early in the development cycle.
Cost Reduction: While initial setup costs for automation can be high, the long-term savings in manual effort and reduced production defects are substantial. A report by Forrester found that organizations implementing test automation saw an average ROI of 300% over three years.
Reliability: Automated tests eliminate human fatigue and oversight, leading to more reliable test execution and consistent results.
Comprehensive Coverage: Automation allows for more thorough coverage of critical functionalities and paths that might be overlooked in manual regression due to time constraints.
Integration with CI/CD: Automated regression tests are seamlessly integrated into CI/CD pipelines e.g., using Jenkins, GitLab CI, GitHub Actions, providing immediate feedback on code quality upon every commit. If a regression test fails, the build is typically marked as unstable or broken, preventing further deployment.

Tools for Test Automation

A wide array of tools supports test automation for both retesting and regression testing:

Selenium, Playwright, Cypress: For web UI automation.
Appium: For mobile application automation.
Postman, SoapUI, Rest-Assured: For API testing.
JMeter, LoadRunner: For performance testing which often involves regression of performance metrics.
Cucumber, SpecFlow: For BDD Behavior-Driven Development frameworks that make test cases more readable and collaborative.
Unit Testing Frameworks JUnit, NUnit, Pytest: For developer-level unit regression testing.

Investing in the right automation tools and building a robust automation framework is paramount for any team serious about software quality and efficient release cycles.

Best Practices for Effective Retesting and Regression Testing

To maximize the benefits of both retesting and regression testing, certain best practices should be adhered to. Visual testing strategies

These practices ensure efficiency, thoroughness, and contribute to overall software quality.

Best Practices for Retesting

Verify the Specific Fix: Always ensure the retest directly addresses the reported bug. Don’t get sidetracked by other issues unless they are clearly dependencies.
Document the Fix: Developers should clearly document what was fixed and how, aiding testers in their retest efforts.
Test Environment Parity: Ensure the retest is performed on an environment that mirrors the production environment as closely as possible to avoid environment-specific issues.
Consider Adjacent Functionality: While retesting is focused, it’s good practice to briefly check any directly related, adjacent functionalities to ensure the fix hasn’t subtly broken something immediate. This is a mini-regression within the retest scope.
Clear Defect Status Management: Use defect tracking systems Jira, Azure DevOps, Bugzilla effectively to manage defect statuses Open, Fixed, Retest, Closed, Reopened. This provides transparency and streamlines the workflow.

Best Practices for Regression Testing

Prioritize Test Cases: Not all test cases are equally important for regression. Prioritize based on:
- Criticality: Core business functionalities.
- Frequency of Use: Features used most by end-users.
- Risk: Areas prone to defects or with high impact if they fail.
- Recent Changes: Areas directly or indirectly affected by recent code modifications.
Automate Aggressively: As discussed, automate as much of the regression suite as possible. Manual regression for large applications is unsustainable. Aim for a high percentage of automated regression tests, with some organizations achieving 90% automation for their regression suites.
Maintain the Test Suite: Regression test suites are living entities. Regularly review and update test cases to reflect changes in the application’s functionality. Remove obsolete tests and add new ones for new features. A stale regression suite provides false confidence.
Integrate with CI/CD: Make regression tests an integral part of your continuous integration and deployment pipelines. This provides immediate feedback on the health of the codebase.
Analyze Test Results: Don’t just run tests. analyze the failures. Understand why a test failed. Was it a new bug, an environment issue, or a problem with the test script itself?
Categorize and Organize: Structure your regression test suite logically e.g., by module, by criticality. This helps in selective execution and maintenance.
Regular Reporting: Provide clear and regular reports on the status of regression tests to stakeholders, highlighting failures and overall stability.

Risks and Challenges Without Proper Retesting and Regression Testing

Neglecting or inadequately performing retesting and regression testing can introduce significant risks and challenges, ultimately impacting software quality, user satisfaction, and business reputation.

These testing types are not optional but essential safeguards against a deteriorating product.

Risks of Inadequate Retesting

Unresolved Defects in Production: The most direct risk is that bugs believed to be fixed are actually still present and make it into the production environment. This leads to user frustration and immediate negative impact.
Increased Support Costs: Production defects lead to higher support tickets, increased operational costs for hotfixes, and potential reputational damage. According to a study by IBM, the cost to fix a defect found in production can be 100 times more expensive than fixing it during the design phase.
False Confidence: If a bug fix isn’t properly retested, the team operates under the false assumption that a problem is resolved, potentially delaying proper resolution until a user encounters it.
Missed Dependencies: Sometimes, a bug fix might be correct but relies on another bug fix that hasn’t been implemented or deployed yet. Inadequate retesting might miss this dependency, leading to confusion.

Risks of Inadequate Regression Testing

Introduction of New Bugs Regressions: The primary risk is that new code changes or bug fixes introduce new, unintended defects into previously working functionalities. These “side effects” can be subtle and hard to trace back.
Deterioration of Product Quality: Over time, with many changes and insufficient regression testing, the overall quality of the software can degrade, leading to a brittle system that breaks easily.
Increased Technical Debt: Each new regression adds to the technical debt, making the system harder to maintain and further develop.
Delayed Releases: Discovering regressions late in the cycle e.g., just before release can cause significant delays, impacting time-to-market and revenue.
Higher Cost of Fixing Bugs: Bugs found late in the development cycle or, worse, in production, are significantly more expensive to fix due to increased complexity, longer diagnostic times, and potential emergency deployments.
Damaged User Trust and Reputation: Users quickly lose trust in unstable software. Frequent crashes, data corruption, or broken features lead to negative reviews, decreased adoption, and a damaged brand reputation.
Reduced Development Velocity: If developers constantly have to deal with regressions, their focus shifts from building new features to firefighting, slowing down overall development velocity.

Challenges in Implementing Both

Time and Resource Constraints: Both retesting and regression testing require dedicated time and resources. Teams often struggle to allocate enough of both, leading to shortcuts.
Choosing the Right Automation Tools: Selecting, implementing, and maintaining effective test automation tools requires expertise and investment.
Environment Management: Ensuring consistent and reliable test environments for both retesting and regression testing can be complex.
Scope Creep: For regression testing, there’s a risk of the test suite becoming too large and unwieldy, making full execution impractical. Effective prioritization is key.

Future Trends and the Evolution of Testing

Understanding these trends is crucial for staying ahead and ensuring continued software quality.

AI and Machine Learning in Testing

Artificial Intelligence AI and Machine Learning ML are poised to revolutionize how retesting and regression testing are performed.

Smart Test Case Selection: AI algorithms can analyze code changes, commit histories, and defect data to intelligently select the most relevant test cases for regression, reducing the need for full test suite execution. This moves beyond human intuition to data-driven prioritization. Companies like Google are already leveraging ML to optimize their internal test selection processes, reporting significant efficiency gains.
Predictive Analytics for Defects: ML models can predict areas of the application most likely to contain defects or be impacted by changes, guiding testers to focus their efforts. This can proactively identify potential regression areas.
Automated Test Script Generation and Maintenance: AI tools are emerging that can assist in generating test cases and even maintaining automated test scripts by detecting changes in the UI or APIs and suggesting updates. This addresses the significant challenge of test maintenance.
Root Cause Analysis: AI-powered analytics can help pinpoint the root cause of test failures faster, by correlating logs, code changes, and test results.
Self-Healing Tests: Some advanced automation frameworks are starting to incorporate AI to automatically adjust test scripts when minor UI changes occur, reducing manual intervention in test maintenance.

Shift-Left Testing and DevOps

The “shift-left” philosophy, deeply embedded in DevOps, emphasizes performing testing activities earlier in the software development lifecycle.

Early Detection: Integrating retesting and regression testing into the earliest stages of development e.g., unit testing, static code analysis, peer reviews means defects are found and fixed when they are cheapest to resolve.
Continuous Testing: In a true DevOps model, testing is not a separate phase but a continuous activity that runs alongside development. Automated retesting and regression tests are triggered with every code commit, providing immediate feedback.
Developer Ownership of Quality: Shift-left encourages developers to take more ownership of quality, performing unit tests and even integration tests themselves before handing off to dedicated testers. This reduces the burden on later testing phases.
Automated Gateways: CI/CD pipelines use automated regression tests as quality gates. If these tests fail, the build is automatically rejected, preventing faulty code from moving down the pipeline. This leads to higher quality releases and faster deployment cycles. Organizations that fully embrace continuous testing can achieve up to 5x faster release cycles with improved quality.

Test Data Management TDM and Environment as Code

Effective testing, especially regression testing, relies heavily on realistic and consistent test data and environments.

Automated Test Data Generation: Tools that automatically generate diverse, representative test data are becoming critical. This overcomes the challenge of finding suitable data for complex scenarios and ensures test coverage.
Data Masking and Virtualization: For sensitive data, techniques like data masking and data virtualization allow testers to work with realistic, yet secure, data sets without compromising privacy.
Environment as Code EaC: Defining and provisioning test environments using code e.g., Docker, Kubernetes, Terraform ensures consistency across different testing stages and prevents “works on my machine” syndrome. It allows for rapid spinning up and tearing down of environments for specific test runs. This significantly reduces environment-related failures and setup times.

These trends highlight a move towards more intelligent, integrated, and efficient testing processes, where automation and proactive strategies reduce the manual burden and ensure higher software quality from the outset.

Frequently Asked Questions

What is the primary goal of retesting?

The primary goal of retesting is to verify that a specific, previously identified defect has been successfully fixed and no longer exists in the software.

What is the primary goal of regression testing?

The primary goal of regression testing is to ensure that new code changes bug fixes, new features, or configuration updates have not introduced new defects or negatively impacted existing, previously working functionalities. Ios devices for testing

Is retesting performed before or after regression testing?

Retesting is typically performed before regression testing.

First, you verify the specific bug fix retesting, and then you run regression tests to ensure that fix and other changes hasn’t broken anything else.

Can retesting be automated?

Yes, retesting can and should be automated, especially for recurring defects or critical functionalities.

Automation provides faster feedback and consistency.

Can regression testing be done manually?

While regression testing can be done manually for very small applications or limited changes, it is highly inefficient and prone to error for complex systems. Automation is highly recommended and widely adopted for regression testing due to the large volume of test cases.

What triggers retesting?

Retesting is triggered when a developer reports that a specific bug has been fixed and deployed to a testing environment.

What triggers regression testing?

Regression testing is triggered by any significant code change, such as new feature implementation, bug fixes, code refactoring, environment upgrades, or before a new release.

What is the scope of retesting?

The scope of retesting is narrow and focused, limited to the specific test cases that failed due to the defect and led to its reporting.

What is the scope of regression testing?

The scope of regression testing is broad, involving the execution of a subset of the entire test suite, focusing on critical functionalities and areas potentially impacted by recent changes.

Is retesting a type of functional testing?

Yes, retesting is primarily a type of functional testing because it verifies the correct functionality of a specific feature after a bug fix. What is non functional testing

Is regression testing always functional?

No, regression testing can involve various types of tests.

While it heavily includes functional tests, it can also encompass performance regression, security regression, and usability regression to ensure non-functional attributes haven’t deteriorated.

What happens if retesting fails?

If retesting fails, it means the bug has not been successfully fixed.

The defect is typically reopened and sent back to the development team for further investigation and correction.

What happens if regression testing fails?

If regression testing fails, it indicates that new bugs have been introduced into existing functionalities due to recent code changes.

These new defects are reported, prioritized, and addressed by the development team.

How does test automation benefit both retesting and regression testing?

Test automation significantly benefits both by enabling faster execution, increased consistency, reduced manual effort, and higher frequency of testing, leading to earlier defect detection and improved overall software quality.

Can you skip retesting if you do regression testing?

No, skipping retesting is not advisable.

Retesting specifically verifies the fix for a known issue, which regression testing does not guarantee.

Regression testing focuses on side effects, not explicit fix verification. Visual test automation in software development

Can you skip regression testing if you do retesting?

No, skipping regression testing is a major risk.

While retesting confirms a bug is fixed, it doesn’t assure that the fix or any other change hasn’t broken other parts of the system. Regression testing is the safety net.

What is a regression bug?

A regression bug is a defect that is introduced into a previously working functionality as a result of recent code changes or modifications. It’s a new bug caused by a change.

What is a retest scenario?

A retest scenario is the specific set of steps and conditions used to verify that a particular bug fix has been successfully implemented.

It’s often the same scenario that initially revealed the bug.

How often should regression testing be performed?

The frequency of regression testing depends on the project’s needs, release cycles, and code change velocity.

It can range from daily or nightly runs in CI/CD pipelines to weekly, bi-weekly, or before every major release.

Are retesting and regression testing mutually exclusive?

No, retesting and regression testing are not mutually exclusive.

They are complementary activities that serve different purposes but are both essential for comprehensive software quality assurance.

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Retesting vs regression testing