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Managing Regression Risk with Evolving Manual and Automated Test Cases

In an Agile project, as each iteration completes, the product grows. Therefore, the scope of testing also increases. Along with testing the code changes made in the current iteration, testers also need to verify no regression risk has been introduced on features that were developed and tested in previous iterations. The risk of introducing regression in Agile development is high due to extensive code churn (lines of code added, modified, or deleted from one version to another). Since responding to change is a key Agile principle, changes can also be made to previously delivered features to meet business needs. In order to maintain velocity without incurring a large amount of technical debt, it is critical that teams invest in test automation at all test levels as early as possible. It is also critical that all test assets such as automated tests, manual test cases, test data, and other testing artifacts are kept up-to-date with each iteration. Regression Risk is highly recommended that all regression test assets be maintained in a configuration management tool in order to enable version control, to ensure ease of access by all team members, and to support making changes as required due to changing functionality while still preserving the historic information of the test assets.

Testers often do routine job every iteration; however, there might be excessive work load during some iteration it may be difficult to juggle around several issues. The testers at the beginning of the iteration will have to get together to prepare a test strategy to deal with the unknowns and known and proceed accordingly. They testers team should also review the tests written earlier and discuss the probably touch points on where they need to add or delete the scripts.

Because complete repetition of all tests is seldom possible, especially in tight-timeline Agile process, testers need to allocate time in each iteration to review manual and automated test cases from previous and current iterations to select test cases that may be candidates for the regression test suite, and to retire test cases that are no longer relevant. Tests written in earlier iterations to verify specific features may have little value in later iterations due to feature changes or new features which alter the way those earlier features behave.

While reviewing test cases, testers should consider suitability for automation. The team needs to automate as many tests as possible from previous and current iterations. This allows automated regression tests to reduce regression risk with less effort than manual regression testing would require. This reduced regression test effort frees the testers to more thoroughly test new features and functions in the current iteration.

It is critical that testers have the ability to quickly identify and update test cases from previous iterations and/or releases that are affected by the changes made in the current iteration. Defining how the team designs, writes, and stores test cases should occur during release planning. Good practices for test design and implementation need to be adopted early and applied consistently. The shorter time-frames for testing and the constant change in each iteration will increase the impact of poor test design and implementation practices and reduce regression risk.

Use of test automation, at all test levels, allows Agile teams to provide rapid feedback on product quality. Well-written automated tests provide a living document of system functionality. By checking the automated tests and their corresponding test results into the configuration management system, aligned with the versioning of the product builds, Agile teams can review the functionality tested and the test results for any given build at any given point in time.

Automated unit tests are run before source code is checked into the mainline of the configuration management system to ensure the code changes do not break the software build. To reduce build breaks, which can slow down the progress of the whole team, code should not be checked in unless all automated unit tests pass. Automated unit test results provide immediate feedback on code and build quality, but not on product quality.

Automated acceptance tests are run regularly as part of the continuous integration full system build. These tests are run against a complete system build at least daily, but are generally not run with each code check-in as they take longer to run than automated unit tests and could slow down code check-ins. The test results from automated acceptance tests provide feedback on product quality with respect to regression since the last build, but they do not provide status of overall product quality.

Automated tests can be run continuously against the system. An initial subset of automated tests to cover critical system functionality and integration points should be created immediately after a new build is deployed into the test environment. These tests are commonly known as build verification tests. Results from the build verification tests will provide instant feedback on the software after deployment, so teams don’t waste time testing an unstable build.

Automated tests contained in the regression test set are generally run as part of the daily main build in the continuous integration environment, and again when a new build is deployed into the test environment. As soon as an automated regression test fails, the team stops and investigates the reasons for the failing test. The test may have failed due to legitimate functional changes in the current iteration, in which case the test and/or user story may need to be updated to reflect the new acceptance criteria. Alternatively, the test may need to be retired if another test has been built to cover the changes. However, if the test failed due to a defect, it is a good practice for the team to fix the defect prior to progressing with new features.

In addition to test automation, the following testing tasks and regression risk may also be automated:

  • Test data generation
  • Loading test data into systems
  • Deployment of builds into the test environments
  • Restoration of a test environment (e.g., the database or website data files) to a baseline
  • Comparison of data outputs

Automation of these regression test reduces the overhead and allows the team to spend time developing and testing new features.

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