Simplify Test Execution
Continuous Testing
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Vector Software Quality
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Unit Testing
- Continuous Testing
Tests not only show that the developed software fulfills its requirements. If the software is further developed or modified, the existing tests can show that previously implemented functions still meet expectations. Standards require you to do this regression testing based on a specified strategy.
Best practice is to integrate the execution of the available tests into the building pipeline as part of the continuous integration environment, enabling continuous testing.
Test Automation
For continuous testing consistent and repeatable processes for managing test activities and reporting key quality metrics such as code coverage are paramount. Test automation simplifies test execution. With automated test scripts, executing tests becomes a breeze, and compatibility with various compilers and frameworks ensures flexibility.
You can use our test automation solutions to rerun existing test cases against the latest version of your source files. These tests are designed for compatibility with successive code versions. The framework handles test execution management and organizes test results, making it straightforward to compare outcomes from the same test cases against different software versions. This systematic approach helps in identifying potential issues that might arise from changes in software components, supporting a more consistent CI process.
Change-Based Testing
Rerunning all existing test cases may be effective but not always efficient. Especially when only slight changes to the source code have been made, executing a full run is not required.
It is sufficient to rerun all the test cases, which cover the section of the code that has changed. The correlation of test cases and recorded coverage data helps to identify the minimum set of required tests. This Change-Based Testing technology significantly increases the efficiency of the continuous testing environment.
Full runs can still be performed when needed. But in between you can benefit from faster feedback on the impact of code changes.
Test-data Analysis
The main goal of continuous testing is to maintain the completeness of the test activities. For example, as the project progresses, requirements are modified, new ones are added, bugs are fixed, code is adapted or extended. This makes it necessary to adapt, re-execute or create tests. This is the great strength of data intelligence solutions. They bring together data from the many sources of a project and show correlations and effects.
Examples
Monitor the requirements coverage by taking the data from the Requirements Database and the Test Management System. Easily identify requirements without test cases.
Measure the Code Coverage across multiple coverage data sources. Quickly find the code sections with incomplete coverage.
Track the progress of test activities. Discover unstable and unreliable test cases based on trends. Keep an eye on the results of different product variants.
Compare the test results from the Test Management System and their dates with commit data from the Version Control System. Highlight code sections for which the test results are not consistent with the last commit.
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