Test Cycle Report – Real Insight into Software Quality
This report presents the detailed results of a complete regression test cycle, including test execution statistics, code coverage metrics, risk analysis, and performance data.
In the example, 831 out of 847 test cases were executed with a 95% pass rate, while the coverage of the modified code reached 85%, which proved sufficient to approve the release.
The document clearly demonstrates how a software version’s quality can be evaluated in a data-driven way before production deployment.
Download PDFParallel Test Execution and Code Coverage – A Probabilistic Approach for QA Engineers
Code coverage remains a fundamental metric in quality assurance, as it shows which parts of the codebase have been exercised by the tests. However, tracking coverage becomes more complex when tests run in parallel. This challenge is not limited to automated testing, but can also arise in manual testing scenarios when multiple testers work simultaneously.
In this post, we combine the perspective of probability theory with practical testing experience to demonstrate why parallel test execution does not compromise the reliability of code coverage measurement. We show that despite the added complexity from parallel runs, essential coverage information remains stable, and statistical reasoning further reinforces confidence in the results. The document is written in English, and we hope readers find it insightful.
Download PDFCase Study: Developing a Test Coverage Measurement Tool for a Leading Hungarian Bank
A tailor-made test coverage measurement solution designed to bring real-time visibility into UAT readiness.
By combining change detection, intelligent test prioritization, and coverage analytics, it helps teams focus testing where risk is highest.
The approach enables measurable quality gates, reduces post-release defects, and supports confident, data-driven release decisions.
Download PDFTestNavigator - the essence of testing
Test cases play a crucial role in the software development process, as they validate that the program and its functions work as intended. With thousands of test cases,
it is particularly important to rank them appropriately to maximise the effectiveness of hte etsts ofcusing on:
- testing the most critical and high-risk areas of the code
- prioritizing tests that provide the most value to the users
- code-level changes that have the highest risk to delivery
In this document you can read about how TestNavigator can help you meet these expectations
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