How do you evaluate and compare test case design metrics across different test phases and types?

1 Test case design metrics

Metrics are essential for measuring the success of test case design. The number of test cases is a good indicator of the size and scope of the test suite, which can help estimate the resources and time needed for testing, as well as potential risks. Test case coverage assesses how closely the test cases align with customer expectations and business goals. Test case effectiveness evaluates how well your test cases detect and report defects, while test case efficiency compares cost and benefit to optimize the design process. All these metrics can help ensure that user satisfaction and software performance are maximized with minimal effort and resources.

2 Test phases and types

The STLC consists of various phases and types of testing, each with its own objectives, methods, and criteria. Unit testing is used to verify the functionality and logic of the code, and detect any errors or bugs at the lowest level. Integration testing verifies the compatibility and communication of the code, and detects any errors or mismatches at the integration level. System testing tests the software as a whole, to verify its functionality and performance, while acceptance testing tests the software from the user's perspective, to ensure its usability and quality. These tests help detect any errors or issues that may affect user satisfaction.

3 How to evaluate and compare metrics

To evaluate and compare test case design metrics across different test phases and types, you should consider the purpose and scope of each phase, the level of detail and complexity, and the sources and standards. For instance, in unit testing, you may opt for a high number of test cases and a high test case coverage to thoroughly test each unit. In contrast, acceptance testing may require a low number of test cases with high test case effectiveness to meet user’s needs. Additionally, integration testing may involve a test case coverage metric that considers data, control, or interface integration. System testing may involve a test case effectiveness metric that considers functional, non-functional, or security defects. Lastly, unit testing may use a code coverage metric such as statement, branch or path coverage while acceptance testing may employ user acceptance criteria like user stories, scenarios or use cases.

4 How to improve metrics

To ensure your test case design metrics are successful across different test phases and types, it is essential to follow some best practices. Firstly, you should define clear and measurable objectives and requirements for each phase and type of testing, ensuring that your test case design aligns with the anticipated outcomes. Additionally, you should use appropriate techniques and tools for each phase and type of testing; for example, black-box techniques such as equivalence partitioning or boundary value analysis can be used for system or acceptance testing, while white-box techniques like code analysis or code coverage are better suited to unit or integration testing. Finally, it is important to review and refine your test cases regularly in order to eliminate any gaps, redundancies, or errors in your design, thus improving the quality, coverage, and effectiveness of your test cases.

5 How to compare metrics

To compare your test case design metrics across different test phases and types, you need to use some methods and tools. Charts and graphs can be used to visualize your metrics, enabling you to spot trends, patterns, and differences. For example, a pie chart can show the distribution of your test cases by type or category, while a bar chart can demonstrate the comparison of your test case coverage or effectiveness by phase or module. Tables and reports can be used to summarize your metrics, with a table showing the number, status, and outcome of your test cases by phase or type. Additionally, formulas and calculations can help quantify your metrics, such as calculating the test case coverage percentage or ratio by phase or type. This will help measure the value, performance, and quality of your metrics across different test phases and types.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?