How can you use code coverage metrics to improve the quality of your engineering designs?

1 What are code coverage metrics?

Code coverage metrics are numerical indicators that show how much of your code is executed by your test cases. They can be calculated at different levels of granularity, depending on the type of code and the testing objective. For example, statement coverage measures the percentage of statements in your code that are executed by your test cases, while branch coverage measures the percentage of branches in your code that are taken by your test cases. Other types of code coverage metrics include condition coverage, path coverage, and function coverage, which focus on different aspects of your code's logic and structure.

2 Why are code coverage metrics important?

Code coverage metrics are important because they help you evaluate the quality and completeness of your test cases. They can reveal areas of your code that are not tested, or tested poorly, and help you prioritize your testing efforts. By using code coverage metrics, you can ensure that your test cases cover all the possible scenarios and behaviors of your code, and that they detect any errors or defects in your design. Code coverage metrics can also help you optimize your testing resources, by reducing redundant or unnecessary test cases, and increasing the efficiency and effectiveness of your testing process.

4 What are the benefits of using code coverage metrics?

Using code coverage metrics can bring several benefits to your engineering design process, such as improved quality and robustness, reduced risk of errors and failures, faster and cheaper testing, and increased customer satisfaction. You can ensure your code meets expected functionality and performance standards, detect and fix any bugs or defects in your code early and efficiently, optimize testing resources, avoid rework or redesign due to faulty or incomplete testing, deliver a reliable design that meets customer needs and expectations, and demonstrate your testing quality and coverage.

5 What are the challenges and limitations of using code coverage metrics?

Using code coverage metrics in your engineering design process can pose some challenges and limitations. It's important to select the right types and levels of code coverage metrics that suit your objectives, and to interpret them correctly and cautiously. Additionally, you must balance the trade-offs between achieving high code coverage and maintaining reasonable testing costs and efforts. Code coverage metrics can only tell you how much of your code is executed by your test cases, not how well or thoroughly it is tested, or if it meets the design specifications or requirements. Achieving high code coverage may require more test cases, more testing time, more testing tools, and more testing expertise, but it does not guarantee that your design is error-free or fully functional. Therefore, you need to determine the optimal level of code coverage that meets your design and testing goals and constraints.

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?