Software developers routinely write and test codes. Automated testing allows them to make changes, add features and refactor current code bases with surety, knowing that they won't have to rework the code entirely in case something goes wrong.
Testing is one of the most important phases of the Software Development Life Cycle (SDLC). Developers have access to several different types of software testing methods, depending on the metrics and parameters that apply the best to their code.
The code coverage approach is significant, making it a vital metric to help the quality assurance team get reliable results.
What is Code Coverage?
Code coverage is a metric in software testing used to gauge the effectiveness of tests and allow you to spot problems. It demonstrates a commitment and dedication to quality, helping you understand how much of your source is tested and analyze how extensively a software has been verified.
Moreover, it gives the teams assurance in their tests and enhances the code's quality. Code coverage is also called test coverage. Typically, it is quantified in the percentage of the total lines executed of the overall code lines and run code tests.
Why Is it Beneficial to Use Code coverage Analysis?
Code coverage is a powerful software testing metric that helps assess any software's quality and performance.
These insights are beneficial to the QA and development team. They can monitor the quality and health status of the source code and pay more heed to the uncaptured code's parts. For developers, code coverage can help with dead code elimination and detection, while QA can help check uncovered or missed test cases.
Here are some benefits of code coverage:
- Software with good outcomes (high percentages) is less likely to have undetected bugs that can stem from coding errors, overly complex code, non-adherence to best coding practices
- The university of Gothenburg concluded that 70-80% is the critical point for code coverage in terms of cost efficiency
- The bigger the project team, the more vague their outlines are for well-tested code. Code coverage is an estimated metric, consolidating the team's efforts and ensuring consistent testing practices. This also creates and fosters a healthy team culture
How to Use Code coverage Analysis?
Most code coverage analysis tools leverage a set of metrics to report code coverage analysis. Use it to measure the following metrics:
This is the number of stated methods/functions that have been invoked after you have run test suites.
This concerns minor potential units accessible to programmers, such as assertions, assignments, conditionals, loops, and returns.
This assessment of the number of coherent branches is gauged in your code.
These tools equip your program's source code or byte code, helping users benefit from collating detailed code metrics.
Here are some practical code coverage tools:
· Visual Studio. Microsoft's well-known code tool, Visual Studio offers a range of testing features, such as calculating cyclomatic intricacy
· Codecov. This is a robust code coverage tool that you can leverage to generate coverage for your project's reports. Upload the information generated from code coverage in your internal/local file structure to codecov, and the tool can easily visualize the info concerning coverage on various charts
· JaCoCo (Java Code coverage Library). Open source projects aim to provide a novel standard tech for analyzing code coverage in Java VM-based settings, with integrations for tools such as Eclipse, Ant, and Maven
While there are multiple roles involved in delivering a successful software project, all share the ultimate goal of ensuring to provide a quality product. Code coverage offers a metric that all members can work to enhance and edge their projects efficiently, closer to delivery.
Achieving good coverage should be the goal, but also remember to pair it with a robust test suite to ensure the continued integrity of the system.