Software testing is an essential activity in SDLC to ensure the quality of software products and their compliance with specified requirements. To validate software products or services, the creation of tests is inevitable. Another aspect that plays a vital role in software testing is test coverage.
Test coverage in software testing is a popular black-box testing strategy that helps you keep track of a product’s features tested using a certain set of tests. It makes software products more robust and error-free. For instance, if you have 1000 lines of code, your test cases must be able to cover the entire codebase. This is what test coverage is.
This article explains more about it in detail below.
What is Test Coverage?
It is a software testing metric that helps you know the amount of code your test cases have exercised. It basically tells the percentage of total code a specific set of test cases cover when they run. Simply put, test coverage is “What are we testing, and how much are we testing?”
For example, consider that your software has 10 requirements, and you created 100 tests. If you have run 90 tests, the test case coverage is 90%.
Test coverage can identify software modules that have been executed when you run the particular test suite. Testers write test cases in such a way that they cover the maximum requirements specified in the Software Requirements Specification (SRS). This ensures that all requirements meet and there is no issue left before releasing the software or its new version.
Many testing teams only consider functional requirements while calculating the test coverage. And it is fair since what matters the most is the functionality of software products. If requirements are not met, the software’s speed and security are of no use.
Even if you have a good test coverage percentage, it does not necessarily mean your software is 100% bug-free or meets all the requirements. You should also perform other types of testing after test case coverage results.
Benefits of Test Coverage
Here are some remarkable benefits of performing test coverage:
- Eliminates Defects at Early Stages: You can determine defects in your application and requirements gaps in the early stages of the software development life cycle. This helps you relieve the headache you would get in fixing these issues if discovered in the later stages.
- Better Coverage: When your test cases exercise most of the source code, the amount of work you need to do later decreases. Also, it reduced the number of defects, leading to delivering refined products.
- Eliminate Redundant Cases: It identifies and eliminates redundant, irrelevant, and less significant test cases. This makes the source code lighter.
- Identifies Uncovered Areas: It uncovers areas of the source code that a set of tests has not covered. This makes your source code error-free.
- Higher ROI: Test coverage helps detect most of the bugs at the production stage before moving to the acceptance testing phase. This has a great impact on the return on investment (ROI).
- Smooth Testing Cycles: Test coverage helps with multiple testing activities, such as regression testing, test case prioritization, and test suite augmentation and minimization. Also, it helps prevent defect leakage.
What is the Purpose of Test Coverage?
- The primary purpose is to show how much code a test suite exercises quantitatively. This can help you understand the testing quality and know whether you need additional test cases to validate the remaining part of the application. Doing this improves your application’s quality and reduces risks.
- Another purpose is to set priorities while testing. You can focus on exercising the critical part of your applications and allocate necessary resources accordingly. It ensures that the most important parts of the software get tested first, reducing the risk of critical issues occurring later in production.
- It helps testers eliminate the less relevant or duplicate test cases that do not have any positive effect. These duplicate test cases cause redundancy, which is usually a bad practice in the Software Testing Life Cycle (STLC). By reducing redundancy, test overage reduces the size of input test cases, which, in turn, makes code lighter.
Types of Test Coverage
- Product Coverage – This tells you about how much percentage of the product is tested from the given test cases. It checks whether the features of the products are working as expected in different scenarios. In this way, it verifies the application’s different “if-else” conditions.
For example, if you have a “cart” feature on an E-commerce website, you can use product coverage to check different scenarios such as:
- The cart does not clear once the user closes the application.
- Only the selected items are inside the cart.
- The user is able to increase or decrease the number of items in the cart.
An application with a good product coverage percentage verifies every possible scenario like the ones mentioned above.
- Risk Coverage – It gives you information about the coverage of the risky areas in the application. This will help you prioritize your application’s risky portions. If some parts of the application are too risky and have less test case coverage, these are highly prioritized.
For example, consider an application’s function calls a 3rd party API for fetching data. It needs a good amount of risk coverage. This is because if the third-party server goes down, no data will be received, and your application must handle this case.
- Requirements Coverage – This coverage is the most basic among all types and just tests the requirements specified by end users, irrespective of the quality and security. For example, if the end-users have the requirement to post images as a post on a social network application, then you primarily test if users can upload their photos irrespective of their quality or filtering.
- Compatibility Coverage – This tells you about the coverage of the compatibility of applications on different operating systems, networks, devices, etc. Today, there are hundreds of platforms available that users use. For example, one user might open your application on a PC with Windows OS installed and another on a mobile with Android OS installed. These two are completely different platforms and OS. You need to ensure your application is compatible with most of these platforms. This is where compatibility coverage helps you.
Below are some types of compatibility testing:
- Network Testing: Tests the application on different network environments like 3G, 4G, 5G, etc.
- Browser Testing: Tests the application on different browsers like Chrome, Firefox, Brave, etc.
- Mobile Testing: Tests the application on different mobiles like Apple, Android, etc.
- OS Testing: Tests the application on different OS like Ubuntu, Windows, etc.
Test Coverage Formula
You only need two variables to calculate the test coverage percentage of the testing:
- The total number of an application’s lines of code you are testing: X
- The number of lines of code the given test cases currently executes: Y
Test Coverage = (X % Y) * 100
The result of this calculation is in %.
Test Coverage Metrics
These metrics gauge the testing effort and answer the question, “How much of the application was tested?”. There are primarily three test coverage metrics: Code testing, data testing, and application testing metrics.
- Code Testing Metrics
Test execution rate is the most basic metric. It measures the percentage of the executed test cases to the total number of test cases.
- Let the number of tests executed be N.
- Let the total number of tests to be executed be M.
The formula for the test implementation rate is:
Test Execution Coverage Percentage = (N / M) * 100
The primary advantage of this is you get detailed insights into the testing process with the total number of passed and failed test cases. The major setback is that passed test cases do not assure the quality of those tests.
- Data testing Metrics
This metric establishes a connection between testing conditions and the components of an application. For example, if you make changes to a test case or application component, you can use data metrics to see how those changes affect other parts of the application.
One example of data testing metrics is the requirement coverage rate. It determines how many requirements the test cases cover. To calculate the requirement coverage rate, you have to divide the number of requirements covered by the total number of requirements that need to be covered in a specific project, sprint, or release.
- Let the number of requirements met be P.
- Let the total number of requirements be Q.
Requirement Coverage Rate = (P / Q) * 100
Here, you link tests with requirements, and test case coverage determines the impact of changes in the tests or requirements.
- Application Testing Metrics
Defect density is an example of application testing metrics. It is a measure of the total number of defects found by the size of a software entity.
The formula for defect density is-
Defect Density = Number of known defects / Size of a software entity
By finding this metric, you can identify areas that need automation. If a specific functionality has a higher defect density, it needs retesting. You can automate test cases for known defects in retesting.
Test Coverage Best Practices
- Quality Over Quantity – You should always take care of quality before quantity in terms of testing. Clearing bugs should always be your priority before incorporating any new features in your application. Test Coverage should focus on ensuring that the application’s critical parts are working as expected rather than creating a large number of test cases and randomly testing the application. This will never provide you the informative results.
- Define Test Objectives – It is essential to define clear objectives and ensure that all test cases are relevant to your objective. This helps ensure that all parts of the application most relevant to the objective get tested properly. For example, if you introduce a new search feature in a social network application, your testing should focus more on things related to the search feature rather than other side features.
- Leverage Automated Testing Tools – You should always use automated testing tools to increase the speed and accuracy of the testing process. These tools execute tests more efficiently and consistently than manual testing. More importantly, automated testing tools cover a wide range of scenarios and test cases compared to manual testing. As a result, you can ensure that your application’s all aspects have undergone testing.
- Avoid Redundancy – Redundant data includes duplicate or irrelevant test cases. You should avoid data redundancy as it affects the system’s resources and test coverage. Redundancy also makes it hard to identify and resolve some issues as they might not be strong enough to catch all possible scenarios.
- Test as Early as Possible – You should start testing your application in the early stages of development. This helps identify errors and bugs early and saves time fixing them if they were detected in the later stages. Adopting a test-driven development is beneficial for identifying errors early and fixing them as soon as possible.
Test Coverage vs Code Coverage
Another term called code coverage measures the number of lines of the source code tested. Let us understand how test and code coverage differ.
|Test Coverage||Code Coverage|
|You will need both manual and automated tools to perform test coverage.||You generally need only automated testing tools for code coverage.|
|This makes sure that the system meets all the specified requirements.||This ensures that code executes as expected without any issues, irrespective of features.|
|You can measure it using different metrics like features tested, test implementation rate, etc.||You can measure it using metrics like number lines executed successfully.|
|It measures the degree to which your application functionality gets tested.||It measures the degree to which your application’s code is tested, irrespective of whether the features are working as expected|
This was all about test coverage. Test coverage can have a huge contribution to streamlining your testing cycles. As development has become more systematic and well-structured these days and organizations look for testing completeness and effectiveness, test coverage is considered valuable. It helps you prioritize testing an application’s critical areas, keep track of testing, and reduce data redundancy.
However, it is not always true that the more you test, you get better results. Without a proper strategy, you end up investing more time, effort, and resources when testing more. But when you have a structured strategy, you can aim at 100% test coverage and not compromise the quality.