Test coverage and code coverage are essential tools to analyze the software and measure the effectiveness of its codebase in development. They could be interchangeable, but they are different. This article explains what makes them different to help your understanding.
What is Code Coverage?
Code coverage is a white-box testing technique. It verifies the extent to which developers have executed the code. The tools used for code coverage contain static instrumentation. Testers can use these to insert statement monitoring code execution at crucial points in the code.
While adding instrumentation does increase the test execution time and code length, the information received by the tester due to this more than justifies the increase. Testers receive a report from the code coverage scripts detailing the extent to which the developers have executed the application. Testers will analyze the result to understand the product, make their tests effective, and reduce possible defects after release.
Also read: Root Cause Analysis for Software Defects
Why perform Code Coverage?
Developers perform code coverage at the unit test level; this gives them a great vantage point to help them decide the tests they need to include. Code coverage helps them answer questions like:
- Does the unit test suite have enough tests?
- Has the code been implemented intentionally?
Further, as development progresses, developers add new features and fixes to the codebase, changing the code to stay updated with these changes while trying to maintain the established testing standards. Code coverage ensures developers maintain these standards, and only optimal quality code remains.
A higher code coverage percentage means lesser chances of overlooking unidentified bugs. It helps when you set up a minimum level that code coverage must achieve to reduce the chances of finding bugs at later stages of the development process.
Benefits of Measuring Code Coverage
- A high percentage of software is less likely to contain defects resulting from non-adherence to coding practices, overly complex code, or coding errors.
- A high percentage can imply that the code is more readable and maintainable.
- It helps provide stakeholders not involved in the software development process with a way to gauge software quality.
- Since a larger team leads to ambiguity when defining well-tested code, this process acts as an approximation metric, unifying the team's understanding of a well-tested code and leading to a more consistent test practice.
Also check: Fundamentals of Test Harness
Standard Metrics to Measure Code Coverage
Method Coverage (Function Coverage)
Testers measure code through method or function coverage by counting the number of functions a test suite calls.
Statements are instructions highlighting an action a program needs to carry out. Statement coverage hence measures the percentage of code statements and gives an accurate estimate of the quantity of code the tests execute.
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Branch coverage measures whether a test suite executes the branches from decision points written into the code. Such decision points arise from if and case statements, with two possible outcomes: true and false.
Testers use branch coverage to verify if their test suite executes the branches from decision points in the code. These are typically statements with two possible outcomes: a true and false or an if and case statement.
The goal is to verify if the tests execute all branch points across a comprehensive set of inputs. It helps testers measure code logic.
Developers use condition coverage to verify if tests execute statements using boolean expressions in the code - this is another way of ensuring that tests perform all possible code paths.
Multiple Condition Decision Coverage (MC/DC)
Each decision statement can have a combination of conditions. Multiple condition decision coverage ensures that tests execute all these combinations seamlessly. Testers use this metric to test safety-critical apps like those inside aircraft.
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Parameter Value Coverage
As the name suggests, parameter coverage ensures that tests cover all possible parameter values for each program. This metric is essential as neglecting specific parameter values leads to software defects.
Testers use the cyclomatic complexity metric to measure the number of linearly dependent paths in a program's source code. It is also helpful to determine coverage for particular code modules.
Code Coverage Advantages
- You can use it to determine the quality and performance of any software.
- Code coverage helps maintain the code base.
- You can evaluate the quantitative measure of code coverage.
- It helps analyze the software verification process and access the test suite's quality.
- It exposes harmful and unused code.
- You can use it to create additional test cases.
- It increases time to market by increasing efficiency and productivity.
- It helps identify uncovered test cases.
- You can use it to measure test implementation efficiency.
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Code Coverage Disadvantages
- It cannot always cover code entirely and accurately.
- You cannot test all feature values; it does not come with this guarantee.
What is Test Coverage?
Test coverage is a black-box testing technique that provides details on tests executed on an app or website. Testers use it to ensure maximum coverage (according to the requirements outlined in documents like FRS (Functional Requirements Specification), URS (User Requirement Specification), and SRS (Software Requirements Specification), and to monitor executed tests.
How To Perform Test Coverage?
You can perform test coverage through various tests. However, the type of tests you run depends on your testing team's business priorities. For example, an organization building a user-centric web app will prioritize UI/UX tests over functional testing.
Here are some test coverage mechanisms, the scope could depend on definitions:
Functional testing involves testing app functionalities against client requirements or those mentioned in the FRS documents.
Testers perform unit tests at the unit or module level. Bugs found at this level differ from those found at the integration level.
Integration testing is also called system testing. Testers perform this test once developers integrate all software modules.
You use this test to determine if a product qualifies for customer use. Typically, developers must receive approval from SMEs and testers to push code changes from staging to production.
Testers use test coverage depending on the level at which they perform the tests and the type of software they're testing. Moreover, test coverage metrics are different for mobiles and websites.
There are many times of test coverage and you can measure them at various testing levels like component testing, integration testing, or acceptance testing.
Here are some coverage types:
Features coverage involves writing test cases to help implement maximum coverage of product features. These test cases must test all mandatory and optional features according to the priorities set by the product team.
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Risk coverage addresses the risks associated with the project. It helps mitigate these risks by identifying the core issues. However, we cannot predict risks due to changes in market conditions. Hence, we cannot use risk coverage at this stage.
Requirements coverage ensures that when you write test cases, they provide maximum coverage according to set requirements. Such a requirement can be the default language for an SMS application - which is usually dependent on the location of where the app is released.
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Why Is Test Coverage Analysis Important?
Test coverage analysis ensures the identification of defects that you can address. Here’s why it is essential:
Users Don't Tolerate Bugs.
A report from Statista highlighted that in 2019, 25% of users stopped using a mobile app after just one use. Users will abandon an app that is glitchy or has many unexpected behaviors.
Running Various Tests Is Important
To ensure your app or website meets all requirements stated in the agile testing manifesto, you must cover all testing types in your development process. You'll need to run performance, security, functional, accessibility, and other tests to prevent defects. To ensure app responsiveness and quality, you'll need to perform tests under real user conditions.
Don’t Rely on iOS Emulators & Android Simulators. Test on Real Devices.
Developing and Implementing a Comprehensive Test Coverage Strategy
To ensure your test coverage strategy is effective, you need to ensure accuracy in:
- How you build and maintain your test labs.
- The platforms you include and use to test.
- Testing scenarios you build and execute for each software iteration.
HeadSpin: A Part of Your Test Coverage Tools
The HeadSpin Platform is a great test coverage tool that you can use to meet your test coverage requirements. Its Create Your Own Lab (CYOL) product lets you organize and utilize your existing device investment by delivering uninterrupted local access to remote devices. You can use this to test and debug critical workflows remotely. With CYOL, you get 68% fewer hours on QA and 30% faster in-app load time.
The HeadSpin Platform supports all kinds of testing. It supports 30+ automation frameworks, lets you perform tests in real user conditions and execute tests in parallel, contains real SIM-enabled devices, and provides cross-device and cross-browser support.
Advantages of Test Coverage
- It reports on portions of the codebase that necessary test cases have not covered.
- It helps detect areas of test cases that don't apply to a project. You can eliminate these cases to make the code light.
- Developers can use it to create additional test cases when required to ensure maximum test coverage.
- You can use it to prevent defect leakage.
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Code coverage is an essential metric; however, test coverage is what you should aim to achieve. By going beyond unit tests to acceptance tests, integration tests, and others, you ensure your app is without glitches and is ready for production.
However, even with test coverage, ensure you develop a strategy as testing often without one does not always result in good. Understanding your requirements and then testing is the best approach you can take.
Q1. What are some examples of test coverage metrics?
A1. The top test coverage metrics include:
- Test cases by requirement.
- Test execution coverage percentage.
- Defects per requirement.
- Requirements coverage.
- Test case performance in finding defects.
- Defects per functional area.
- Defects per platform under test.
Q2. What does refactoring mean?
A2. Developers use this to revamp existing code by testing continuously with existing test code. They perform refactoring in small steps, changing the code without changing its external behavior, i.e., the functionality or logic. Additionally, it also helps to identify bugs.
Q3. What are the advantages of black-box testing?
- Testers do not need to be technical when performing black-box testing.
- Testing is balanced and unprejudiced.
- Black-box testing puts the point of view of the user first.
- It helps to identify contradictions in functional requirements.