What is Code Coverage, and how to measure it?
Software testing is essential in the development process. As a general standard, you should meet the specified requirements. Further, you should create a usable end product. This is what code coverage helps you achieve. It is a metric that should part testing.
In this piece, you’ll learn everything about code coverage, right from the basics to its best practices.
What Is Code Coverage Testing?
It refers to the percentage of software code covered by tests. This measurement shows the statements in a code run through tests. It also shows the line, statements, and branches that haven’t been executed in those tests.
Coverage data shows the aspects of the code thoroughly tested. The loop continues up to a point where Coverage meets the needed target.
Do We Need Code Coverage?
Coverage data also cuts down the chances of test entropy. As code goes through the release cycles, there are usually more chances of unit tests to atrophy. Likewise, the added code may not meet testing standards before the products’ first release.
Doing this will also maintain your testing at the required standards. You will then be confident that once you release the final product, it will have fewer problems.
In simple words,Coverage data is essential because of the reasons below.
- Helps us understand how well our tests test our code
- It helps us understand whether we have put up enough testing.
- By noticing drops in tests, you are more likely to write a unit test.
- It creates a culture of writing unit tests with code coverage rules that, in turn, help to cover all the parts of untested code.
- High Coverage increases the confidence in code.
- This is an excellent metric for investors.
- Code coverage checks if tests are run.
- Code coverage may lead to code refactoring.
How is Code Coverage Going to Help in Software Testing?
Code coverage is a good test of software quality. It is also an essential part of software maintenance.
- Code coverage prevents errors.
- You can also create more tests to improve Coverage.
- Further, you can achieve a better ROI by reducing UAT defects.
- It notes areas not run by tests.
- It tests a good amount of an app’s quality.
How Code Coverage Helps the Developer (Unit Tester) and Tester (System Tester)
High code coverage will result in lesser chances of bugs. The developer and system tester can set goals that must be met.
Benefits to the Developer
- First, the developer can identify the parts covered by tests as well as those not.
- Second, developing the code, a developer can find missed paths.
- Further, you can write unit tests to improve Coverage.
Benefits to the System Tester
- High Coverage increases confidence in the code.
- More Coverage is essential to investors.
- Tests can result in code editing.
Code Coverage Vs. Test Coverage
Code coverage is a white-box testing metric that shows the amount of code covered by tests.
On the other hand, test coverage is a black-box testing method. It shows tests have covered the code under test. Test coverage does not need much skill to do. Test coverage goes beyond code. Instead, it concentrates on user needs as well as building code for functionality.
However, when compared to code coverage, is that it is a manual approach. Test coverage will take more time as well as effort to build as well as assess test cases.
How Are Code Coverage Metrics Calculated?
To calculate code coverage, divide the total code lines in a test by the total number of code lines. Multiply what you get by 100.
Code Coverage Levels
There are different approaches to running code coverage. However, you can focus on these subtypes.
- Function Coverage. This shows the total number of functions that have been run in test cases at least once.
- Line Coverage. This indicates the number of code lines that have been checked by tests.
- Statement Coverage. Statement coverage tests are run to calculate the total number of statements in a source code that have been run. All executable statements are run at least once.
- Branch coverage. This is also known as decision coverage. It uses logical branches to assess code. You can make the right decisions based on every existing unit. E.g., by using variables for compatibility testing, It is good to use all variables with enough inputs.
How Test Coverage Is Performed
Like code coverage, test coverage includes several testing mechanisms. The right Coverage is usually based on an individual business’s propositions.
- Unit Testing. Unit testing is aimed at measuring bug encounters. This may differ from the run mechanism during the integration level.
- Function Testing. This is a metric taken to follow functional specifications.
- Integration Testing. Also known as system testing, integration Testing is tested on a system level. This test is run during the integration of necessary modules.
- Acceptance testing. This test is done to confirm the final product’s acceptability by final users. It is a green signal for developers to speed up product launches before making the last code changes.
Other test coverage levels include risk coverage, features coverage, as well as requirement coverage.
What Are Code Coverage Branches?
Branch coverage is a testing technique that ensures that every branch from each decision point has been run. This ensures that all reachable code gets executed.
Each branch is taken each way, whether false or true. Besides, branch coverage validates all code branches to ensure that none leads to an app’s abnormal behavior.
How Do I Check My Code Coverage or Test Coverage?
There are two approaches to checking code and test coverage.
Testing Code Manually
This includes setting debug points in code as well as verifying all paths. Unfortunately, this approach can take days to measure even a small codebase quality.
Using Code Coverage Tools
To show code quality to the management, you need to present tests that are done as well as a printout of all paths as proof of quality.
The surest way of testing software is through the use of code coverage tools.
With a tool, you can generate code coverage reports as well as share them with other project stakeholders.
How Code Coverage Tools Work
When a project is buildable and ready for testing
- Integrating tool with project build(in some cases just instrument) and tool Instruments code by adding counter or inject probes to collect the code executed during the test.
- Testing the application. This is done with or without unit test cases.
- Then a collection of coverage data at the application’s runtime.
- Report generation.
What is Instrumentation?
Instrumentation refers to a technique used by a tool to inject counters to collect coverage data from source code or objects.
You can also define instrumentation as a technique used to track code execution at run time.
The tool practically adds data collector calls in the source code to record whether a line or statement or branches or condition was run or executed.
Generally, there are two significant types of instrumentation:
- Source code level instrumentation. This includes adding a counter to the source code to collect coverage data at run time. This approach is followed by the majority of the tools.
for ex: the RKTracer tool
- Object-level Instrumentation. This takes objects and put additional instrumentation vie to disassemble and collect coverage data at run time
What Is Code Coverage In Unit Testing?
It is a process of running unit tests to assess the function behavior and produce coverage information using the code coverage tool.
Unit Testing is the mechanism by which code is written, i.e., unit test cases to evaluate function behavior.
Unit testing frameworks are used to write the test case. Stubs, drivers, as well as mock (or fake objects) are used in unit testing.
The benefits of code coverage in unit testing include:
- Ease in testing the functionality provided by a unit. Tests at unit levels will help you understand the unit API better.
- Unit tests allow developers to refactor code at a later date. With this, you can confirm whether the model still works well. The procedure here is to create test cases for all methods and functions. This way, changes that cause fault can be identified as fast and fixed.
- Thanks to unit testing’s modular nature, you can test parts of your project without having to wait for other dependency parts or modules to be complete. Here we can make sure of stubs make the behavior of dependency functions.
Unit Testing Best Practices
- Each unit test case should be independent.
- Only test one function at a time
- Have a clear and consistent naming system for your tests
- Every time you change code in a module, have a corresponding unit test case.
- Fix all bugs identified during unit testing before you proceed to the next phase
- Last, have a “test as you code” approach to maximize efficiency.
How Do You Generate a Code Coverage Report?
We can make use of the Code Coverage tool to generate reports. RKTracer tool will allow you to generate reports for all top programming languages.
The tool allows you to publish the generated reports in SonarQube as well as Jenkins easily.
Following are references on how to generate code coverage reports:
- How to Generate and Publish Coverage Reports for Python
- The Best Way to Generate and Publish Coverage Reports for Kotlin
- Generating and Publishing Coverage Reports for Golang
- A Simple Way to Generate and Publish Coverage Reports for Swift
How to improve Test Coverage
Want to get the most of your testing time and end up with quality apps or programs?
You can achieve this with our four easy tips.
Plan and Set Goals
You need to define the different aspects of your code testing strategy.
To achieve this, you can define the operating systems, devices, and OS versions you intend to run your tests.
Be sure to focus on testing that gives a great experience to customers with your products. Simply said, you’ll need to define the device coverage of your app. Likewise, with a goal, you’ll have something to work towards.
Increase Code Coverage
It becomes more comfortable for you to run code coverage against your code during testing with a continuous integration tool. This will give you great insight to enhance Coverage by creating missing tests with the right inputs. The goal should be 80% or higher.
Enhance Test Automation
This will allow you to carry out more tests in less time. Continuous integration will enable you to identify errors early enough.
Test on a Bigger Scale
You will quickly get more from your automated tests by running tests on more devices simultaneously.
Although this takes time, testing on a larger scale will guarantee you wholesome success.
Can I generate code coverage without unit test cases?
Code coverage is not only for unit test cases. But you should try and test everything you can. Doing this would create a legacy for later on. This would give you peace of mind when you make changes down the road. It will also ensure that your code keeps working as expected. Further, it documents the intended use of interfaces.
What Code Coverage Percentage Should You Aim For?
The least acceptable Coverage differs from project to project as well as from industry to industry. Your project’s economics should influence your goal. Some factors to consider when setting a plan include:
- Cost of failure. When creating a system with a high price of failure – like for the automotive as well as medical industries – raise your coverage goal.
- Resources available to test Coverage
- Development Cycle Status.
- Testable design. In case your system has special test provisions, you can raise your goal.
Is 100 Percent Code Coverage Possible?
When covering each branch and piece of error handling the code, it is almost impossible to achieve 100% coverage. You should not spend much of your quality time aiming for 100% coverage.
Also, 100% coverage does not always mean that the code is bugless. This is because even non-quality tests can reach 100% coverage. The goal here is to maximize the quality of tests as well as aim for a reasonable coverage percentage.
What is a Good Percentage for Code Coverage?
A 70-80% code coverage is a reasonable goal for system testing. For projects that have higher failure costs, you can use a higher goal.
The least code coverage for unit tests should be 10 to 20% higher than what you’ve set for system testing
What Code Coverage Will Not Do
Your team should understand two things: How the app behaves when used correctly as well as how it should behave when someone tries breaking it.
Code coverage tools can help you know where you should focus most on next. However, they’ll not tell you whether your set-up tests are good enough for unexpected behavior.
- Code coverage doesn’t say anything about software that’s not written. It only measures Coverage of written software, i.e., the code itself.
- Code Coverage will not check omitted functions. If a specified function isn’t implemented, code coverage won’t say anything about them. It only looks at existing structures.
To have a quality program, we need to have good code coverage, that should be paired with a robust test suite. This will protect the integrity of your system.
How to Select A Code Coverage Tool
When looking for a code coverage tool, you need to ask yourself some questions.
- Is the tool easy to use?
- Does it support different levels of Coverage?
- Which languages does the tool support?
- Do the reports generated by the tool provide enough information?
- Is the tool user friendly?
- Does the tool support backup for bugs?
Unfortunately, not all tools are good enough.
- RKTracer is easy to use the tool.
- It also supports all coverage levels.
- Speedy analysis. It runs hundreds of files within seconds.
- It can generate test reports without unit tests.
- Reports are easy to understand. Further, you can merge them with other platforms.
- Ready to use Jenkins and SonarQube plugins.
- It integrates with in-house CI.
- Team with over 20 years of support experience.