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Coding is not an easy task, and it is a time-consuming activity. In order to make the process of writing code more manageable, various tools have been developed that help automate different tasks. Code coverage tools do just that.
Code coverage tools provide a way to measure how much of the code is executed when running tests. This information can be used to identify which parts of the code need more testing and also provides a way of assessing the quality of the tests themselves.
In this post, we will take a look at some of the most popular code coverage tools and how they can be used to improve your testing process.
What Is Code Coverage?
In software testing, code coverage measures the degree to which the source code of a program is executed when a particular test suite runs. Basically, a higher code coverage percentage means better test coverage.
What Are Code Coverage Tools?
Scrum and other Agile processes place a strong emphasis on delivering quality software products. Various quality assurance activities are performed throughout the project’s lifespan to ensure that the product meets all customer expectations. Code coverage is one of those activities, and code coverage tools aid this process.
Code coverage tools monitor the execution of your program in order to identify which parts of the code have been executed and which have not. This can be a valuable metric for assessing the quality of your tests and ensuring that they provide adequate coverage of your codebase.
This information can also be used to improve the quality of your code by helping you find and fix bugs, and optimize the performance of your software.
What Is JaCoCo Code Coverage?
JaCoCo is an open test coverage toolkit for the Java programming language. It produces line-by-line code coverage information from bytecode; thus, it can be used with all languages that make Java bytecode, including Scala, Kotlin, and Android libraries and frameworks.
JaCoCo code coverage uses a modular design and allows you to create custom plugins easily. The JaCoCo distribution mainly provides three metrics:
- Line coverage: How many lines/statements are executed
- Branch coverage: How many branches (if/else, switch, etc.) are covered
- Method coverage: How many methods are invoked
What Is Cobertura?
Cobertura is another free and open-source Java code coverage tool that measures the amount of code covered by tests. It can be used to identify which parts of your Java program lack test coverage.
Cobertura generates reports in HTML and XML formats, which makes it easy to view results and share them with other team members. It is basically a reporting tool that tells you how much of your code is covered by tests.
JaCoCo vs. Cobertura
In Java, two popular tools for measuring code coverage are JaCoCo and Cobertura. JaCoCo and Cobertura are both open-source tools used for measuring code coverage. JaCoCo is newer and under active development, while Cobertura has been around since 2004. However, both tools produce accurate and consistent results.
In the JaCoCo vs. Cobertura debate, some key differences can be observed. JaCoCo is a pure Java tool and does not require any particular configuration, while Cobertura works best with Java projects that use Eclipse or Maven for build automation. JaCoCo also supports a broader range of coverage metrics than Cobertura.
In terms of performance, JaCoCo is generally faster than Cobertura. This is because JaCoCo uses a more efficient algorithm for calculating coverage data. However, Cobertura can be configured to use less memory than JaCoCo, so it may be a better choice for projects with large codebases.
JaCoCo is the clear winner in terms of features and performance. It supports a wider range of coverage types, including line, branch, and method coverage. It also has better support for complex code, such as code that uses reflection or Generics.
Cobertura, on the other hand, only supports branches or line coverage. However, Cobertura is still viable for Java projects using Eclipse or Maven.
Best Code Coverage Tools
There are many test code coverage tools available, but some java code coverage tools are better than the rest. Each of these tools has its own unique features and benefits, but overall, they all help improve your codebase's quality by ensuring that your test suite covers all of the code.
Here is our list of the best code coverage tools:
Coverage.py
Coverage.py is a Python tool that analyzes your code to determine which parts of it have been executed by your test suite and which have not. The latest version of the tool is Coverage.py 6.4.1 which was released on June 2, 2022. This version is supported on Python versions 3.7 through 3.11.ob3 and PyPy3 7.3.8.
It's open-source and easy to use, making it a popular choice among Python developers. By default, it can measure line coverage, but it can also measure branch coverage and show you which tests cover each line of code.
Moreover, this coverage tool can produce numerous reports using different formats, including an HTML report, text, JSON, and XML output. The coverage tool offers API and an SQLite database for users who wish to utilize its advanced features.
Bullseye Coverage
Bullseye Coverage is a commercial code coverage tool that supports C and C++ to improve the quality of software used by medical, automotive, communications, aerospace, and many more vital systems. It also offers some unique features not found in other tools, such as the ability to create custom reports.
This Java code coverage tool can be integrated into various development environments, including Microsoft Visual Studio, Eclipse, and Makefiles. In addition, Bullseye Coverage performs coverage measurement at the source code level instead of the object code level, which makes it easier to adapt to a wide range of environments and CPU architecture.
The tool also helps exclude any unwanted code from the project and export data in XML and CSV format. Another unique feature about it is that it automatically saves and loads data, which can be used to monitor the progress of a project.
Moreover, the tool offers merging capabilities to combine the coverage data of multiple test runs into one report. The tool provides function coverage metrics, which is a popular choice among developers. Lastly, it can be used to create custom reports using the data collected by the tool.
Ncover
Ncover is a commercial .NET code coverage tool that offers various features to help developers improve the quality of their software. It is the most popular and most powerful .NET code coverage tool available. It can be used to measure line coverage, branch coverage, and method coverage.
In addition, it can be used to generate HTML reports, XML reports, and text reports. Ncover also offers a unique design that reduces overall memory consumption through a series of memory, cache, and data structure optimizations. The coverage tool also gives the ability to manage multiple projects and execution runs.
This can be useful if parts of the code are not relevant to the current test or if the developer wants to focus on a specific area of the code. Ncover also offers an API that allows developers to create their custom reports and supports both 32 and 64-bit systems. The code coverage tool takes advantage of the increased processing power on 64-bit systems.
Vector Software
Vector Software is a leading provider of software development tools that help companies improve the quality of their software. The company’s products are used by some of the world’s largest organizations, including NASA.
The Vector Software flagship product is VectorCAST, a tool that helps developers ensure that their code is properly tested. VectorCAST can be used to perform unit, integration, and system testing. It also provides support for test automation and continuous integration.
Vector Software also offers several other tools, including:
- VectorTEST: A tool for testing software on embedded systems
- VectorCAST/Ada: A tool specifically for testing Ada code
- VectorCAST/C++: A tool specifically for testing C++ code
- Vector/QA: A tool for test management and quality assurance
- TESTinsights: Extends the functionality of VectorCAST
- VectorCAST/Coupling: Automates the analysis and verification of control couplings for C and C++ sources
Devel::Cover
Devel::Cover is a Perl module that provides code coverage analysis for Perl programs. It can be used to measure the amount of code executed during testing and identify which parts of the code are not being tested.
This is one of the best code coverage tools around, since it has a wide range of functionalities, such as determining which tests to create to achieve full coverage of the code.
Devel::Cover is available as an open-source software package that exports numerous report formats, including text and HTML. Annotations to reports are also possible, and the gcov2perl program can be used to convert gcov data into Devel::Cover's own format. This action enables developers to use Devel::Cover with any software for which gcov data is available.
Moreover, it has a wide range of configuration options that can be used to customize its operation.
dotCover
JetBrains dotCover is a .NET tool that provides code coverage analysis for managed and native applications. It can be integrated with Visual Studio and JetBrains Rider, which also helps the code editor analyze and visualize the code coverage.
JetBrains dotCover has several features that make it a powerful code coverage tool, including:
- The ability to measure and calculate code coverage for multiple platforms, including .NET Framework, .NET Core, and Mono
- Support for various report formats, including HTML, XML, and JSON
JetBrains dotCover has manual test sessions that can be used to profile the application and determine which parts of the code are not being tested.
It also executes and debugs unit tests using the command-line utility or in Visual Studio, wherein developers can assess the quality of their code. The unit testing framework can be used in MSTest, NUnit, xUnit, and MSpec.
dotCover can detect potential risk areas in the code with a Hot Spots view and identify the most complex methods with the least test coverage. The tool also provides coverage analysis with an intuitive graphical representation while automatically re-running the tests affected by your latest code changes.
The continuous testing mode feature can be switched on for any unit test session, which can help you choose the test you want to keep re-running and which unit test to run in the traditional way.
Clover (Atlassian)
Clover code coverage is a commercial tool from Atlassian, the company behind the popular JIRA software. Clover provides both a standalone application and an IDE plugin for various IDEs, including IntelliJ IDEA and Eclipse.
Clover offers several features that make it one of the most powerful code coverage tools, including:
- The ability to measure and calculate code coverage for multiple languages, including Java, Groovy, and AspectJ
- Support for various report formats, including text, HTML, XML, PDF, and JSON
Clover code coverage tool is open-sourced and integrates with popular Continuous Integration (CI) servers such as Jenkins, Hudson, and Bamboo. It can also be used with Atlassian's own Bitbucket Server product.
In addition, the coverage metrics of the clove code coverage tool for each project can be the method, statement, branch, global coverage, and per-test coverage. It also has built tool integrations such as command line, Ant, Maven, Grails, and Gradle.
Parasoft Jtest
Parasoft Jtest is one of the best Java code coverage tools that provide both static and dynamic analysis of Java code. Jtest can be used to measure the amount of code that is executed during testing, and to identify which parts of the code are not being tested.
Parasoft Jtest helps increase developer productivity by automatically creating unit tests for the application and achieving code coverage targets. Moreover, the smart test execution feature can help get faster feedback from CI and within your IDE.
They also offer a test impact analysis wherein it can automatically identify and run only the tests affected by your code changes. The compliance verification documentation can also be generated to check if the code adheres to various coding standards.
In unit testing, Jtest can collect coverage data from different build systems, such as Ant, Maven, or Gradle, IDEs (i.e., Eclipse and IntelliJ), and the JUnit testing framework. Furthermore, JTest can easily integrate with third-party test execution software and still provide effective test traceability.
The reports can be in an HTML or PDF format or even on a web server which can combine coverage results of different test runs into one dynamic dashboard.
Conclusion
Code coverage tools are a valuable asset for any development team and can help improve the quality of their code. Not only do these tools speed up the code writing process, they’re also incredibly efficient at pointing out weak spots in code so that teams can quickly make adjustments.
This article has touched on some of the best code coverage tools, all of which can be used to measure the amount of code executed during testing and identify which parts of the code are not being tested.
Many different code coverage tools are available, each with its advantages and disadvantages; the right code coverage tool for your project will depend on your specific needs. Creating error-free codes is important in every organization, and code coverage tools are one of the very best ways to achieve that goal.
With GoRetro, you can hold Agile retrospectives and take your code coverage to the next level. Reflect on the development process as a team, so that you can continue to improve and speed up your code coverage for greater efficiency all around.
