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Codecov vs JaCoCo: What are the differences?
Introduction
In this Markdown code, we will discuss the key differences between Codecov and JaCoCo, two popular code coverage tools.
Integration: Codecov is a third-party tool that integrates with various Continuous Integration (CI) platforms like Travis CI, CircleCI, and Jenkins. It generates reports by extracting data from the CI platforms. On the other hand, JaCoCo is a code coverage library that can be directly integrated into the build process using build tools like Maven or Gradle.
Language Support: Codecov provides support for multiple programming languages, including Java, Python, JavaScript, Ruby, and more. It can be used for code coverage analysis in a wide range of languages. However, JaCoCo is primarily focused on Java applications and offers comprehensive support specifically for Java projects.
Report Generation: Codecov generates coverage reports in a visual format with user-friendly dashboards. These reports provide a clear overview of code coverage metrics, such as line coverage, branch coverage, and function coverage. JaCoCo, on the other hand, generates coverage reports in HTML, XML, and CSV formats, which can be customized and further processed as per the project requirements.
Test Execution: Codecov requires the test execution to be performed separately, and then it can gather the coverage data from the test runs. In contrast, JaCoCo can collect code coverage information during runtime, by attaching to the JVM (Java Virtual Machine), without the need for separate test executions.
Accuracy: Since Codecov relies on coverage data provided by different CI platforms and test environments, the accuracy of the coverage reports can vary based on the quality of the test cases and the execution environment. JaCoCo, on the other hand, analyzes the bytecode directly and provides more accurate coverage information at the method, line, and branch levels.
Community Support: Codecov has a large and active community of users and contributors, which ensures regular updates and improvements to the tool. The community provides support through forums, documentation, and issue tracking. JaCoCo also has a significant user base but relatively less community support compared to Codecov.
In summary, Codecov is a third-party tool with extensive language support and integration capabilities, while JaCoCo is a code coverage library specifically designed for Java applications, offering accurate coverage analysis during runtime.
My website is brand new and one of the few requirements of testings I had to implement was code coverage. Never though it was so hard to implement using a #docker container.
Given my lack of experience, every attempt I tried on making a simple code coverage test using the 4 combinations of #TravisCI, #CircleCi with #Coveralls, #Codecov I failed. The main problem was I was generating the .coverage
file within the docker container and couldn't access it with #TravisCi or #CircleCi, every attempt to solve this problem seems to be very hacky and this was not the kind of complexity I want to introduce to my newborn website.
This problem was solved using a specific action for #GitHubActions, it was a 3 line solution I had to put in my github workflow file and I was able to access the .coverage
file from my docker container and get the coverage report with #Codecov.
Pros of Codecov
- More stable than coveralls17
- Easy setup17
- GitHub integration14
- They reply their users11
- Easy setup,great ui10
- Easily see per-commit coverage in GitHub5
- Steve is the man5
- Merges coverage from multiple CI jobs4
- Golang support4
- Free for public repositories3
- Code coverage3
- JSON in web hook3
- Newest Android SDK preinstalled3
- Cool diagrams2
- Bitbucket Integration1
Pros of JaCoCo
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Cons of Codecov
- GitHub org / team integration is a little too tight1
- Delayed results by hours since recent outage0
- Support does not respond to email0