Need advice about which tool to choose?Ask the StackShare community!
Codecov vs Coverity Scan: What are the differences?
Introduction: Code coverage tools play a crucial role in software development, helping developers identify the areas of code that are not being tested. Codecov and Coverity Scan are two popular code coverage tools used by developers. In this comparison, we will highlight the key differences between Codecov and Coverity Scan.
Integration: Codecov can be easily integrated with popular continuous integration (CI) tools such as GitHub Actions, Jenkins, and Travis CI. It provides seamless integration through plugins and supports multiple programming languages, making it versatile for different software projects. On the other hand, Coverity Scan focuses more on static analysis of code and tends to be integrated into the development process as part of a code review or build process rather than directly with CI tools.
Code Coverage Metrics: Codecov provides detailed code coverage metrics, including line coverage, branch coverage, and test coverage trending over time. It supports multiple coverage report formats, making it adaptable for different project setups. Coverity Scan, on the other hand, primarily focuses on identifying code defects and vulnerabilities rather than code coverage metrics. It provides detailed reports highlighting potential security flaws, resource leaks, and other defects.
Community and Support: Codecov has an active community and provides robust documentation, making it easier for developers to get started and resolve issues. It also offers personalized support through email and chat. Coverity Scan is a commercial tool provided by Synopsys and offers customer support through a dedicated help desk. However, the community support and documentation for Coverity Scan may be relatively limited compared to Codecov.
Pricing: Codecov offers both free and paid plans, making it accessible to developers and organizations of different sizes. The free plan provides basic code coverage features, while the paid plans offer additional functionalities and support. Coverity Scan, being a commercial tool, requires a paid license for full access to its features. The pricing may vary depending on the specific requirements and scale of the project.
Focus of Analysis: Codecov primarily focuses on code coverage analysis and provides insights into test quality and the thoroughness of the test suite. It helps identify areas of the codebase that may require additional testing. On the other hand, Coverity Scan specializes in static analysis and focuses on identifying potential defects, vulnerabilities, and bad coding practices in the codebase that could lead to problems in production.
Ease of Use: Codecov offers a user-friendly interface and intuitive features that make it easy for developers to navigate and interpret code coverage reports. Its integrations with CI tools simplify the setup process. Coverity Scan, while powerful in terms of defect detection, may have a steeper learning curve due to its more advanced static analysis capabilities and the need to understand and interpret the reports generated.
In Summary, Codecov provides seamless integration with CI tools, extensive code coverage metrics, active community support, flexible pricing options, focuses on code coverage analysis, and offers an intuitive user interface. Coverity Scan, on the other hand, focuses on static analysis, offers commercial licensing, highlights code defects and vulnerabilities, and may require a deeper understanding of its reports.
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 Coverity Scan
Sign up to add or upvote prosMake informed product decisions
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