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Codecov

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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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

Decisions about Codecov and Coverity Scan

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.

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Pros of Codecov
Pros of Coverity Scan
  • 17
    More stable than coveralls
  • 17
    Easy setup
  • 14
    GitHub integration
  • 11
    They reply their users
  • 10
    Easy setup,great ui
  • 5
    Easily see per-commit coverage in GitHub
  • 5
    Steve is the man
  • 4
    Merges coverage from multiple CI jobs
  • 4
    Golang support
  • 3
    Free for public repositories
  • 3
    Code coverage
  • 3
    JSON in web hook
  • 3
    Newest Android SDK preinstalled
  • 2
    Cool diagrams
  • 1
    Bitbucket Integration
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    Cons of Codecov
    Cons of Coverity Scan
    • 1
      GitHub org / team integration is a little too tight
    • 0
      Delayed results by hours since recent outage
    • 0
      Support does not respond to email
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      What is Codecov?

      Our patrons rave about our elegant coverage reports, integrated pull request comments, interactive commit graphs, our Chrome plugin and security.

      What is Coverity Scan?

      Coverity's implementation of static analysis can follow all the possible paths of execution through source code (including interprocedurally) and find defects and vulnerabilities caused by the conjunction of statements that are not errors independent of each other.

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      What companies use Codecov?
      What companies use Coverity Scan?
      See which teams inside your own company are using Codecov or Coverity Scan.
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      What tools integrate with Codecov?
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      What are some alternatives to Codecov and Coverity Scan?
      Code Climate
      After each Git push, Code Climate analyzes your code for complexity, duplication, and common smells to determine changes in quality and surface technical debt hotspots.
      Coveralls
      Coveralls works with your CI server and sifts through your coverage data to find issues you didn't even know you had before they become a problem. Free for open source, pro accounts for private repos, instant sign up with GitHub OAuth.
      SonarQube
      SonarQube provides an overview of the overall health of your source code and even more importantly, it highlights issues found on new code. With a Quality Gate set on your project, you will simply fix the Leak and start mechanically improving.
      Codacy
      Codacy automates code reviews and monitors code quality on every commit and pull request on more than 40 programming languages reporting back the impact of every commit or PR, issues concerning code style, best practices and security.
      JaCoCo
      It is a free code coverage library for Java, which has been created based on the lessons learned from using and integration existing libraries for many years.
      See all alternatives