Best Code Coverage Tools for Kubernetes

Find and compare the best Code Coverage tools for Kubernetes in 2024

Use the comparison tool below to compare the top Code Coverage tools for Kubernetes on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    IntelliJ IDEA Reviews
    Top Pick

    IntelliJ IDEA

    JetBrains

    $16.90 per user per month
    22 Ratings
    IntelliJ IDEA, a JetBrains IDE, is the leading IDE for Java and Kotlin development. It helps you stay productive with a suite of efficiency-enhancing features such as intelligent coding assistance, reliable refactorings, instant code navigation, built-in developer tools, web and enterprise development support, and much more.
  • 2
    GoLand Reviews

    GoLand

    JetBrains

    $199 per user per year
    All Go developers, whether they are newbies or professionals, can use the on-the-fly error identification and suggestions to fix it. One-step undo and intelligent code completion are all available. Documentation hints and dead code detection are also available. It takes a lot of effort and time to understand legacy, team, and foreign projects. GoLand code navigation allows you to quickly switch between shadowed methods, implementations and usages. You can jump between files, types, and other symbols. You can also find their usages, and examine them with a convenient grouping by type. You can run and debug your applications with powerful built-in tools. You can create and debug tests with no additional plugins or configuration work, and you can test your applications directly in the IDE. The IDE includes a built-in Code Coverage tool to ensure that your tests do not miss any important information.
  • 3
    Codacy Reviews

    Codacy

    Codacy

    $15.00/month/user
    Codacy is an automated code review tool. It helps identify problems through static code analysis. This allows engineering teams to save time and tackle technical debt. Codacy seamlessly integrates with your existing workflows on Git provider as well as with Slack and JIRA or using Webhooks. Each commit and pull-request includes notifications about security issues, code coverage, duplicate code, and code complexity. Advanced code metrics provide insight into the health of a project as well as team performance and other metrics. The Codacy CLI allows you to run Codacy code analysis locally. This allows teams to see Codacy results without needing to check their Git provider, or the Codacy app. Codacy supports more than 30 programming languages and is available in free open source and enterprise versions (cloud or self-hosted). For more see https://www.codacy.com/
  • 4
    SonarCloud Reviews

    SonarCloud

    SonarSource

    €10 per month
    SonarCloud automatically analyzes and decorates pull request branches to maximize your throughput. To prevent undefined behavior from affecting end-users, catch tricky bugs. Security Hotspots will help you identify and fix vulnerabilities that could compromise your app. It takes just a few mouse clicks to get your code up and running. Instant access to the most recent features and enhancements. Project dashboards keep stakeholders and teams informed about code quality and releasability. Show your communities that you care about awesome by displaying project badges. Your entire stack should be concerned about code quality and security. We cover 24 languages, including C++, Java, Python, and many other. Transparency is a good thing and the trend is growing. Join the fun! Open-source projects are completely free!
  • 5
    Code Intelligence Reviews
    Our platform uses a variety of security techniques, including feedback-based fuzz testing and coverage-guided fuzz testing, in order to generate millions upon millions of test cases that trigger difficult-to-find bugs deep in your application. This white-box approach helps to prevent edge cases and speed up development. Advanced fuzzing engines produce inputs that maximize code coverage. Powerful bug detectors check for errors during code execution. Only uncover true vulnerabilities. You will need the stack trace and input to prove that you can reproduce errors reliably every time. AI white-box testing is based on data from all previous tests and can continuously learn the inner workings of your application. This allows you to trigger security-critical bugs with increasing precision.
  • 6
    Jtest Reviews
    Maintain high-quality code while adhering to agile development cycles. Jtest's extensive Java testing tools will ensure that you code flawlessly at every stage of Java software development. Streamline Compliance with Security Standards. Ensure that your Java code conforms to industry security standards. Automated generation of compliance verification documentation Get Quality Software Out Faster Java testing tools can be integrated to detect defects faster and more efficiently. Reduce time and costs by avoiding costly and complicated problems later. Increase your return on unit testing. Create a set of JUnit test suites that are easy to maintain and optimize for code coverage. Smart test execution allows you to get faster feedback from CI as well as within your IDE. Parasoft Jtest integrates seamlessly into your development ecosystem and CI/CD pipeline for real-time, intelligent feedback about your testing and compliance progress.
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