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Monitoring and analyzing code coverage fosters a data-driven culture to inform decisions. Utilizing code coverage effectively enhances productivity, testing efficiency, and application reliability. It minimizes risks and facilitates data-driven release decisions by leadership.
Code coverage visibility is a cornerstone of elevating confidence in software quality. By providing a comprehensive view of which lines of code have been tested, developers, testers, and stakeholders minimize the likelihood of undetected quality and security issues and release with greater confidence.
Identify areas of insufficient testing. Track code coverage across all automated testing practices to mitigate risks and ensure release-ready applications.
Locate areas where untested code is present. Quickly create new test cases to address coverage gaps and ensure thorough testing.
Analyze code coverage that correlates to new and recently modified code to mitigate risks by ensuring sufficient testing of code changes.
Meet code coverage targets faster. Merge and correlate unit testing coverage with code coverage collected from all automated testing efforts.
Ensure thorough testing, fulfill regulatory requirements, enhance fault detection, reduce risks, and improve security assurance with Parasoft’s code coverage solutions. Verify that every line of code has been tested to reduce the likelihood of undetected defects causing system failures.
Ensure code coverage for embedded safety and security-critical applications by employing a blend of techniques with Parasoft C/C++test and C/C++test CT to meet compliance standards. Code instrumentation is central to this effort, which involves integrating additional code into the user codebase to track the execution of statements, branches, and MC/DC code structures. Often, code coverage must be gathered directly from the target hardware, which both C/C++ testing solutions do.
Parasoft C/C++test and C/C++test CT, together with Parasoft DTP, collects coverage metrics and produces documentation that’s indispensable for safety-critical applications. Generated reports detail each line of code’s execution status—whether it’s fully, partially, or not—serve as a critical reference for development teams and certification auditors, facilitating the assessment of code coverage compliance.
It’s imperative that code coverage analysis tools are TÜV-certified for use in safety-critical applications, like both C/C++test and DTP.
70%
Code coverage reached with automated test generation and execution.
Automated
Tool qualification process to reach code coverage requirements.
Collect, monitor, and analyze C/C++ code coverage data generated during dynamic analysis testing, including unit, integration, and system testing phases with our testing solutions for C and C++ software development.
Fundamental in software testing and quality assurance, code coverage metrics offer valuable insights into testing thoroughness and pinpoint areas that may require more attention. Parasoft’s C and C++ testing solutions collect various types of code coverage metrics during dynamic analysis testing, whether conducted locally or via integration with the CI/CD pipeline.
Embedded developers can examine coverage results directly in a preferred code editor, ensuring a streamlined workflow. Teams can guarantee adherence to requirements with tailored quality gates to automatically validate builds based on predefined code coverage metrics.
Our solutions intelligently aggregate coverage information from various execution runs, including testing on target hardware, providing a comprehensive understanding of the code’s test coverage. By analyzing coverage at granular levels like method, class, file, or project, teams can accurately pinpoint areas with insufficient coverage and higher risk.
DTP’s comprehensive reports and dashboards show aggregated, in-depth test coverage and compliance metrics. Teams can automate requirements traceability between test cases, code artifacts, and requirements to ensure a cohesive, efficient development process required in safety-critical development.
Learn how a leading financial firm leveraged Parasoft Jtest to:
75%
Reduction of software problem reports issued during development.
Decreased
Development costs with self-verification.
Collect, monitor, and analyze code coverage from unit and functional testing for Java and .NET applications. Drive higher levels of code coverage by understanding what lines of code have been tested and targeting coverage gaps.
Development and testing teams can execute unit tests either locally or within the CI/CD pipeline and effortlessly examine coverage results directly within the developer IDE with Parasoft’s Java code coverage and .NET code coverage tools. Here’s what else they can do:
Learn how a leading financial firm leveraged Parasoft Jtest to:
85%
Code coverage achieved in a few weeks.
Teams modernizing legacy applications use analysis provided by our code coverage tools for Java, .NET, C#, C, and C++ applications to create a strategy that safeguards existing functionality when making changes.
With insight into previously tested legacy applications, teams can evaluate the effectiveness of their inherited regression test suite and determine if new test cases are needed to strengthen their regression safety net.
For legacy applications with low coverage, Parasoft Jtest or C/C++test rapidly generate unit tests in bulk that can be run in regression to ensure that the new functionality introduced does not impact the existing functionality.
In parallel with regression testing, teams often adopt a coverage policy that helps them create a baseline for new development. However, it can be challenging to ensure high code coverage on modified code when the existing legacy code has low levels of coverage.
Parasoft enables teams to collect, analyze, and monitor code coverage metrics that correlate specifically with new or modified code. This ensures that all new or changed code is thoroughly tested and meets the organization’s quality standards and incrementally increases the coverage across the codebase.
Read Blog: Testing Legacy Code & 3 Steps to Update »
Code modifications can introduce new bugs and break existing code functionality. Mitigate these risks by tracking code coverage specifically associated with modified code and easily enforcing coverage policies to ensure all modified code is well tested.
Publish code coverage captured during automated test execution in the CI/CD pipeline into Parasoft DTP for advanced build-to-build reporting and analysis. Set quality gates for modified code coverage in the CI/CD pipeline, and leverage Parasoft DTP’s modified code coverage widget to analyze and view code coverage that correlates only to new code or to modified lines of code.
By ensuring any new or modified code has high levels of code coverage, development teams can mitigate the risk of untested changes slipping into production and incrementally increase the overall test coverage of their codebase.
Read Blog: Application Coverage Is the Most Powerful Metric You’re Not Measuring »
In distributed microservices architectures, gathering coverage from end-to-end test runs is challenging due to the interconnected services and complexity of interactions between them. Our coverage solutions simplify gathering functional testing code coverage for Java and .NET services within complex microservice architectures.
Collect and analyze code coverage from the testing of distributed Java and .NET microservices. Easily correlate which lines of code in each individual microservice are tested during the execution of automated end-to-end functional tests and increase test thoroughness for higher quality and more reliable software. Here’s how it works:
Code coverage collection also enables test impact analysis workflows to reduce the number of end-to-end tests that must be re-run to validate code changes.
Read Blog: Get a Better View of Your Code Coverage »
Bring visibility to your manual testing practice by collecting and analyzing code coverage during test runs. It helps your team close the gap between manual and automated testing, so you can understand the true impact of manual efforts.
Leverage CTP in combination with DTP for reporting and analysis. Code coverage agents for Java and .NET are deployed to capture execution data as tests are performed.
Testers can import manual test definitions from their test management system in CTP’s intuitive web interface. As testers execute their test cases, CTP enables users to easily manage the coverage agents in synchronization with their testing, automatically capturing exactly which parts of the code are exercised by each test case.
After testing is complete, the collected data is automatically published to Parasoft DTP, where detailed reports correlate the manual test cases with the exercised portions of code. This gives teams a clear picture of what areas were covered by manual testing, identifies gaps and testing redundancies, and supports auditing or compliance needs. The manual testing coverage can also be merged and correlated with automated testing coverage providing the team with a complete view of coverage across the application.
Gain a complete view of test strategy effectiveness and make data-driven decisions on the release readiness of Java, .NET, C#, C, and C++ applications.
Our solutions capture code coverage from multiple testing practices, like unit testing, API testing, microservices testing, web UI testing, integration testing, and end-to-end testing. Results go to Parasoft DTP for build-to-build trend analysis.
Application code coverage monitoring capabilities collect and analyze code coverage during the execution of automated tests regardless of the testing framework.
DTP’s code coverage dashboards correlate and merge code coverage results from multiple test types to determine areas of low test coverage with high risks. Teams gain actionable insights on where tests are needed to fill code coverage gaps and mitigate the risk of untested code in the hands of end users.
With the data collected by Parasoft code coverage tools, teams can optimize test execution in their CI/CD pipeline with test impact analysis. Use test impact analysis to reduce the number of tests needed to be executed to validate application changes by identifying and running only the subset of test cases that correlate to code modifications.
Read Blog: Measuring Code Coverage: Guide to Effective Testing »
