Best Code Coverage Tools for Cloud

Parasoft C/C++test measures structural code coverage during unit, integration, and functional testing, supporting metrics including statement, branch, MC/DC, call, and object/assembly coverage. Coverage can be captured on host, simulator, or target hardware, and integrates with open-source frameworks like GoogleTest, Boost.Test, and CppUnit for teams using those instead of C/C++test's built-in framework. Results feed into Parasoft DTP for centralized, per-test coverage reporting and trend tracking across builds, helping teams both identify gaps and satisfy the coverage requirements mandated by standards like ISO 26262 and DO-178C.

Sahi Pro is a no-code test automation tool for web, desktop, mobile, and SAP applications. Sahi Pro empowers business testers and automation engineers to streamline their test automation processes. Sahi Pro reduces the time, effort, and complexity involved in test automation, making it an ideal choice for various domains including automobile, healthcare and BFSI. Features: 1. Non-flaky Test Execution - For reliable test results and reduced time wastage in analysis of false-positives or false-negatives. 2. Supports Multiple Technologies - Achieve end to end automation across technologies. 3. No-code Automation - Enable non-technical business testers to automate. 4. Integrations - Integrate and work with your existing ecosystem. Testers using Sahi Pro easily automate complex tests without writing code. With Sahi Pro, you can achieve faster release cycles, improved software quality, & reduced costs. Our customers love Sahi Pro for its speed, flexibility, and ease of use.

Velocity provides in-depth, contextual analytics that equip engineering leaders to support stuck team members, address team roadblocks, and streamline engineering processes. Actionable metrics for engineering leaders. Velocity turns data from commits and pull requests into the insights you need to make lasting improvements to your team’s productivity. Quality: Automated code review for test coverage, maintainability and more so that you can save time and merge with confidence. Receive automated code review comments on your pull requests. Our 10-point technical debt assessment provides real-time feedback, so you can save time and focus on what matters in your code review discussions. Get test coverage right, every time. See coverage line by line within diffs. Never merge code without sufficient tests again. At a glance, identify frequently changed files that have inadequate coverage and maintainability issues. Track your progress against measurable goals, day-by-day.

Codacy is a comprehensive platform for code quality and security that helps development teams build secure, maintainable, and compliant software. It integrates across the entire development lifecycle, from IDE to production, providing real-time feedback and automated checks. Codacy analyzes code repositories, enforces quality standards, and detects vulnerabilities before deployment. With AI Guardrails, it also protects against risks introduced by AI-generated code. The platform centralizes rules and policies, ensuring consistency across teams and projects. Developers benefit from automated pull request checks, test coverage tracking, and actionable insights. Overall, Codacy enables faster development without compromising security or code quality.

Do you want everything set up for you instantly, or do you want to customize your environment and your workflow? CodeShip lets the developer pick the path that’s best for them, to maximize productivity and let teams evolve over time. From deployments to notifications to code coverage to security scanning and on-premise SCMs, CodeShip lets you integrate with any tool, service or cloud you need for your organization’s perfect workflow. Not only do we make CodeShip easy to use, we also provide fast and thorough developer support. When you need help or identify a problem, you want to talk to someone technical sooner rather than later, and that’s what you’ll get with CodeShip. You can get your builds and deployments working in less than 5 minutes with CodeShip’s turnkey environment and simple UI. From there, you can evolve into more sophisticated workflows and config-as-code as your projects grow.

dotCover is a .NET unit testing and code coverage tool that works right in Visual Studio and in JetBrains Rider, helps you know to what extent your code is covered with unit tests, provides great ways to visualize code coverage, and is Continuous Integration ready. dotCover calculates and reports statement-level code coverage in applications targeting .NET Framework, .NET Core, Mono for Unity, etc. dotCover is a plug-in to Visual Studio and JetBrains Rider, giving you the advantage of analyzing and visualizing code coverage without leaving the code editor. This includes running unit tests and analyzing coverage results right in the IDEs, as well as support for different color themes, new icons and menus. dotCover comes bundled with a unit test runner that it shares with another JetBrains tool for .NET developers, ReSharper. dotCover supports continuous testing, a modern unit testing workflow whereby dotCover figures out on-the-fly which unit tests are affected by your code changes.

Try your first CodeRush feature right now and see instantly just how powerful it is. Refactoring for C#, Visual Basic, and XAML, with the fastest test .NET runner available, next generation debugging, and the most efficient coding experience on the planet. Quickly find symbols and files in your solution and easily navigate to code constructions related to the current context. CodeRush includes the Quick Navigation and Quick File Navigation features, which make it fast and easy to find symbols and open files. Using the Analyze Code Coverage feature, you can discover what parts of your solution are covered by unit tests, and find the at-risk parts of your application. The Code Coverage window shows percentage of statements covered by unit tests for each namespace, type, and member in your solution.

Advanced fuzzing solution that combines guided fuzzing with symbolic execution, a patented technology from CMU. Mayhem is an advanced fuzz testing solution that dramatically reduces manual testing efforts with autonomous defect detection and validation. Deliver safe, secure, reliable software with less time, cost, and effort. Mayhem’s unique advantage is in its ability to acquire intelligence of its targets over time. As Mayhem’s knowledge grows, it deepens its analysis and maximizes its code coverage. All reported vulnerabilities are exploitable, confirmed risks. Mayhem guides remediation efforts with in-depth system level information, such as backtraces, memory logs, and register state, expediting issue diagnosis and fixes. Mayhem utilizes target feedback to custom generate test cases on the fly -- meaning no manual test case generation required. Mayhem offers access to all of its test cases to make regression testing effortless and continuous.

Automating the creation and deployment of component test harnesses, test stubs and test drivers is a cinch thanks to OneTest Embedded. With a single click from any development environment, one can profile memory and performance, analyze code coverage and visualize program execution behavior. Additionally, OneTest Embedded helps be more proactive in debugging, while identifying and assisting in fixing code before it breaks. Allows for a virtual cycle of test generation, while executing, reviewing and testing improvement to rapidly achieve full test coverage. One click is all it takes to build, execute on the target, and generate reports. Helps preempt performance issues and program crashes. Additionally, can be adapted to work with custom memory management methods used in embedded software. Provides visibility on thread execution and switching to develop a deep understanding of the behavior of the system under test.

Our platform uses various security techniques, including coverage-guided and feedback-based fuzz testing, to automatically generate millions of test cases that trigger hard-to-find bugs deep within your application. This white-box approach protects against edge cases and speeds up development. Advanced fuzzing engines generate inputs that maximize code coverage. Powerful bug detectors check for errors during code execution. Uncover true vulnerabilities only. Get the input and stack trace as proof, so you can reliably reproduce errors every time. AI white-box testing uses data from all previous test runs to continuously learn the inner-workings of your application, triggering security-critical bugs with increasingly high precision.