Use the comparison tool below to compare the top Code Coverage tools on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Parasoft's AI-powered testing platform and automated solutions help organizations deliver high-quality software continuously. Parasoft's proven technology reduces the time, effort and cost associated with delivering secure, compliant, and reliable software. This is done by integrating everything, from deep code analysis and API testing to web UI testing and unit testing, as well as service virtualization and full code coverage, into delivery pipelines. Bringing all this together, Parasoft's award-winning reporting and analytics dashboard provides a centralized view of quality, enabling organizations to deliver with confidence and succeed in today's most strategic ecosystems and development initiatives--security, safety-critical, Agile, DevOps, and continuous testing.
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Code Climate
Code Climate
1 RatingVelocity provides detailed, contextual analytics that enable engineering leaders to help their team members, resolve team roadblocks and streamline engineering processes. Engineering leaders can get actionable metrics. Velocity transforms data from commits to pull requests into the insights that you need to make lasting improvements in your team's productivity. Quality: Automated code reviews for test coverage, maintainability, and more so you can save time and merge with confidence. Automated code review comments for pull requests. Our 10-point technical debt assessment gives you real-time feedback so that you can focus on the important things in your code review discussions. You can get perfect coverage every time. Check coverage line-by-line within diffs. Never merge code again without passing sufficient tests. You can quickly identify files that are frequently modified and have poor coverage or maintainability issues. Each day, track your progress towards measurable goals. -
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PyCharm
JetBrains
$199 per user per year 21 RatingsAll the Python tools in one location. PyCharm will take care of the routine, saving you time. To make the most of PyCharm's productivity features, you should focus on the important things. PyCharm has all the information you need about your code. PyCharm can help you with intelligent code completion, quick error checking and quick fixes, project navigation, and many other things. The IDE allows you to write clean and maintainable code and helps you maintain control of quality with PEP8 tests, testing assistance and smart refactorings. PyCharm was created by programmers for programmers to give you all the tools you need to create Python code. PyCharm offers smart code completion, code inspections and quick-fixes. It also includes automated code refactorings. -
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IntelliJ IDEA
JetBrains
$14.90 per user per month 23 RatingsIntelliJ IDEA analyzes the code and finds connections between symbols in all files and languages. This information provides in-depth coding guidance, quick navigation, clever errors analysis, and, ofcourse, refactorings. Space gives you a list of the most relevant symbols applicable in the current context. This and other completions are continuously learning from you and move the members of the most commonly used classes and packages to top of the suggestions list so you can choose them faster. This is a deeper version of Smart Completion. It lists all applicable symbols that are accessible through methods or getters within the current context. Let's say you are looking for Project but only have the Module module declaration. Space twice to get module.getProject() without any additional effort. Complete static members Allows you to use constants or static methods easily. It displays a list of symbols that match your input and automatically adds the required import statements. -
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Introducing Xcode 12. Introducing Xcode 12. Xcode 12 creates Universal apps by default to work with Apple Silicon. This is often done without changing a single line. Designed for macOS Big Sur. Xcode 12 looks great in macOS Big Sur. It has a navigator sidebar that extends to the top of your window and clears new toolbar buttons. The default font size for the navigator is a larger one that's easier reading, but you can choose from multiple sizes. You can create a working set within your workspace by creating new document tabs. Document tabs. You can open a new tab by double-clicking, or track the file as you move around the navigator. To create a working set for your current task, you can arrange the document tabs and change how content is displayed within each tab.
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Codecov
Codecov
$10 per user per monthDevelop healthier code. Improve code quality and workflow. Codecov offers a comprehensive suite of tools that allow you to group, merge and archive coverage reports, as well as compare them. Open source. Plans starting at $10/user per month. Ruby, Python and C++ as well as Javascript are all available. All CI products and workflows can be integrated easily. No setup is required. Automatic report merging for all CI languages and languages into one report. You can get custom statuses for any group of coverage metrics. You can review coverage reports by folder, project, and type (unit tests or integration tests). You can comment the detailed report directly in your pull request. Codecov is SOC 2 Type II Certified. This means that Codecov has been audited by a third party and attested to our security practices. -
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NCrunch
NCrunch
$159 per yearNCrunch monitors your code coverage in real time, and displays this in markers right next to your code. This makes it easy for you to see where your coverage is lacking or high. NCrunch was built with complex large-scale projects in mind. The last 12 years have been spent optimizing and scaling NCrunch to meet the requirements of real-world systems with millions of lines and thousands of tests. NCrunch keeps track of all test data and provides you with the most relevant feedback as quickly as possible. The tests that have been affected by your code changes are prioritized for execution using high-performance IL-based change mapping. NCrunch can transfer build and test work to other computers. You can farm tasks to connected machines or scale up to the cloud. Developers can share processing resources, allowing teams to pool their testing resources. -
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GoLand
JetBrains
$199 per user per yearAll 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. -
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SmartBear AQTime Pro
SmartBear
$719 one-time paymentDebugging should not be complicated. AQTime Pro converts complex performance and memory information into easily digestible and actionable insights that allow you to quickly identify the root cause of bugs. Code bugs can drain your life! AQTime Pro makes it simple to find and squash highly differentiated bugs. You can quickly find memory leaks and performance bottlenecks as well as code coverage gaps with just a few clicks using over a dozen profilers. AQTime Pro allows you to find and fix all bugs in one tool, so you can get back to writing high-quality code. Code profilers shouldn't limit you to a single framework or codebase. They can prevent you from finding performance bottlenecks and memory leaks as well as code coverage gaps that are unique to your project. AQTime Pro can be used across multiple codebases or frameworks in a project. It supports many languages, including C/C++ and Delphi,.NET and Java. -
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Go
Golang
FreeIt is now easier than ever to create services with Go thanks to the strong ecosystem of APIs and tools available on major cloud providers. Go allows you to create elegant and fast CLIs using popular open-source packages and a robust standard repository. Go powers fast, scalable web applications thanks to its enhanced memory performance and support of several IDEs. Go supports both DevOps as well as SRE with its fast build times and lean syntax. All you need to know about Go. Get started on a project or refresh your knowledge about Go code. Three sections provide an interactive introduction to Go. Each section ends with a few exercises that allow you to put what you have learned into practice. Anyone can use a web browser to create Go code that we instantly compile, link, then run on our servers. -
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Tarpaulin
Tarpaulin
FreeTarpaulin, a code coverage reporting tool for Cargo build system is named after a waterproof cloth that was used to cover cargo on ships. Tarpaulin currently provides working line coverage, but the results may not be 100% reliable. It has taken a lot of work to get it working on many different projects. However, sometimes unique combinations of packages or build features can cause problems so please report any issues. Check out our roadmap to see the planned features. Linux Tarpaulin's default trace backend is still Ptrace. It will only work with x86_64 processors. This can be changed to llvm coverage instrumentation by using --engine llvm. For Windows and Mac, this is the default collection method. You can also run it in Docker. This is useful for those who don't have Linux but still want to run it locally. during development. For more information, see below. -
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OpenCppCoverage
OpenCppCoverage
FreeOpenCppCoverage, a tool that covers C++ under Windows, is an open-source code cover tool. It is used primarily for unit testing coverage. However, you can also use the tool to determine the executed lines of a program for debugging purposes. Visual Studio support. Visual Studio support. OpenCppCoverage will run your program without you needing to recompile it. HTML reporting, line coverage. Run as Visual Studio Plugin. Jenkins support and optimized build. A regular expression can be used to exclude a line. Coverage for child processes. Coverage aggregation allows you to run multiple code coverages and combine them into one report. Requires Windows Vista and higher. All editions, including the Express edition, require Microsoft Visual Studio 2008 or greater. It should also work with previous versions of Visual Studio. The Test Explorer window can be used to run the tests. -
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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/ -
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CodeShip
CloudBees
$49 per monthDo you want everything to be set up instantly or do you prefer to control your environment and your workflow? CodeShip allows developers to choose the path that is best for them. This will maximize productivity and allow teams to evolve over time. CodeShip allows you to integrate with any tool, cloud, or service you need to create the perfect workflow for your company. We make CodeShip simple to use and provide quick and thorough support for developers. CodeShip will help you get technical support quickly if you have a problem or need assistance. CodeShip's easy-to-use UI and turnkey environment make it easy to get your deployments and builds up and running in no time. As your projects grow, you can develop into more complex workflows and config as-code. -
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Sahi Pro
Tyto Software Pvt Ltd
Sahi Pro is a suite automation tools for web, Web-services, Windows desktop and Java applications. Sahi Pro features include automatic waits, recorders and accessor spy, inbuilt frame and editor, parallel playback, automatic reporting, automatic logging, and reporting. Also, Sahi Pro can save 70% of the time and effort that is normally spent on test automation. Sahi Pro has been trusted by more than 400 companies around the world and is quickly becoming the preferred tool for test automation in the agile world. -
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SonarCloud
SonarSource
€10 per monthSonarCloud 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! -
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Appvance
Appvance.ai
Appvance IQ (AIQ), delivers transformative productivity gains and lower costs for both test creation and execution. It offers both AI-driven (fully automated tests) and 3rd-generation codeless scripting for test creation. These scripts are then executed using data-driven functional and performance, app-pen, and API testing -- both for web and mobile apps. AIQ's self healing technology allows you to cover all code with only 10% of the effort required by traditional testing systems. AIQ detects important bugs automatically and with minimal effort. No programming, scripting, logs, or recording are required. AIQ can be easily integrated with your existing DevOps tools, processes, and tools. -
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DeepSource
DeepSource
$12 per user per monthDeepSource allows you to automatically identify and fix bugs in your code during code reviews. This includes security flaws, anti-patterns and bug risks. It takes less that 5 minutes to create your Bitbucket or GitLab account. It works with Python, Go, Ruby and JavaScript. -
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Typemock
Typemock
$479 per license per yearThis is the easiest way to unit-test. You can write tests without having to modify your code. Even legacy code. Methods, private methods, nonvirtual methods and out parameters, as well as members and fields. Developers around the globe can use our professional edition for no cost. You can also purchase a paid support package. You can improve your code integrity and produce quality code. You can create entire object models by using one statement. Mock statics, private constructors and events. Our suggestion feature generates test suggestions that are suitable for your code. Our smart runner will run your impact tests and give you instant feedback. While you code, our coverage feature displays your code coverage. -
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CodeRush
DevExpress
$49.99 one time paymentYou can instantly try your first CodeRush feature and discover how powerful it is. Refactoring for C# and Visual Basic. The fastest test.NET runner, next-generation debugging and the most efficient coding experience. You can quickly find symbols and files within your solution and navigate to code constructions relevant to the current context. CodeRush also includes Quick Navigation and Quick File Navigation, which make it quick and easy to locate symbols and open files. Analyze Code Coverage allows you to see which parts of your solution are covered and pinpoint the risky parts. The Code Coverage window displays the percentage of statements that have been covered by unit testing for each namespace, type and member of your solution. -
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froglogic Coco
froglogic
€124.17 per monthCoco®, a tool for multi-language code coverage, is available. Automated source code instrumentation can be used to measure test coverage for statements, branches, and conditions. When a test suite is run against an instrumented application, data can be collected that can be later analyzed. This analysis can be used for understanding how much of the source code was touched by tests, which additional test suites need to be written, and how the test coverage has changed over time. Identify dead or untested code, redundant tests, and untested code. Identify the impact of a patch and code coverage. Coco supports branch coverage, statement coverage, MC/DC, and other levels. Linux, Windows, RTOS, and other platforms. GCC, Visual Studio and embedded compilers are all available. You can choose from text, HTML, XML and Cobertura report formats. Coco can also integrate with other build, test, and CI frameworks such as JUnit Jenkins, SonarQube, and SonarQube. -
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PHPUnit
PHPUnit
FreePHPUnit needs the dom, json extensions. These extensions are usually enabled by default. PHPUnit also needs the reflection, pcre and spl extensions. These extensions are default enabled and cannot be disabled without patching PHP’s build system or C sources. To use the code coverage report feature, you will need to have the Xdebug (2.7.0 and later) and tokenizer extensions. The xmlwriter extension is required to generate XML reports. Unit tests are intended to be a good practice for developers to identify and fix bugs, refactor code, and serve as documentation for the unit of software being tested. Unit tests should cover all possible paths within a program to reap these benefits. A unit test typically covers one path within a function or method. A test method is not always an independent, encapsulated entity. There are often implicit dependencies between test method, which are hidden in the test's implementation scenario. -
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Devel::Cover
metacpan
FreeThis module provides Perl code coverage metrics. This module provides code coverage metrics for Perl. They show how thoroughly tests use code. Devel::Cover allows you to identify areas of code that are not being used by your tests. You can also determine which tests to add to increase coverage. Code coverage can be considered an indirect indicator of quality. Devel::Cover has many of the features you would expect in a useful coverage tool. Reports include information on the coverage of statements, branches, conditions, subroutines, and pods. Subroutine and statement coverage data should be accurate. Although not always as accurate as one might expect, branch and condition coverage data should be generally accurate. Pod coverage is derived from Pod::Coverage. If Pod::Coverage::CountParents is available it will be used instead. -
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LuaCov
LuaCov
FreeLuaCov is a coverage analyzer that Lua scripts can use. A Lua script that has the luacov module loaded is executed. It generates a stats report with the number of executions for each line and the loaded modules. This file is processed by the luacov command-line script, which generates a report file that allows one to see which code paths were not followed. This file can be used to verify the effectiveness of a test set. LuaCov includes several configuration options, which have their defaults stored in src/luacov/defaults.lua. These are the global defaults. To use project-specific configuration, create a Luascript setting options as globals and returning a table with some options. Then store it as.luacov within the project directory where luacov is running. This config tells LuaCov, for example, that foo module and submodules must be covered. They are located in the src directory. -
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grcov
grcov
Freegrcov aggregates code coverage information from multiple source files. grcov processes.profraw files and.gcda file which can be generated using llvm/clang/gcc. grcov can also process lcov files (for JS cover) and JaCoCo (for Java coverage). Supported operating systems include Windows, macOS, and Linux.
Overview of Code Coverage Tools
Code coverage tools areprograms that measure the amount of code in a given program that is actually executed when you run it. It measures how much of your code is tested, or has been exercised at least once during its lifetime. Code coverage tools allow developers and testers to quickly identify areas of un-tested code which can help inform development decisions about what tests need to be written, as well as where optimization opportunities exist.
Using code coverage tools helps ensure quality and robustness of the applications being created by identifying gaps in test cases. These gaps can be addressed with additional unit tests, integration tests, or manual testing methods. By discovering untested lines of code early on, bugs and other issues can be prevented from reaching production environments. This emphasis on maintaining a high level of quality also boosts customer confidence in the application that they are using and encourages ongoing product improvement.
When running a code coverage report, most tools will generate a detailed report showing which lines in the source code have been covered (or tested) and which ones have not been touched by any test case yet. The report may also provide an indication of what percentage of total lines were actually tested against the total number available for testing; this is referred to as Coverage Percentage or Test Coverage Rate.
Most modern IDE’s (Integrated Development Environments) offer some form of built-in support for code coverage analysis allowing for execution times to be monitored efficiently within the development environment itself rather than having to resort to external scripts each time changes are made to the software under review or test cases need verification. Examples include Xcode's Instruments tool from Apple Inc., Visual Studio's Code Coverage Tool from Microsoft Corporation and Apache Ant's Cobertura Software Project among others; all providing easy-to-use GUI interfaces tailored largely to their respective user base needs while still offering more advanced capabilities like customizing filters and output reports based on specific user preferences.
What Are Some Reasons To Use Code Coverage Tools?
- Ensuring Complete and Thorough Testing: Code coverage tools measure the degree to which code is tested. By setting a certain threshold for code coverage, administrators can ensure that all components of their code base are thoroughly tested before production.
- Enhancing Quality Assurance Processes: Code coverage tools help to identify areas where tests need improvement or additional tests should be written. This helps ensure the quality of the final product, as bugs and issues can be identified quickly during testing.
- Measuring Test Effectiveness: Code coverage tools provide an objective measure of how effective tests are in finding bugs and eliminating defects from application code.
- Determining Improvement/Decline: These tools also allow developers to track their test performance over time by measuring code coverage at different points in the development cycle, making it easier to spot any decline or potential improvements that need to be made going forward.
- Accelerating Development Cycles: With detailed analysis provided by these tools, developers can spend less time troubleshooting problems and more time implementing new features or improving existing ones on their projects - thereby accelerating development cycles significantly.
Why Are Code Coverage Tools Important?
Code coverage tools are an essential part of software development. They alert developers to areas of code that are not adequately tested, allowing them to focus their efforts on optimizing their application’s functionality. By providing clear reports and analysis, these tools streamline the coding process and increase efficiency.
Using code coverage tools helps developers identify which lines of code were executed during testing and what lines were skipped or not activated at all. This is especially useful for debugging, as it gives developers a better picture of how specific sections of code have been handled by the system—what did work? What didn't? With this information in hand, developers can fine-tune their code to ensure the best possible results from testing.
Another way that code coverage tools come in handy is through automated integration with bug tracking systems. When bugs arise during testing, the tool can quickly pinpoint exactly where they occurred in the source code, so that appropriate measures can be taken immediately. This ensures faster resolution time for any issues encountered during testing and streamlined corrective action for future releases.
Finally, some modern code coverage products offer additional features such as unit tests guidance and support for multiple languages and frameworks. Such features help developers stay on top of newly emerging technologies while simultaneously ensuring uniform performance across different operating systems and web servers—saving valuable development time in the long run.
All in all, using a quality coverage tool means enhanced productivity throughout your software development project cycle—from debugging to test runs to bug fixing—and improved overall application performance over time.
Code Coverage Tools Features
- Source Code Navigation: Code coverage tools offer developers the ability to navigate through source code, allowing them to quickly find specific components and files. This is typically done by using a graphical user interface (GUI) which provides users with an organized view of the source code.
- Test Case Creation: Code coverage tools can be used to help create test cases that are tailored for the application under testing. The tool will analyze the source code, identify possible input values and generate appropriate test cases that can be then used in the testing process.
- Data Flow Analysis: These tools are capable of analyzing data flows through an application, providing developers with insight into which components are being used or not used during program execution. This feature also makes it easier to pinpoint errors and bugs related to variable manipulation within a program, as well as any potential race conditions in multithreaded programs that could produce unexpected results during runtime execution.
- Coverage Reports: Coverage reports provide information about how thoroughly tested a program has been by showing which parts of its source code have been exercised and which ones have not yet been reached by tests at run time. This allows developers to focus on areas that need more thorough testing before releasing their product into production environments or onto marketplaces for customers to use.
- Path Analysis: Path analysis is a process where testers measure how many different paths are being taken while system tests execute and ensure they all follow desired outcomes as expected within an application's requirements specification document (RSD). By examining every single path taken, testers can gain insights into any areas where flaws may exist and address those if necessary before signing off on entire projects or features within applications or software systems they're working on.
Types of Users That Can Benefit From Code Coverage Tools
- Developers: Code coverage tools help developers get valuable insights into the code they are writing. This includes identifying potential issues, tracking progress and seeing which parts of the code have been tested.
- Quality Assurance Professionals: Code coverage tools can be used to identify areas of code that may need more testing or additional bugs that could be causing problems in production applications.
- Project Managers: Code coverage tools provide managers with an overview of how much and what kind of testing is being done on each part of a project, helping them to better understand their team's progress and whether any areas need further development.
- Business Leaders: By understanding how well teams are covering their code in tests, business leaders can gain insights into how efficiently projects are moving forward and where there may be risk factors or areas for improvement.
- Security Teams: Security teams use code coverage tools to scan codebases for vulnerabilities and to make sure security protocols are being followed correctly by developers.
How Much Do Code Coverage Tools Cost?
The cost of code coverage tools can vary depending on the specific tool being used and the features you need. Generally, there are a range of options available, ranging from free to enterprise-level pricing.
For basic code coverage needs, open-source tools such as Cobertura or gcov are available for free. These tools run analyses on your codebase and output results that may still require manual interpretation in order to draw insights about program quality. They also generally lack dynamic traceability of code changes and other advanced metrics but are sufficient for basic analysis purposes.
At the higher end of the spectrum, commercial products such as Parasoft’s Jtest or Veracode offer more comprehensive analysis capabilities from both a static and a dynamic perspective. These packages generally provide enhanced reporting capabilities with detailed dashboards that allow users to monitor various aspects of their applications in real time. The advance analytics often come at a price though – high-end solutions can range between $20K up to several hundred thousand dollars per license depending on features needed and size of the deployment team.
Code Coverage Tools Risks
- False positives: Code coverage tools can give inaccurate results, resulting in the wrong code being tested or untested code being neglected.
- False negatives: Similarly, code coverage tools may not pick up certain nuances that may be hidden in the execution of a program and fail to indicate any issue with it.
- Performance issues: As more tests are run for better coverage, the time taken to complete them increases which affects the overall performance of the system.
- Over-reliance: Code coverage tools should only be used as an aid while testing but they can lead testers to become over-reliant on them and overlook other important aspects of software development such as security and usability.
- Costly investments: Implementing these tools may require significant costs due to their sophistication and maintenance requirements, as well as training teams on how to use them correctly.
What Software Can Integrate with Code Coverage Tools?
Software that is written in a programming language can integrate with code coverage tools. This includes application software, system software, and libraries. These types of software are able to provide metrics on the number of lines and functions that have been executed. The data gathered by code coverage tools can then be used as feedback to improve the quality and maintainability of the codebase. In addition, many Integrated Development Environments (IDEs) offer plugins for code coverage tools which make it easier for developers to monitor their projects during the development and testing phases.
What Are Some Questions To Ask When Considering Code Coverage Tools?
- What environments does the code coverage tool support? Is it platform-agnostic, or do you need to be running a certain operating system and/or programming language?
- Does the tool have built-in integration with various testing frameworks, such as JUnit or Mocha?
- How configurable is the tool in terms of what data it collects and reports on (line coverage, branch coverage, etc.)?
- Is there an interface that allows you to easily review data collected by the tool? Can you drill down into specific code files to get a more granular look at how your tests are covering that code?
- What kinds of output formats are available for sharing results (e.g., HTML reports)?
- How easy is it to set up new projects in the tool—does the setup have any dependencies that might cause issues on certain machines or platforms?
- If necessary, can you customize existing rules or create custom rules for collecting metrics from your codebase?
- Does the tool offer helpful guidance on writing effective unit tests and assessing overall test quality (e.g., identifying untested elements of your codebase)?