Code coverage is an important measure that quantifies the degree to which the source code of the program has been tested. There is a plethora of Code Coverage Tools in the market and selecting one for your project could be a challenge.

Following is a curated list of Top 13 handpicked Code Coverage tools with popular features and latest download links

1) Coco

Coco-platform is a multi-language code coverage tool. Automatic source code instrumentation helps you to measure test coverage of statements, branches, and conditions.

Features:

• Coco allows you to perform statement coverage, branch coverage, MC/DC and other levels
• Coco supports C, C++, C#, Tcl, and QML
• Helps you to merge multiple execution reports to provide advanced analysis

There is a plethora of Code Coverage Tools in the market. Parasoft Jtest offers integrated Java development testing for the enterprise. Mercedes benz star calculator.

2) Parasoft Jtest

Parasoft Jtest offers integrated Java development testing for the enterprise. The tool allows you to accelerate Java software development by providing a set of tools for keeping your software reliable and secure. This helps you to improve the quality of your software and minimize business risks.

Features:

• Prevent reliability and security issues from entering production
• Unit testing for active development
• Helps you to understand where to focus your testing activities
• Get visibility into your Java quality with immediate feedback

3) Cobertura

Cobertura is a popular open source code coverage tool. It allows you to execute tasks via Maven and Ant, or the Cobertura CLI. You can embed with other multiple QA tools.

Features:

• Allows you to measure coverage without having the source code
• Helps you to find which parts of your Java program are lacking test coverage
• Allows you to represent reports in HTML and XML format
• Helps you to test lines and branches of the class & method

Download link: https://cobertura.github.io/cobertura/

4) Coverage.py

Coverage.py is another useful code coverage tool. It helps you to monitor Python programs, notes which are parts of the code have been executed.

Features:

• Coverage.py helps you to specify what source files you want it to analyze via the configuration file
• It also helps you to analyze the source to find out code that which could have been executed but was not.

Download link:https://coverage.readthedocs.io/

5) JaCoCo

JaCoCo is a free Java code coverage tool distributed under the Eclipse Public License. It is an open source free code coverage tools for Java, which has been made by the EclEmma.

Features:

• JaCoCo offers instructions, line and branch coverage
• It supports Java 7 and Java 8
• Helps you to test lines and branches of the class & method
• Offers easy to navigate HTML or XML report

Download link: http://www.eclemma.org/jacoco/

6) OpenClover

OpenClover tool helps you to measures code coverage for Java and Groovy and collects over 20 code metrics. It helps you to display untested areas of your application. It helps you to combines coverage and metrics to find the riskiest code.

Features:

• Helps you to runs your test faster
• Allows you to focus what's necessary for your test
• Both branch and statement coverage support
• Allows you to generate XML-based report that, combined with ReportGenerator, produces TML-based report on coverage
• Helps you to keep the balance between application and tests

Download link: http://openclover.org/

7) Bullseye Coverage

BullseyeCoverage is a code coverage software for C++ and C that tells you how much of your source code was tested. This tool allows you to perform unit testing, integration testing, and final release.

Features:

• Provide better coverage measurement
• Helps you to create more reliable code and save time
• Allows you to Include or exclude any portion of the project code
• Merge results from distributed testing

Download link:http://www.bullseye.com/

8) NCover

NCover is an advanced level code coverage tool for.Net programs and applications. It provides support for statement coverage and branch coverage. This code coverage tool is available on open source and as well as on commercial license.

Download trim enabler pro. Features:

• .NET code coverage according to your customized needs
• Helps you to test, track and manage a unified coverage number across entire teams
• Detailed and centralized data about coverage
• Extensive documentation and user support
• This tool helps you to perform manual and coverage tests
• Deliver products to market faster and confidently in agile environments

Download link: http://www.ncover.com/

9) Vector Software

VectorCAST allows you to implement consistent processes for managing test activities and reporting key quality metrics. This software testing tool offers a cost-effective approach to unit testing, regression management, and code coverage analysis.

Features:

• Easy Test Collaboration
• System Test Automation
• Quality trend & change Impact Analysis
• Allows parallel Testing
• Web-based Quality Dashboard

Download link:https://www.vectorcast.com/software-testing-products/vectorcast-analytics-web-based-metrics-quality-and-testing

10) Devel:Cover

Devel cover offers code coverage metrics for Perl. With the help of this code cover tool, you can discover areas of code not exercised by your tests. It helps you to tests to create to increase coverage.

Features:

• Offers some reports which include various types of HTML output, textual reports
• Statement, branch, condition, subroutine, and pod coverage information is reported

Download link:http://search.cpan.org/~pjcj/Devel-Cover-1.23/lib/Devel/Cover.pm

11) dotCover

dotCover offers by JetBrains is a .NET unit test runner and code coverage tool. It allows you to integrate with Jet brains rider with Visual Studio. You can also calculate reports statement-level code coverage in applications for .NET, Silverlight or .NET Core.

Features:

• Allows you to visualize code coverage according to your business needs
• Provides a console utility for use with a Continuous Integration server
• Helps you to customize your coverage analysis with a coverage filter
• Allows you to use a shortcut to finds out which unit tests cover a particular statement

Download link: https://www.jetbrains.com/dotcover/

12) Visual Studio

Code coverage feature of Visual Studio helps you to determine what part of your project's code is tested by coded tests like unit tests. The tool allows you to view the previous set of results.

Features:

• Helps you to view a previous set of results
• Make results readable as text, select export code coverage results
• Allows you to merge results of several runs
• Allows you to export Code Coverage Results to save the results of a merge operation

Download link:https://msdn.microsoft.com/en-IN/library/dd537628.aspx

13) Istanbul

Istanbul is a code coverage tool used for Javascript. It support of ES6/ES2015+ using babel-plugin. The tool offers all javascript instrumentation library which helps you to tracks statement, branch, and function coverage.

Features:

• Collection of reporters offers both terminal and HTML output
• Support for the most popular JavaScript testing frameworks
• Support for instrumenting subprocesses, using the NYC command-line-interface

Download link:https://istanbul.js.org/

What is Test Coverage?

Test coverage is defined as a metric in Software Testing that measures the amount of testing performed by a set of test. It will include gathering information about which parts of a program are executed when running the test suite to determine which branches of conditional statements have been taken.

In simple terms, it is a technique to ensure that your tests are testing your code or how much of your code you exercised by running the test.

In this tutorial, you will learn

What Test Coverage does?

• Finding the area of a requirement not implemented by a set of test cases
• Helps to create additional test cases to increase coverage
• Identifying a quantitative measure of test coverage, which is an indirect method for quality check
• Identifying meaningless test cases that do not increase coverage

How Test Coverage can be accomplished?

• Test coverage can be done by exercising the static review techniques like peer reviews, inspections, and walkthrough
• By transforming the ad-hoc defects into executable test cases
• At code level or unit test level, test coverage can be achieved by availing the automated code coverage or unit test coverage tools
• Functional test coverage can be done with the help of proper test management tools

Benefits of Test Coverage

• It can assure the quality of the test
• It can help identify what portions of the code were actually touched for the release or fix
• It can help to determine the paths in your application that were not tested
• Prevent Defect leakage
• Time, scope and cost can be kept under control
• Defect prevention at an early stage of the project lifecycle
• It can determine all the decision points and paths used in the application, which allows you to increase test coverage
• Gaps in requirements, test cases and defects at the unit level and code level can be found in an easy way

What Are Main Differences Between Code Coverage And Test Coverage?

Code coverage and test coverage are measurement techniques which allow you to assess the quality of your application code.

Here, are some critical differences between booths of these coverage methods:

Parameters	Code Coverage	Test Coverage
Definition	Code coverage term used when application code is exercised when an application is running.	Test coverage means overall test-plan.
Goal	Code coverage metrics can help the team monitor their automated tests.	Test coverage is given details about the level to which the written coding of an application has been tested.
Subtypes	Code coverage divided with subtypes like statement coverage, condition coverage, Branch coverage, Toogle coverage, FSM coverage.	No subtype of Test coverage method.

Formula to calculate Test Coverage

To calculate test coverage, you need to follow the below-given steps:

Step 1) The total lines of code in the piece of software quality you are testing

Step 2) The number of lines of code all test cases currently execute

Now, you need to find (X divided by Y) multiplied by 100. The result of this calculation is your test coverage %.

For example:

If the number of lines of code in a system component is 500 and the number of lines executed across all existing test cases is 50, then your test coverage is:

Examples of Test Coverage

Example 1:

For example, if 'knife' is an Item that you want to test. Then you need to focus on checking if it cuts the vegetables or fruits accurately or not. However, there are other aspects to look for like the user should able to handle it comfortably.

Example 2:

For example, if you want to check the notepad application. Then checking it's essential features is a must thing. However, you need to cover other aspects as notepad application responds expectedly while using other applications, the user understands the use of the application, not crash when the user tries to do something unusual, etc.

Drawbacks:

• Most of the tasks in the test coverage manual as there are no tools to automate. Therefore, it takes lots of effort to analyze the requirements and create test cases.
• Test coverage allows you to count features and then measure against several tests. However, there is always space for judgment errors.