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Code Coverage Testing in Software Testing

Last Updated : 23 Jul, 2025

Every Software Developer follows the Software Development Life Cycle (SDLC) for the development of any software application. Testing is one of the important phases that is performed to check whether the developed software application is fulfilling the requirements or not.

Different types of software testing are there which are performed based on various metrics/testing parameters.

Code Coverage is a metric used in Software Testing that quantifies the extent to which the source code of a program is tested. It measures the percentage of code executed by the test suite, helping developers identify untested parts of an application.

As we know at last of the development each client wants a quality software product as well and the developer team is also responsible for delivering a quality software product to the customer/client. Where this quality refers to the product’s performance, functionalities, behavior, correctness, reliability, effectiveness, security, and maintainability. Where Code Coverage metric helps in determining the performance and quality aspects of any software. The formula to calculate code coverage is

Code Coverage = (Number of lines of code executed)/(Total Number of lines of code in a system component) * 100

To perform code coverage analysis various criteria are taken into consideration. These are the major methods/criteria which are considered.

The number of statements that have been successfully executed in the program source code.

Statement Coverage = (Number of statements executed)/(Total Number of statements)*100.

The number of decision control structures that have been successfully executed in the program source code.

Decision Coverage = (Number of decision/branch outcomes exercised)/(Total number of decision outcomes in the source code)*100.

The number of functions that are called and executed at least once in the source code.

Function Coverage = (Number of functions called)/(Total number of function)*100.

The number of Boolean condition/expression statements executed in the conditional statement.

Condition Coverage =(Number of executed operands)/(Total Number of Operands)*100.

Understanding the different types of code coverage helps in ensuring comprehensive testing of your software. Here are the main types:

• Definition: Measures whether each line of code is executed.
• Purpose: Ensures that all code statements are tested at least once.
• Example: If a function has ten lines of code, statement coverage ensures each line is executed during testing.

• Definition: Measures whether each possible branch (true/false) from each decision point is executed.
• Purpose: Ensures that all branches of control structures (like if-else statements) are tested.
• Example: If a program has an if-else statement, both the if and the else branches should be tested.

• Definition: Measures whether each function or subroutine in the code is called.
• Purpose: Ensures that all functions in the code are invoked during testing.
• Example: In a class with multiple methods, function coverage ensures each method is called at least once.

• Definition: Measures whether each Boolean sub-expression is evaluated to both true and false.
• Purpose: Ensures that each condition in a decision has been tested for both true and false outcomes.
• Example: In a compound condition like if (A && B), both A and B should be tested for true and false values.

• Definition: Measures whether all possible paths through the code are executed.
• Purpose: Ensures that all possible execution paths are tested.
• Example: For a function with multiple nested loops and conditionals, path coverage would ensure all possible execution routes are tested.

• Definition: Measures the number of executed lines divided by the total number of lines.
• Purpose: Provides a straightforward metric of how much of the codebase is executed.
• Example: If a file has 100 lines and 80 lines are executed during testing, line coverage would be 80%.

• Definition: Measures whether loops are executed and how many times.
• Purpose: Ensures that loops are tested with zero, one, and multiple iterations.
• Example: For a loop that processes items in a list, loop coverage ensures the loop is tested with an empty list, a single-item list, and a multiple-item list.

Each type of code coverage focuses on different aspects of the code, helping to ensure thorough testing and improving overall software quality.

Below are a few important code coverage tools

• JaCoCo
• Cobertura
• Emma
• Clover
• Codecov
• Coveralls
• Istanbul
• SonarQube
• NCover
• BullseyeCoverage
• Visual Studio Code Coverage
• dotCover
• OpenCover
• gcov
• Testwell CTC++

• It helps in determining the performance and quality aspects of any software.
• It helps in evaluating quantitative measures of code coverage.
• It helps in the easy maintenance of the code base.
• It helps in accessing the quality of the test suite and analyzing how comprehensively a software is verified.
• It helps in the exposure of bad, dead, and unused code.
• It helps in creating extra test cases to increase coverage.
• It helps in developing the software product faster by increasing its productivity and efficiency.
• It helps in measuring the efficiency of test implementation.
• It helps in finding new test cases that are uncovered.

• Sometimes it fails to cover code completely and correctly.
• It can not guarantee that all possible values of a feature are tested with the help of code coverage.
• It fails to ensure how perfectly the code has been covered.
• For some test files, additional mock data is required to execute the test cases.
• Sometimes it is difficult to cover the test cases handling functions.
• Lot of test cases are required to increase the test coverages for complex code.
• A developer must have strong knowledge of writing unit test cases to cover all possible scenarios in the developed code.

Code coverage is a crucial metric in software testing, providing insights into the extent to which the source code is tested. It helps developers identify untested parts of an application, ensuring the performance, functionality, and reliability of the software. Various types of code coverage, including statement, branch, function, condition, path, line, and loop coverage, offer comprehensive testing approaches to enhance software quality. By using code coverage tools like JaCoCo, Cobertura, and SonarQube, teams can efficiently maintain their code base, improve test suite quality, and ensure thorough verification of the software.

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