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Test Coverage Measurement and its Benefits

Navdeep Singh Gill | 25 March 2022

What is Test Coverage?

While delivering a software/Product, measures toward quality of testing cycle followed by the teams in the complete procedure of Test Coverage. It is possibly said the procedure implemented in the software testing to check the covered areas in testing. As the name depicts, it is the combination of manual and automated tests to highlight the percentage of software covered by tests.

Why follow this test coverage procedure in the delivery of software?

We use test coverage in the software delivery to improve testing and code development. If software for strict delivery has a lot of modules to test, then this methodology makes sure that everything in the deliverables is tested thoroughly. It is mainly included in the testing phase of software development.

The testing activity also takes an eye on the test coverage of the software. “Coverage is the extent to which a structure has been exercised as a percentage of the covered items. If coverage is not 100%, then more tests may be designed to test those items that were missed and therefore, increase coverage” as test coverage manages the performance monitoring of testing quality level and also provides guidance to the test engineers in creating test journeys that cover areas that are not yet covered.

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What are the ways to use coverage findings?

  • Coverage findings are finding loopholes in the testing, i.e. areas not covered.
  • Test coverage is used in Regression testing to recheck the performance and changes in previously developed code.
  • Setting the priority of test cases
  • Augment & minimize test suites

Why Test coverage and Measurement is important?

  • To make product development similar by removing bugs, errors, and ambiguity early in the development life cycle.
  • To find the hidden/uncovered areas and requirements.
  • Simpler testing cycle to find and prevent defect leakages.
  • Impact on better return of investments by getting less number of user acceptance bugs and the resources used to resolve the user acceptance bugs will work as an asset.

What are the best practices for Test Coverage?

To find the test coverage in the percentage you must be aware of, it is very difficult to cover all the functionalities until you test all the functions/methods of the software code. Test coverage consists of different methodologies from which below mentioned levels are always the same.

  • Requirements Coverage
  • Code Coverage

The first and foremost task while checking the test coverage, we go with checking the requirements coverage with their atomic behaviour to cover them easily. By doing Requirement coverage, whether the test cases cover all requirements or we need to create more test cases and make changes to the already created ones. The below-mentioned equation can calculate requirement coverage-

Test Coverage = Line of code tested / total number of line of Codes X 100

The second task is to check the Code Coverage, which is done by checking the lines of code included in a test cases execution to check whether the full code of the software application is involved in test coverage. Test Coverage testing is white box testing based on System, integration, and unit testing.

A type of testing in which individual units or functions of software testing. Click to explore about, Unit Testing Techniques and Best Practices

How to improve ongoing testing with Test Coverage?

As seen in most product development processes, the root cause of the defects/errors is mainly based on the requirements and less/incomplete test coverage of the products.

  • Check the functional process documents

Functional process documentation consists of different phases with knowledge sharing, review, and approval of the knowledge and understanding through prepared documents. To make a good improvement in the Test Coverage.

  • Test Coverage must be 100% by covering all areas of the product.
Full test coverage creates different dimensions to cover, which are as follows.

- Requirements validation and verification

- Data used in test coverage

- Possible User scenarios

- Compliance check

  • Testing can also be holding some risk to make improvements in the product. Testing with risk is used to check the boundary value analysis and many like it through which the areas are collected having most likely to be defective.

Improving Test Coverage with Automation

Less automation code coverage affects the quality of the products/software and puts an extra burden on testers to manually test the product.

  • To reach Strict deadlines, automation is mostly sidelined and becomes a low-priority task, and manual becomes normal. Manual Testing at strict delivery makes it very difficult to deliver the project on time.
  • Suppose a project is initially developed with less test coverage or unit tests, and you are the one working with the TDD approach. In that case, it becomes important to create test scripts for new ones with handling the already automated ones.
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Improving Test Coverage without Automation

We work with a manual testing approach to test the software/projects with every sprint, and it should move to “Automate” before moving it to do. Creating a separate structure or requirement that shows what is “to be automated” should be important. With Automation, we can improve in -

  • Improvement of delay created in software delivery because of regression testing at strict product production release.
  • It is very useful to go with automation tools to maintain a cover test coverage over different browsers and devices.

What are the frameworks for Test Coverage?

The frameworks for Test Coverage are described below:

  • jFeature - It is an open-source Specification and requirement coverage tool that focuses on requirements covered during code development.
  • Cobertura- It is an Open source tool with language support of java to calculate the percentage of code covered by tests.
  • Jester - This tool is based on java and JUnit tests.
  • Gretel - It is a java based open-source tool used to monitor the test coverage. Currently is used only for statement coverage, and by the side of monitoring test coverage, Gretel also removes the instrumentation for already executed code.
  • Bullseye Coverage - This open-source tool with C and C++ language support to check code coverage and highlight the percentage of code tested. Bullseye Coverage also highlights the areas which need significant attention for review.
  • NCover- It is a tool used for .NET Based platforms/Applications as an open-source application. NCover holds up the functionality of calculating the count of times a line of code is executed in a single application run. Because of such a feature, it holds up the coverage of methods and classes.

After exploring all the above tools, below is the difference between the requirement coverage of the above-mentioned tools. Based on the comparison, it is clear that JFeature is the tool that provides the maximum and same features as NCover, but the difference of the language supported and JFeature, not NCover, does the coverage of requirements.

Java vs Kotlin
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What is the impact of Test coverage and Measurement?

While expecting a software delivery, every customer hopes for smooth and bug-free software. The developing teams need to work on the goal of developing a stable and fully functional product delivered to the client. For customer satisfaction, we discuss the above Test Coverage and its measurement, and a few points are clear to be improved -

  • Make better and more use of code coverage by considering unit testing.
    Enhancing Test automation will lead to better test coverage.
  • By improving in the above two points, there will be an improvement in the product delivery timelines management and the stability of the product.


In the final analysis, we will conclude that the Measurement of the testing we perform on software before delivery is very important. By this, we will ensure how much area of the software was tested thoroughly and monitor the level of testing quality. Test Coverage defines What we're testing and how much we have done with testing, so for improving the code development and testing, we will measure the coverage of testing.