While testing software, you’ll often encounter the question; what can be done to improve test coverage? This task can be challenging, as the software evolves. New features might be added to the codebase, or existing code may change. Before discussing tips for improving test coverage, let’s first explore why striving for better coverage is valuable. Why test coverage is crucial In software testing, we try our best to ensure that the software is reliable, meets the requirements, and is of the maximum quality. Imagine your team released a project on production with an undetected bug, What would happen? it would affect the user’s experience and could cause user drop. In addition, fixing a bug after release is a headache for the team. Moreover, it could cause the system to undergo downtime and impose charges on the company. If we find the bug and fix it before the production release, we will roll out the feature more effectively. That is why we want to ensure the software is well-tested, leaving no stone unturned. Although releasing 100% bug-free software seems impossible, it’s our job to edge closer to 100%. Tips to enhance test coverage in software QA I have used some tips to improve the test coverage of the software that I am sharing with you: 1- Define what you want to achieve and how you will measure your success. For example, define devices or platforms you are going to run your tests on or test your software under different situations. 2- Design test cases based on requirements and risks. Requirements-based testing ensures that your tests cover the features and functions that the software should provide. Risk-based testing ensures that your tests cover the areas and scenarios that are most likely to cause failures or problems. 3- Use multiple types of tests such as E2E,  compatibility, sanity, and so on. 4- Review and update test cases regularly. This will help you to go through your test cases and update them based on the changes to the software. You can do this step on a scheduled basis or on demand. 5- Improve code coverage by leveraging unit tests. It is suggested to mix unit tests with other types of tests such as integration tests,. Let’s discuss these in more detail. Designing test cases You can use business documents, user stories, and product documents to find out what functionalities your software should have. As a result, you can write test cases based on all requirements. Try to see the software from the end user's perspective to know how the user interacts with the software and how they move through it. In addition, you should consider edge cases and boundaries. Apply technical documents and swagger files to keep track of risks and failure areas. For example, in a sign-in page like below: Suppose that when the user taps on the username, the keyboard opens with digits only. This means the user can enter only numbers in the username field. But, if the user enters strings, what happens? How will the server handle it? Does a string crash the server? This is an example of a risk/failure point. It should be considered in the swagger file how the server should respond when an invalid or undefined input arrives. As a result, by using swagger files you can detect the possible failure bugs. The flows of the software and the interactions between the server and databases are usually put in technical documents. By using technical documents, you can discover the flaws and risk points too. Using Multiple Tests There are numerous types of tests in the software QA, but I won’t explore all of them here—I’ll save that for a dedicated article on HackerNoon. Each testing type serves a unique purpose, targeting specific aspects of the software to ensure quality and reliability. For example, focusing solely on performance tests might leave other critical areas, like compatibility across different platforms or devices, unexamined. To truly cover all angles of your application, it’s essential to incorporate as many testing types as possible. Improving code coverage Code coverage is a metric that measures how much of your source code is tested. The question is - how can you measure your code coverage? The answer is simple; by leveraging code coverage tools. You may ask how a tool calculates the coverage. Well, some criteria will be used by the tool to determine what parts of your code were not run in your test suite. There are some common metrics such as function, statement, branches, condition, and line. The tool will go through the code and discover all available metrics in the code. The formula is simple; the percentage of code coverage = (the tested metrics/all metrics in code) * 100. The table below presents some popular code coverage tools based on the programming languages: Programming Language

Code Coverage Tool/Tools



Java

Jacoco, OpenClover, JCov, Cobertura



JavaScript

Istanbul, Blanket, jscoverage



Ruby

SimpleCov, undercover, DeepCover



Python

Coverage.py, pytest-cov



Golang

test-cover command (built-in)



PHP

PHPUnit



Kotlin

Cobertura, JaCoCo



C#

Coverlet, NCover, dotCover



C++

Parasoft Jtest, Coco code coverage, Testwell CTC++ Conclusion To sum up, is it challenging to reach 100% test coverage in the software QA area. The key is that besides using some tips to provide better action, we should monitor the behavior of the application and have an eye on the production to recognize the possible issues that our users raise. In this way, we can find out the missing scenarios and add the related tests to our systems. References https://about.codecov.io/blog/the-best-code-coverage-tools-by-programming-language/ https://www.atlassian.com/continuous-delivery/software-testing/code-coverage Image header: by vectorjuice on freepik While testing software, you’ll often encounter the question; what can be done to improve test coverage? This task can be challenging, as the software evolves. New features might be added to the codebase, or existing code may change. Before discussing tips for improving test coverage, let’s first explore why striving for better coverage is valuable. Why test coverage is crucial In software testing, we try our best to ensure that the software is reliable, meets the requirements, and is of the maximum quality. Imagine your team released a project on production with an undetected bug, What would happen? it would affect the user’s experience and could cause user drop. In addition, fixing a bug after release is a headache for the team. Moreover, it could cause the system to undergo downtime and impose charges on the company. If we find the bug and fix it before the production release, we will roll out the feature more effectively. That is why we want to ensure the software is well-tested, leaving no stone unturned. Although releasing 100% bug-free software seems impossible, it’s our job to edge closer to 100%. Tips to enhance test coverage in software QA I have used some tips to improve the test coverage of the software that I am sharing with you: I have used some tips to improve the test coverage of the software that I am sharing with you: 1- Define what you want to achieve and how you will measure your success. For example, define devices or platforms you are going to run your tests on or test your software under different situations. 2- Design test cases based on requirements and risks. Requirements-based testing ensures that your tests cover the features and functions that the software should provide. Risk-based testing ensures that your tests cover the areas and scenarios that are most likely to cause failures or problems. 3- Use multiple types of tests such as E2E,  compatibility, sanity, and so on. 4- Review and update test cases regularly. This will help you to go through your test cases and update them based on the changes to the software. You can do this step on a scheduled basis or on demand. 5- Improve code coverage by leveraging unit tests. It is suggested to mix unit tests with other types of tests such as integration tests,. Let’s discuss these in more detail. Designing test cases You can use business documents, user stories, and product documents to find out what functionalities your software should have. As a result, you can write test cases based on all requirements. Try to see the software from the end user's perspective to know how the user interacts with the software and how they move through it. In addition, you should consider edge cases and boundaries. Apply technical documents and swagger files to keep track of risks and failure areas. For example, in a sign-in page like below: For example, in a sign-in page like below: Suppose that when the user taps on the username, the keyboard opens with digits only. This means the user can enter only numbers in the username field. But, if the user enters strings, what happens? How will the server handle it? Does a string crash the server? This is an example of a risk/failure point. It should be considered in the swagger file how the server should respond when an invalid or undefined input arrives. As a result, by using swagger files you can detect the possible failure bugs. The flows of the software and the interactions between the server and databases are usually put in technical documents. By using technical documents, you can discover the flaws and risk points too. Using Multiple Tests There are numerous types of tests in the software QA, but I won’t explore all of them here—I’ll save that for a dedicated article on HackerNoon. Each testing type serves a unique purpose, targeting specific aspects of the software to ensure quality and reliability. For example, focusing solely on performance tests might leave other critical areas, like compatibility across different platforms or devices, unexamined. To truly cover all angles of your application, it’s essential to incorporate as many testing types as possible. Improving code coverage Code coverage is a metric that measures how much of your source code is tested. The question is - how can you measure your code coverage? The answer is simple; by leveraging code coverage tools. You may ask how a tool calculates the coverage. Well, some criteria will be used by the tool to determine what parts of your code were not run in your test suite. There are some common metrics such as function, statement, branches, condition, and line. The tool will go through the code and discover all available metrics in the code. The formula is simple; the percentage of code coverage = (the tested metrics/all metrics in code) * 100. The table below presents some popular code coverage tools based on the programming languages: Programming Language

Code Coverage Tool/Tools



Java

Jacoco, OpenClover, JCov, Cobertura



JavaScript

Istanbul, Blanket, jscoverage



Ruby

SimpleCov, undercover, DeepCover



Python

Coverage.py, pytest-cov



Golang

test-cover command (built-in)



PHP

PHPUnit



Kotlin

Cobertura, JaCoCo



C#

Coverlet, NCover, dotCover



C++

Parasoft Jtest, Coco code coverage, Testwell CTC++ Programming Language

Code Coverage Tool/Tools Java

Jacoco, OpenClover, JCov, Cobertura JavaScript

Istanbul, Blanket, jscoverage Ruby

SimpleCov, undercover, DeepCover Python

Coverage.py, pytest-cov Golang

test-cover command (built-in) PHP

PHPUnit Kotlin

Cobertura, JaCoCo C#

Coverlet, NCover, dotCover C++

Parasoft Jtest, Coco code coverage, Testwell CTC++ Programming Language Code Coverage Tool/Tools Programming Language Programming Language Code Coverage Tool/Tools Code Coverage Tool/Tools Java Jacoco, OpenClover, JCov, Cobertura Java Java Jacoco, OpenClover, JCov, Cobertura Jacoco, OpenClover, JCov, Cobertura JavaScript Istanbul, Blanket, jscoverage JavaScript JavaScript Istanbul, Blanket, jscoverage Istanbul, Blanket, jscoverage Ruby SimpleCov, undercover, DeepCover Ruby Ruby SimpleCov, undercover, DeepCover SimpleCov, undercover, DeepCover Python Coverage.py, pytest-cov Python Python Coverage.py, pytest-cov Coverage.py, pytest-cov Golang test-cover command (built-in) Golang Golang test-cover command (built-in) test-cover command (built-in) PHP PHPUnit PHP PHP PHPUnit PHPUnit Kotlin Cobertura, JaCoCo Kotlin Kotlin Cobertura, JaCoCo Cobertura, JaCoCo C# Coverlet, NCover, dotCover C# C# Coverlet, NCover, dotCover Coverlet, NCover, dotCover C++ Parasoft Jtest, Coco code coverage, Testwell CTC++ C++ C++ Parasoft Jtest, Coco code coverage, Testwell CTC++ Parasoft Jtest, Coco code coverage, Testwell CTC++ Conclusion Conclusion To sum up, is it challenging to reach 100% test coverage in the software QA area. The key is that besides using some tips to provide better action, we should monitor the behavior of the application and have an eye on the production to recognize the possible issues that our users raise. In this way, we can find out the missing scenarios and add the related tests to our systems. References References https://about.codecov.io/blog/the-best-code-coverage-tools-by-programming-language/ https://about.codecov.io/blog/the-best-code-coverage-tools-by-programming-language/ https://www.atlassian.com/continuous-delivery/software-testing/code-coverage https://www.atlassian.com/continuous-delivery/software-testing/code-coverage Image header: by vectorjuice on freepik Image header: by vectorjuice on freepik vectorjuice

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Improving Test Coverage in Software QA

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