Techniques for Automation Coverage

May 10, 2022

Let’s face it: while testing manually still has its perks, automated testing has become the real deal. That said, having sound automation coverage techniques remains crucial for any modern software organization. The only problem is that coming up with a proper testing strategy is easier said than done.

One of the major challenges of testing is determining when to stop. What testing capacity is sufficient? Should you focus on testing areas that are more likely to have problems, or should you strive to test 100% of your applications?

In this post, we’ll take a look at the best techniques for automation coverage and how you can use them to make the most out of your testing strategy. But first, let’s take a quick look at what test coverage is.

What Is Test Coverage?

Test coverage refers to the process you use to determine whether you’re testing all the things you’re supposed to test. It enables you to check the quality of your testing. By identifying the areas without coverage, test coverage helps you create tests for those areas, thereby increasing the overall quality of your test suite.

Test Coverage Vs. Code Coverage

Test coverage is often confused with code coverage. That’s understandable, given that they’re very closely related. Even so, despite their underlying principles being similar, they are two different things.

Code coverage is a metric related to unit testing. It measures the percentage of execution paths and lines in the code covered by at least one test scenario. To optimize code coverage, you need to have a dedicated coverage solution, in addition to the unit testing framework you already have in place.

The most common type of code coverage includes line coverage—it measures the ratio of lines of codes covered by at least a single test. Despite this metric being useful, it’s usually not enough. This is because while you may attain 100% line coverage, you’ll still have some untested areas in your application.

On the other hand, test coverage involves testing every requirement at least once and is a QA team activity. It ensures that all the things that need to be tested are tested. So, what’s the difference between code coverage and test coverage?

Code coverage categorizes a lower-level metric whose sole focus thoroughly measures the unit tests that cover existing codes. Because it’s a technical concern, developers are the ones who mostly care about code coverage.

Test coverage, on the other hand, is a higher-level metric that aims to determine how well an application is tested when it comes to its requirements. Therefore, it is a concern not only for engineers but also for other people who perform testing in an organization, such as QA professionals.

How to Find Test Coverage

Calculating test coverage is actually fairly easy. You’ll simply take the number of lines covered by a given test and divide it by the total number of lines in your application. For instance, suppose your app has 100000 lines, and 28000 of those are exercised by at least one test scenario; your test coverage will be 28% or 0.28.

That said, figuring out the number of lines in the application that are currently under test can be challenging since there are several different types of software testing, with each using different QA test coverage tools.

What Are the Benefits of Test Coverage?

Here are some of the ways you can benefit from test coverage:

  • It eliminates any defects in the early stages: With test coverage, you can determine where defects and gaps are in the early stages of the test cases. It, therefore, saves you from future headaches.
  • Better coverage: It creates more test cases to ensure extensive coverage. This minimizes defects and leads to more streamlined processes.
  • It removes redundant scenarios: Test coverage can be especially helpful in identifying and removing test cases that don’t make sense in the current project.
  • It helps discover uncovered areas: It can help you unearth areas that weren’t covered by a set of test cases. As such, it makes your program more robust and mistake-free.
  • It ensures smoother testing cycles: With test coverage, you can prevent any defective leakages by applying test coverage analysis.

6 Key Techniques of Automation Coverage

Programmers made an automated coverage testing system for their new project.
Artificial intelligence technology to make choices.

With the basics out of the way, let us now look at key techniques of automation coverage:

1. Product Coverage

This technique looks at test coverage from a product perspective. Product coverage answers questions that relate to the areas of the product you’ve tested. For instance, let’s say you’re testing a simple calculator (that only has four arithmetic operations). Of course, you need to confirm that operations are working as intended. But there are other factors that you must also take into account.

These include how well the calculator handles large numbers or how it behaves when the user does something unexpected such as posting non-numeric characters into the text field. Only after verifying such scenarios can you claim that your application has complete product coverage.

2. Requirements Coverage

This is arguably the most important automation coverage technique. After all, while your application might work well, it has no value if it can’t meet the user’s requirements. In short, you need to take the list of requirements into account when creating your test plans. Requirements coverage helps ensure that all the requirements are fulfilled, which is the main reason for software development.

3. Risk Coverage

Risk coverage assesses the risks that are inherent to an application and tests them thoroughly. It entails listing the risks that are involved in an application and ensuring that those risks are covered by the test.

For example, suppose you’re testing an app that helps users manage their personal finances; you have to determine how your app will behave in different scenarios when a third-party API goes offline. In short, for your application to have coverage, you have to list all of its relevant risks and answer the questions they elicit.

4. Compatibility Coverage

Compatibility coverage ensures that your tests cover your application across different operating systems and browsers. While it is impossible to test across all combinations, you need to conduct extensive research on three of the most used browsers across various platforms (Android, Windows, macOS, iOS, and Linux) and then ensure that you cover those platforms.

5. Boundary Value Coverage

Boundary value coverage involves ensuring that all your boundaries are properly tested. For instance, suppose you have a feature that takes numbers as inputs, but it only accepts numbers between 0 and 100; you need to ensure that these boundaries receive proper testing. To do that, you need to test at the boundary and the figures immediately below and above the boundary.

6. AI-Aided Test Automation

Just like its name suggests, AI-Aided Test Automation is all about automation. It involves the use of test automation tools that rely on AI, thereby taking testing to a whole new level. Such tools enable test suites that leverage machine learning to learn with every execution and make themselves better. As such, with AI-Aided Test Automation, you end up with a robust and stable test suite.

Learn More About Automation Coverage

Automated testing is essential for any modern software organization – it can help increase their efficiency, as well as their return on investment.

Developing a sound testing strategy isn’t the easiest of tasks, given the numerous challenges involved. One of those is deciding what and how much to test. Fortunately, with the testing techniques outlined above, you can track the quality of your tests and areas currently validated.

Do you want to optimize your software testing? Appsurify’s TestBrain can help your existing practices perform their testing practice more efficiently and optimize their functionalities through automatic risk-based testing. Contact us today to schedule a free demo and eliminate flaky tests from distracting your team.