How to Measure a Test Coverage and Why It Can Be a Problem
Based on various possible concepts and explanations, the coverage is how effectively we can explore a product according to a particular model (an ideal).
A lot of testers, QA engineers and specialists in software testing-related professions wonder: “How to measure coverage?”. In other words, how to record the thoroughness of testing?
Answering this question, we should realize that there’s no unique answer that can fit any situation. In most cases, no testers can measure test coverage with valid and reliable data. Since, unlike length, width, and quantity, the coverage does not have fixed units of measurement.
A simple example:
- If we count all the test cases we have (in the app under test), we will not get complete information about the factors and observations to which these cases are directed.
- The count of the code lines that are used in certain automated tests will not tell us what exactly those tests were evaluated.
- The sum of the items in the list of risks cannot consider the relative importance of these risks.
Sometimes, it is still possible to calculate all the factors that have some relation to the coverage category. A simple example. There’s a system with 8 different users. How many users have been tested, in terms of assessing whether there are permissions and prohibitions set for them? If our answer is less than eight, then our coverage knowledge is insufficient.
Use of Nominal Coverage Rating Scale
We know extremely little about this product. We know it exists, but so far it is like a black box to us. Testing, if any, has not given us the full extent of information about the product.
First, we take a look at the system. We have done purely basic probing: we have done smoke and sanity testing. If the product crashes, we will know about it.
We understand the system performance very well. We have learned all critical aspects of the system’s performance. We have managed to implement a large amount of testing based on private patterns. There are still some parts of a system that weren’t tested.
We have a deep knowledge of the system. We have studied the product well and used an array of test techniques to study it. A wide range of criteria for finding optimal quality have been tested. If a problem or a feature is found in the system, it will be a very big surprise to us.
Measuring test coverage is a vital aspect of software development, offering insights into the quality and reliability of your codebase. However, it’s essential to recognize that while high test coverage can be an indicator of thorough testing, it’s not the sole metric to guarantee bug-free software. Blindly pursuing 100% coverage can lead to diminishing returns, overlooking crucial scenarios, and creating a false sense of security.
The key lies in striking a balance. Prioritize testing critical and complex code paths, consider different types of testing (unit, integration, E2E), and continually assess the effectiveness of your tests. Remember that testing is an ongoing process, and its success isn’t solely determined by numbers but by the depth and relevance of the tests conducted. So, measure your test coverage wisely, focusing on meaningful coverage rather than chasing an arbitrary percentage. Ultimately, it’s the quality of your tests and the thoroughness of your testing that will contribute to a more robust and dependable software product.