Ways to measure test coverage
Anyone who relates to QA will tell you that there is no way to measure Test Coverage with 100% accuracy. No matter what tools or metrics you use, if the test performed manually or by automation. It's like you want to measure results which are currently shown as objects in a three-dimensional coordinate system with the use of the two-dimensional coordinate system diagram. Don't matter how many metrics, tools or methods you try to use you will always have gaps in results - areas which were not measured. And even if you succeed with gathering such a massive amount of data it will require an inconceivable amount of resources and time.
1# What is test coverage?
Test coverage can be considered as a software testing metric that defines test density. In other words, test coverage gives a general idea about the comprehensiveness of the QA process and consequently lets stakeholders understand whether a product has been properly tested, i.e. whether all its ins and outs have been checked.
2# Advantages of test coverage measuring
Some metrics are better than none of them at all. By measuring your test coverage you will get next important advantages:
Let it not be a 100% accurate result, but it still will show how good your current test coverage is which will help to understand how much time it will require to finish with project tests.
According to gaps which will be noticed in test coverage you will be able to add new required tests which will improve the quality of the project.
According to test coverage statistics you may notice which tests do the same job and reduce the amount of overdone tests on your project which will save some additional time and resources.
Having test coverage in place, it is easier to make a decision on whether exit criteria have been met.
With test coverage, it is definitely easier to control the scope of work and schedule.
3# Drawbacks of test coverage measurement
Unfortunately, test coverage measurement is associated with certain challenges that we can refer to its main drawbacks:
Test case analysis cannot be completely automated. In contrast to code coverage, tools that can automatically generate a comprehensive report on test coverage are not available.
As long as most actions are manual, it takes a lot of time and efforts to properly study and analyze requirements and test cases;
Test coverage data is not 100% accurate because there is a high probability of errors and omissions.
4# Basic methods to measure your project test coverage
There are lot's of methods which are using different metrics and tools to gather information which will be later used to indicate the actual test coverage. Many of them are used only for specific types of projects which provide specialized data and can't be used out of scope of such kinds of projects. So let's take a look at most popular from methods which may be applied to almost any type of project and way of testing (manual or automation):
Test coverage by feature - Is the most simple one. First you need to prepare a list of all features which are available at your project and then check that all of them are covered with tests. This way of test coverage is not really informative regarding how good those features are tested but it will quickly show if you don't forget to cover with tests any of the features. It's like the first step in proper test coverage - first you need to make sure that all features are covered and then you need to check how good those features are covered.
Test coverage by instrumentation (test code coverage) - Not so simple method as first one. It uses a special tool which will check what part of code was executed while you perform some action in the system. Results which will provide such tools will indicate the percentage of code which was executed during your set of tests (usually automation tests). But pay attention that if code was executed it doesn't necessarily mean that the expected result was received during this action. So same as in the first case it also doesn't indicate how good the project was really tested. But knowing that all of the system code is affected by your set of tests is also one of the goals which you need to achieve to have the most top test coverage of your project.
Test coverage by GUI - Any project like mobile, desktop, web etc. has some user interface which may have lots of screens, pop-ups, drop-downs, tooltips, buttons, links, scroll-bars and other stuff which also should be covered with your tests as all those elements will be seen and used by user in first place. You need to make sure that all buttons which the user may want to click will work exactly as required.
Test coverage by risks - The next list item is risk coverage. An application cannot be considered completely tested if associated risks and their causes have not been tested carefully. Even if all app functions work properly, it is important to predict possible app failures related to a connection failure, a vast number of concurrent users, etc. QA team should check app behavior in risky situations and its ability to withstand. In nutshell, the technique implies listing the risks related to software work and reassuring they are appropriately covered with tests.
Test coverage by transition - This method counts all number of "ways" or "path" which the user may try to use to receive the required results. It's like you may get to work by car, train or jet and return home from job also by all these ways. So all those ways should be tested well. It's really important to cover this for web applications where users may also navigate through URLs or links and not only by buttons and options in drop-down menus.
Test coverage by scenario (use cases) - One of most important measures of test coverage but at the same time it is really hard to measure it. At least without using relevant tools. Now there are many products which allow you to trace your users activities and record all actions and ways which they used on your site for example. This will allow you to have a list of use cases which are performed by users while they use your project functionalities. And if you covered all of them on a high level - it's a really low chance to miss some critical bug during the testing. But what about cases when you have a new functionality? Case when there is no statistic of how users will decide to use this new feature? Yeah... In such cases this method of test coverage measuring sometimes becomes even less accurate than the first three methods. But a qualified QA team is able to prepare such a list of use cases which will be most close to what real users do so still it is good to have this test coverage measure results as well.
5# Test Coverage Matrix
In a nutshell, a Test Coverage Matrix can be defined as a table used to assure that all the needed requirements, scenarios, or features are counted and not a single one has not been left out. In other words, In the simplest terms, TCM is a checklist that lets QA experts understand if the app functionality is checked in all possible ways.
There are no special requirements to test coverage matrix design. You can get down to TCM on the fly. You may make up your own table according to your preferences. For instance, your table can consist of the following columns: "App module", "feature", "Test case type" (e.g. Positive, negative, boundary), "Test case number", etc.
Test coverage matrix is indeed a useful tool, QA experts actively use to easily detect probable gaps, i.e. functions or requirements not covered with tests or covered improperly or otherwise to see which app features are covered with the excessive number of tests that can be deleted as redundant.
6# Test coverage versus code coverage
These two metrics evaluate the effectiveness of software testing and therefore software quality. However, they are often mixed up. That is why it makes sense to throw the light on the differences between them.
|Test coverage||Code coverage|
|Test coverage defines how many requirements, functions, features have been covered with test cases.||Code coverage defines how many code lines have been successfully validated.|
|The black box testing technique is mostly utilized||The use of the white-box testing technique is needed.|
|Test coverage is relevant for QA teams.||Code coverage is relevant for development teams.|
|It covers all possible types of testing.||It is associated with unit testing only.|
|Test coverage is more subjective. It is difficult to obtain accurate data as too many aspects must be considered||Code coverage is more objective. Data is accurate.|
|Test coverage matrix or TCM is one of the best ways to measure test coverage as it provides a list of requirements or functions and test cases that cover them.||Reports on code coverage are created by special tools (e.g. Serenity BDD, JaCoCo, PITest, JCov, etc.). Injected into certain code junctures statements control code execution and scripts submit information on the extension of code execution.|
7# Ways to increase test coverage
In real-world conditions, it is practically impossible to gain one hundred percent test coverage. Higher test coverage may require more resources, time, and money. So it can lead to extremely heavy test expenses and release delay. In this case, prioritization is a ticket to success, Still, it does not mean that every QA team should not struggle to achieve as high test coverage as possible in order to deliver a product of better quality. Below you can find some ways to enhance your test coverage.
Detect and eliminate unnecessary parts of code, scripts, and test cases
In order not to waste your valuable time and effort on the unnecessary, obsolete, and irrelevant test cases, but to devote it to the new and useful ones instead, it is important to regularly review and update your test cases or scripts.
Plan, plan, and one more time plan!
It is impossible to gain anything without proper planning. A plan helps you set key objectives and shows you the direction in which you should move. So thoughtfully plan your test strategy, define what should be tested, which type of tests should be executed, which devices and platforms should be used. Then carefully track the work progress, indicating what is useful and what seems to be ineffective, and tweak your plan correspondingly to provide maximum test coverage.
Make active use of test automation when it is relevant
Test automation is considered to be the surefire way of test coverage improvement. It is pretty obvious, as automated tests immensely boost test procedures, giving an opportunity to execute tests extremely fast at any time of the day or night and without any human intervention, which means that a QA team can focus on other tests that require their close attention. In other words, test automation is a great way to execute as many tests as possible within stated deadlines.
Enhance your code coverage
As we have already figured out, code coverage indicates the number of code lines executed during unit testing. While unit testing and code coverage cannot address all questions, they still must be considered. A proper and comprehensive unit testing helps reveal more bugs from the very beginning, which significantly improves product quality and simplifies the work of the whole product team.
You can't get a 100% accurate way to measure your product test coverage but by combining different metrics and tools you may get a number which will be most close to the actual one. The methods of test coverage measuring which you should choose totally depend on your project functionality and available resources, time. But by having such data you will be able to have more or less stable and high test coverage level of all project aspects during all time of development and support which will significantly improve quality of your product!
Hope that this article didn't leave any open questions for you and it was interesting to read it. Have a nice day and make good effort in improving the quality of software in the world!