Test Coverage in Software Testing: Get to Know Your Unknowns Better

What Test Coverage Does And What Is For?

Simply put, Test Coverage in software development is a specific metric that measures how well a tester's tests are performing. 

It is a suite of tests that harnesses, catalogs, and analyzes information about how well an app is thoroughly being tested and it attempts to identify critical gaps in the requirements, allowing QA testers to further hone and refine their testing patterns.

Test Coverage, more and more, is becoming a central indicator of how rigorous an app’s testing process is, and therefore it is playing a very important role in the overall development process as well as playing a very crucial role in software maintenance. 

While both being able to monitor that QA testing adheres to certain high levels of quality, Testing Coverage also helps guide testers to better design their tests for test cases which are being overlooked or areas that are not being carefully addressed. 

Testing Coverage comes with a traceability factor that allows for the tracking of changes, as well as, at an early stage, can identify defect leakages and other bugs usually found in pre-production testing environments.

Testing The Unknowns

There are known knows is a famous phrase from a response former United States Secretary of Defense Donald Rumsfeld gave to a press conference, who later added, there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns—the ones we don't know we don't know.

Test Coverage easily adopts and embraces this philosophical metaphor. 

Its purpose is to allow QA teams to comparatively and comprehensively address these tricky known unknowns, to fill in the gaps between what the teams know they don’t know but need to figure out before the next stage in the process makes it all to clear to them that they really need to know. 

And, of course, by doing this, Test Coverage helps devote resources to knowing the full testing picture, the Big Testing Matrix as it were, and it allows teams to save energy for addressing the unknown unknowns, the unforeseen and unplanned for challenges that can trip up even the most solidly designed strategies. 

How Test Coverage Can Be Accomplished?

As with all things DevOps, app software is already built-in with testing parameters in mind, with scores of dedicated libraries and controlled test environments already going hand in hand down the development process pipeline. 

Optimal coverage aims to map every executed function, even functions that are rarely or hardly ever accessed. It prioritizes the conditions of the most important functions that have passed all tests. The results, after careful analysis, help to reveal the unknown knowns areas of the tests which can then be updated to include and account for these missing variables and develop the most rigorous and manageable set of regression tests.

The team over at TRYQA.com spells out three distinct flavors of coverages:

1) Statement coverage
2) Decision coverage
3) Condition coverage 

All three segments of what is considered solid coverage help identify two main situations: quantitative measurements as an indicator of the quality of the test, increasing coverage, as well as identifying those test cases that are either redundant or lacking in meaning which therefore decrease test coverage.

How Is Test Coverage Calculated

Essentially, Test Coverage is calculated as a percentage with the goal of coverage to reach the much-coveted but almost impossible 100% mark. 

This infographic illustrates the theory:


Requirements Coverage

Hardik Shah, writing for SimForm.com, chimes in with his view of how to create solid testing coverage:

In the Requirements module, you create test coverage by linking tests to a requirement. Test coverage assesses the impact of a change in the test or requirement. Instead of covering each requirement only at the level of the test, you can cover a requirement by test configurations. A test configuration represents a specific use-case of a test. Covering test configurations with requirements provides finer granularity by covering multiple use cases.

Finer granularity is like wearing a new pair of sunglasses and seeing the world with different eyes. Finer vision equals increased clarity into all the aspects of testing an app but specifically those that have yet to be tested or yet to be incorporated into more austere testing matrices or added to this more rigorous form of Testing Coverage. 

Increased clarity equals more time to resolve issues early enough in the process so that they can be tackled efficiently.
Test Coverage Cover

Test Coverage

Tools Of The Test Coverage Trade

Test Coverage, as with all aspects of DevOps and testing, is complemented and augmented by a hugely diverse and quickly evolving set of toolboxes, kits and chains, all there to help determine which code has been tested and, more importantly and strategically, which code has been overlooked let’s say in the case where automated testing strategies have been applied.

Following tools that are the most popular among Test Coverage designers:

Building The Perfect Test Coverage Matrix

To ensure that an app has been thoroughly tested, a Test Coverage Matrix is created to cover a wide spectrum of tests including but not limited to new feature testing, application coverage and code coverage.

Essentially, as the name suggests, a Test Coverage Matrix is a spreadsheet table of all possible outcomes in a given scenario and can really be useful to give testers basically a visual checklist to run down everytime a new component is added or has been modified.

Below, we have one illustrating all of the possible outcomes to an attempted log in.

Test Coverage Matrix 

Test Coverage Matrix - Simple Spreadsheet Structure

What exactly goes into building a matrix varies from team to team and firm to firm but generally, they are used to trace that all requirements have been thoroughly tested throughout each and every phase of software testing.

The Benefits Of Test Coverage

The benefits of Test Coverage are exhausting when performed with proper test management tools. They employ normal static review techniques like peer reviews, function inspections, and end-user walk-throughs. 

At first what is just now seen as a defect or a bug can become a caterpillar who later will undergo metamorphosis into a beautiful butterfly of the next actual test case, passing with flying colors. 

On the one hand, Test Coverage assures the quality of all tests made in the app’s development cycle, identifying which segments of code were actually modified. And on the other hand, it helps make determinations of how to test the paths in an app that have not yet been tested. 

Just like an apple a day keeps the doctor away, early prevention is the only way to keep our bodies disease free and similarly with app testing.

If you want to avoid nasty illnesses like all sorts of bugs, app hangs and crashes, incompatibilities across different devices, defect leakages, all huge time and money wasting situations, test coverage, like a simply delicious and nutritious apple, will make sure your app has a healthy birth and release to the market and likewise, a solid Test Coverage strategy will care for the app’s health as the little baby grows up, matures and evolves, release to release, version to version.

What Are the Main Differences Between Code Coverage And Test Coverage?

There are some variations in how code coverage and test coverage are to be employed and how these two concepts interact for professional testers in today’s DevOps world. 

Code coverage is a measure of how much code is being processed during a given test (a white box testing methodology) while test coverage more embraces a range of suites of tests that cover and employ a wide array of mechanisms (a black box testing methodology). 

Developers utilize code coverage mostly while unit testing, forever calculating what percentage of every line of code has been executed, tested, and verified. They design tests that check branch coverage, or sometimes called decision coverage, for example, to ensure browser compatibility. 

They focus on function coverage, testing all possible functions especially the ability of the app to access the terabytes of Big Data in the Cloud as with calls to external API functions. 

And finally, they orchestrate statement and loop coverages to make sure every possible statement and loop has been rigorously tested. Each of these results in code and runtime instrumentations, a compiled set of performance indicators, and powerful diagnostic data to detect any discrepancies.

Test coverage is a slightly bigger concept that streamlines different code coverages into a framework of tests depending on the priorities and functions of the app. 

These developers employ unit and function testing at the very micro, line by line, scale and later they move on to the larger scale, macro-level testing with integration testing to ensure all of the app’s parts work together. 

Finally, acceptance tests are designed to make sure the app is actually ready to be released to the public. This is where an app’s priorities and purpose come into account and methodologies like features coverage, risk coverage, and requirement coverage all come into play, all to ensure that the testing coverage is appropriate whether its for a mobile app or a full-featured web site.

Both code coverage and test coverage have suites of tools available to help developers integrate these systems into their testing suites.  And most projects would benefit from adopting both code and test coverage into their test schemes. 

Examples Of Test Coverage



In their presentation titled “Assuring Mobile Test Coverage,” the folks at Perfecto Media share their strategy of 80%, 50%, 30% as a way to envision a more generalized Test Coverage modest goal of coverage. 

In this particular case, they examine the coverage of the highly fragmented and highly diversified range of mobile devices and operating systems. 

Their initial target goal of 30% coverage along the Test Coverage process being further refined and enhanced to 50% coverage with the end goal of 80% coverage to basically help cover the majority of mobile phone users even those mostly senior citizens still using legacy phones and outdated and no-longer update-able obsolete dinosaurs like iPhone 4S’s and Samsung Galaxy Minis. 

Conclusion: Never Enough Coverage

In the metro tunnels of London’s famed Tube, you can see a sign on each platform warning commuters to “Mind the Gap” between their feet on the edge of the platform and the opening doors of the metro car.

Mind the Gap could be the perfect slogan for those looking to implement a Test Coverage Matrix.

A strategy is all about thinking about what you haven’t thought of yet. Here in Test Coverage, it’s all about testing everything you never bothered to test before. Anticipate that you already know that you may have a few unknown factors already lurking in your codes that could turn out to be huge performance disasters down the road. 

Know that they probably do exist, anticipate for them, and having solid coverage just increases your chances of hunting them down.

Is 100% coverage even possible? 
How much coverage is enough? 

The quick answer: it’s never enough. 

But more and more what is becoming the overall guiding goal of testers is to take all steps possible to make sure that their Test Coverage is as maximum as possible. Teams who have designed their coverage for max potential tend to have easier, more hassle-free paths down the production pipeline and that’s what it’s all about.

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Grzegorz Kłos
Grzegorz Kłos - Apphawks Co-founder
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