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Which quality defects can you automatically detect in system tests and requirements?

I am a strong advertiser of modern, automatic methods to improve our day to day life. And so I really don’t want to check by hand whether my tests and requirements fit my template, or whether my sentences are readable. So quality assurance and defect detection, for example reviews or inspections, should use automation as far as possible.

BUT: When I speak to clients, sometimes people get so hooked up by the idea of automatic smell detection, that I need to slow them down. Therefore, this post tries to give a rough overview: What is possible to detect automatically?

The answer basically depends on two questions:

  1. How much syntax (or structure) do your artifacts and tests have?
  2. Which language do you use?

In this post I will refer to requirements artifacts here and there, but the answers are pretty much the same for both system tests and requirements.

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Conditionals: Why you should avoid these two letters for better test case execution

At Qualicen, it’s often my job to check other people’s system test cases and tell the team what I think about these tests. So what do I look for? Well, in principle it is simple: After tests are written down, they are “only” executed and maintained. So this is where tests can be bad and I try to spot things that make execution and maintenance harder. For the maintenance, the largest problem here are clones, which we covered in our last blog post. For the test execution, the main problem that you want to avoid is that different testers test different things. This is called ambiguity and comes in many tastes. In this blog post, I want to explain what is structural ambiguity and why it is bad, and this way help you to create better test cases.

(Scroll to the summary, if you don’t care about the details) 😉

Ambiguous test flow

The problem for test execution that I want to discuss here, is an ambiguous test flow. This means, that for a single test case, there are multiple paths that a tester can follow when she executes the test. Let’s look at an example.

A simple, straight-forward natural language system test case.

A simple, straight-forward natural language system test case.

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Why test clones mess with your test quality – And how to avoid them

I recently reviewed a manual test suite of one of our customers. One of the first things I check very early in a review is the number of clones (i.e. duplicated parts of a test suite, usually created by copy and paste). In this recent case, I discovered that nearly 70% of the test suite is duplicated. That means, when I take some arbitrary test step, the chance is 70% that the test step is a 1:1 copy of another step. At the top of the post is a tree map that visualizes the amount of clones I found. Each rectangle represents a test, the more red a rectangle is, the bigger the amount of cloning.

In my experience, cloning in test suites is the biggest problem with regard to maintainability of a test suite. Cloning causes considerable costs as the effectiveness of the test suite decreases and the effort for maintenance rockets. In this post I take a closer look on cloning in test suites. I show you an example to illustrate how clones can look like and explain where clones come from. Later, I give you good reasons why you should care about clones in tests and discusss strategies you can employ to avoid or at least deal with clones.

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