What Is Mutation Testing: Tutorial With Examples

In this comprehensive guide, we’ll unpack the idea of Mutation Testing, explain the process behind it, and scrutinize various types of mutation tests with examples from the real world:

What Exactly is Mutation Testing?

Mutation Testing is a defect-based testing method in which variations are made to a software application to measure the capacity of the test dataset in detecting discrepancies.

Whilst it may seem intricate initially,

About Mutation Testing

Mutation Testing’s inception dates back to the 1970s and was first introduced as an academic project. Due to it being a process requiring substantial resources, it was primarily disregarded. Regardless, with the progression in computing technology, particularly in software development, Mutation Testing has seen a resurrection, and is today a popularly used testing technique.

Defining Mutation Testing

Also referred to as fault-based testing, error-based testing, mutation analysis, or program mutation, Mutation Testing is a method for testing software that emphasizes making small alterations, or mutations, to the source code to evaluate if the predefined test cases can effectively recognize errors in the code.

The ideal scenario is for none of the test cases to pass. Passing a test case implies the presence of an error in the code. This signifies that the mutant (the altered version of the code) has persisted. On the other hand, a failed test case indicates the absence of an error in the code, and the mutant has been “terminated”. The primary aim of Mutation Testing is the eradication of all mutants.

Mutation Testing also contributes to assessing the quality of the test cases or test suite and encourages the development of more efficient tests. The more mutants we can eradicate, the higher the quality of our tests.

Key Concepts of Mutation Testing

Before we dive deeper into Mutation Testing, let’s acquaint ourselves with some fundamental concepts:

#1) Mutants: Mutants are the altered versions of the original source code. In essence, they are variations of the code involving minor modifications. Ideally, when test data is run through the mutants, the results should differ from those of the original source code. Mutants are also known as mutant programs.

In terms of types, mutants can be:

• Persistent Mutants: These mutants remain unaffected or “survive” even after the test data is run against both the original source code and the mutant versions. Persistent mutants need to be eliminated and are also referred to as live mutants.
• Eliminated Mutants: These are mutants that are eradicated or “killed” after mutation testing. The test results produce different outcomes when compared to the original source code, indicating an error’s presence.
• Equivalent Mutants: Although equivalent mutants bear resemblance to live mutants in terms of remaining “alive” after the test data runs through them, they maintain the same meaning as the original source code and differ syntactically.

#2) Mutators/Mutation Operators: These form the backbone of mutation testing as they form the structure required for introducing modifications to the source code. Mutation operators specify the exact amendments or transformations made to the code to create mutant versions. They are sometimes identified as faults or mutation laws.

#3) Mutation Score: The mutation score is a measure based on the number of mutants. It is computed using the subsequent formula:

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