Snapshot Testing: A Powerful Tool for Assuring the Quality of Automated Tests

The test data is an essential part of the verification logic in automated tests. There are two kinds of data: the input data and the expected data. The input data defines the program flow and the expected data specifies the desired outcome of the test. For example, assertEquals(user.getName(), “Andreas”); shows that “Andreas” is expected data and is part of the verification logic. The quality and quantity of both types of data determine how high your data coverage can be. If you have poor input data and verify only a few data points, the data coverage is low and the data processing logic is not protected from unwanted code changes.

A practical approach to reduce implementation and maintenance effort is to record the actual data to a snapshot file and use it during the next test run for data comparison. This technique is called snapshot testing. Snapshot files become a part of the verification process and are usually committed to the code base and handled like any other code. That means snapshot files have to be reviewed in pull requests and traced in git log for changes.

Snapshot testing has several advantages:

• It allows recording a large amount of expected data in seconds.

• It simplifies updating snapshot files by replacing the existing file with a new one and validating the changes.

• It reduces development and maintenance costs and guarantees high data coverage if the data scope is correctly defined.

Snapshot testing also has some challenges:

• It requires defining the appropriate test scope, which can be very difficult to filter dynamic data.

• It lacks good tools for filtering and managing snapshot files.

• It has not been fully understood from a theoretical perspective.

If you have problems with defining the test scope in your automated tests and want to discuss it, please contact me and we can see what we can do in your situation. I have a lot of experience in snapshot testing and provide effective tools that help you increase data coverage in your application and keep development and maintenance cost low.

Your passionate tester, Andreas Hollmann

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