Automated Acceptance Testing Automated Testing

Refactoring legacy code using automated acceptance tests

A question I often get asked as a consultant is how to maintain a legacy code base that has very little or no unit tests, or any automated tests for that matter. How do you start to refactor the code and introduce unit tests?

The problem with immediately adding unit tests to a unit test free legacy code base is the code won’t be testable (as it wasn’t test-driven), and it will require refactoring to make it so. But refactoring legacy code without unit tests as a safety net is risky and can easily stop your application and introduce bugs, so you’re in a catch-22.

A good solution to this problem is to write a few specific automated acceptance tests for the feature you would like to add unit tests to, before you write any unit tests.

For example, imagine you would like to add some unit tests to the registration feature of your application, you might automate four acceptance test scenarios:

Scenario One: User can register using valid credentials
Scenario Two: User can’t register using existing email address
Scenario Three: User can’t register without providing mandatory data
Scenario Four: User can’t register from a non-supported country

Before you make any changes to your code base, you must write and execute these scenarios until they are all passing.

Once they are all passing then you can start writing unit tests one by one until each passes. As you write unit tests and refactor your code as required, you should run your specific acceptance tests to ensure the high level functionality hasn’t been broken by your changes.

Once you have completed your unit tests you will have a set of unit tests and automated regression tests with code that supports both.

You can repeat this for each feature in your system, and slowly combine a few key scenarios into an end-to-end scenario that replicates a common user-journey throughout your application.

At the end of this process you will have cleaner code, a set of unit tests, a set of feature based acceptance tests and one or two end-to-end user journeys that you can execute against any change you make.

Paying down technical debt is hard, but following a methodological approach using automated acceptance tests as a safety net makes it practical to do so.

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