What is BDD (Behavior Driven Development)?

Behavior Driven Development (BDD) describes the behavior of a feature in a structured language that the specialist department and development team understand simultaneously. The core pattern is called Given-When-Then: Precondition, Action, Expected Result. This format bridges different ideas, serves as the basis for automated testing and keeps requirements and test code consistent in a common place.

Key Takeaways

• The given-if-then syntax of BDD creates a common language for business and development that specifically prevents misunderstandings in feature descriptions.
• Cucumber combines readable text descriptions directly with executable test code, so that even non-specialists can understand the purpose of a function without knowing the technical implementation.
• Test data can be stored in BDD as data tables directly in the feature file or outsourced to external files, whereby an incomplete database is the most common pitfall from the outset.
• Functions in the test code should not have more than eight executable lines. If a function grows beyond this, it is a candidate for splitting.
• BDD tests are much less likely to be affected by adjustments than surface tests, which justifies the initial additional effort during implementation in the long term.

What Behavior Driven Development actually describes

Behavior Driven Development (BDD) describes the behavior of a feature in a language that is understood by both business and technical stakeholders. The focus is not on the code, but on the question of what a feature should do.

The classic process without BDD is asymmetrical: a feature is formulated and initially it is primarily the product owner who knows what it is about. The development team only joins in later and has to figure out what is important.

BDD starts before that. It forces everyone involved to describe the desired behavior in such a way that no technical jargon is necessary and nobody drifts off. The result is a common basis to which both the specialist area and technology can refer.

How the Given-When-Then structure works

BDD scenarios follow a given-if-then structure that breaks down a test into three clear phases. The Cucumber tool uses the Gherkin language for this.

Using the example of a browser test, it looks like this:

• Given (Given): The browser is open, the page to be tested is called up. This is the initial situation.
• When (When): The login mask is filled in and the OK button is pressed. This is the action.
• Then (Then): If the data is correct, the page appears after the login; if it is incorrect, an error message appears. This is the expectation.

This form is compact and still readable for everyone. A developer recognizes what needs to be done. Someone from the department who has thought about it understands what it is about without any technical knowledge.

This overlap is precisely the point. Prose text creates a different image for each reader, and these images are rarely identical. You often don’t even notice the difference. The Given-When-Then structure narrows this scope and eliminates misunderstandings.

BDD is teamwork, not a question of roles

Nobody has the exclusive right to write BDD scenarios. Both the specialist department and a test analyst can formulate a scenario; there is no fixed responsibility.

In practice, the analysts often provide an initial version and the testers check it. Some things can be adopted one-to-one, others have to be supplemented or adapted. Every change is fed back to the specialist department: is it still correct or has a deviation occurred?

This interaction is the real value. Talking and agreeing with each other, not the format itself, ensures a shared understanding.

From the description to the executable test

Once a scenario has been satisfactorily formulated, implementation follows. In Cucumber, the steps can be generated from the scenario as a framework, which is then filled with code, the so-called glue code.

This glue code contains the programmed functionality and is typically implemented by test automation engineers or developers. The Given, When and Then steps reappear in the names of the functions, creating a one-to-one assignment.

The effect: even someone from the specialist department could look at the test code and understand which functionality maps which step. How exactly it was implemented is of secondary importance.

The finished tests are run via a build server, such as Jenkins. Depending on the test strategy, they are executed as soon as a commit is received.

How BDD handles test data

In BDD, test data can be stored directly as data tables in the feature file. These tables are filled and flow into the automated test during the run. Who maintains them, whether department or tester, is open.

Alternatively, the data can be stored in external files and retrieved from there. Both methods are possible.

The preparatory work is important. The test data should be meaningful and complete before you start. Subsequent extensions are feasible, but often entail modifications to the test. Test data management therefore deserves intensive attention in advance.

A source of truth about Jira and build servers

BDD only unfolds its benefits when scenarios and code remain synchronized. Theoretically, the department could write directly in Cucumber, but this is not usual.

One practical way is via Jira: scenarios are stored there and downloaded to the feature files via a plugin or uploaded again when changes are made. The exchange is bidirectional and can be controlled via the build server.

If a developer pushes a change, the build server pulls the updates and reloads the current status. The department always sees the latest version of the feature files in Jira.

This solves an old problem. Multiple storage locations quickly lead to the question of which version is the latest. BDD, on the other hand, relies on one source of truth in one place.

Where BDD fits and where the limits lie

BDD is flexible because practically anything can be packed into the glue code. It is not limited to surface tests, but is also suitable for integration and acceptance tests, expandable via additional libraries.

Even manual tests are possible. The Given-When-Then statements are then prepared without executable glue code behind them. They serve as standardized documentation that is processed by a manual tester.

There is a clear limit to load testing. Technically feasible, but not the right tool. Other means should be used here instead of bending BDD.

Why getting started starts with the right test case

The best starting point is a test case that is neither trivial nor overly complex. It should have a visible impact, but should not take months to complete.

Behind this is an honest realization: BDD comes with an overhead. It is faster to code down a test case directly than to create additional feature files and a well thought-out Gherkin structure. This additional effort only pays off later, and this must be clearly communicated from the outset.

This BDD implementation has a certain overhead that only pays off later. You have to be aware of that, and you have to be careful from the outset.

• Pascal Moll

Maintenance: BDD tests age more slowly than surface tests

BDD tests need to be maintained like any other test, with one extra step. If circumstances change, the Given-When-Then statements must also be adapted to the current status.

The good news: experience shows that this happens much less frequently than with pure surface tests. Surface tests are noticeably more maintenance-intensive.

The background keyword in Cucumber is a practical way of preventing redundancy. This allows you to define steps that always run at the beginning of a test. This saves duplicated code and makes the scenarios clearer.

Test code is code: Clean code pays off

BDD scenarios generate real code, and this requires the same quality as production code. The complexity of a programmed function should not exceed a healthy level.

A practical rule of thumb: if a function exceeds eight lines, it is worth thinking carefully about whether it can be split up. A sub-function creates an overview. This heuristic is easier to apply than formal complexity models, where you first have to identify nodes and edges in the code.

Reviews and joint reviews also help. A four-eyes principle or a review by the whole team uncovers optimizations. Fixed refactoring days, such as one or two days specifically for code improvement, have been proven to reduce complexity.

Where AI realistically supports BDD today

AI can assist with BDD, but it cannot replace human testing. There are plugins that make suggestions during testing, such as predictions based on data.

One concrete approach: predictions can be derived from the history of a test, i.e. how often it was successful or failed. If a developer pushes code into the repository, the aim is to predict which errors this code could trigger and which tests could fail.

It is also conceivable that AI will suggest Given-When-Then structures in the future. The real work will then be checking: does the proposal fit, does it meet expectations, are small adjustments necessary? This will come as an aid, but not as a replacement for those involved for the time being.