What Is BDD?

Behavior-Driven Development (BDD) is a refinement of Test-Driven-Development (TDD) which includes additional stakeholders in the development process. BDD centers on specifying and verifying software behaviors through collaborative, human-readable scenarios. Developers, testers, and stakeholders write these scenarios in plain language, which then drive the code implementation. This approach prioritizes observable outcomes and user interactions over internal code structure.

Regardless of the size of your team and what you are working on, I believe that BDD is currently one of the most effective ways to write software.

Note that it's recommended that you have a good understanding of how TDD works in order to get the most out of this post. If you are unfamiliar with TDD, check out my post on TDD first.

Collaboration: Involving Stakeholders Early

Collaboration transforms software development from an isolated technical exercise into a shared, transparent process. BDD formalizes this collaboration through structured conversations that happen before any code is written. These conversations bring together developers, testers, product owners, and other stakeholders to discuss how the system should behave in specific situations.

The core mechanism is simple: teams discuss concrete examples of system behavior rather than abstract requirements. Instead of saying "the checkout should handle discounts," stakeholders talk through specific scenarios like "when a customer applies a 20% off coupon to a $50 item, the final price should be $40." This shift from documentation to dialogue uncovers ambiguities, conflicting expectations, and edge cases that would otherwise surface later as bugs.

Ubiquitous Language

Ubiquitous Language is the shared vocabulary that a team develops and uses consistently throughout a project. It emerges from the collaborative conversations between developers, testers, and stakeholders, and it becomes the bridge between technical and non-technical team members. Unlike jargon that isolates different roles, Ubiquitous Language is deliberately chosen to be understandable to everyone involved in the project.

The key principle is that once a term is defined during these discussions, the entire team uses it exclusively in code, documentation, and conversation. If the team agrees to call a promotional code a "coupon" rather than a "discount token" or "promo," that term appears in scenario steps, in variable names, in database columns, and in user-facing text. This consistency eliminates the mental translation overhead that occurs when different people use different words for the same concept.

Developing Ubiquitous Language requires deliberate effort. Teams should actively challenge vague or ambiguous terms during scenario writing. When someone says "the system should handle the discount properly," the response should be "what does 'properly' mean in concrete terms?" This insistence on clarity during conversations naturally produces the precise, shared vocabulary that makes scenarios meaningful.

Scenarios

A scenario is a concrete example of how the system should behave in a specific situation. It takes the abstract requirements from a user story and transforms them into something tangible that everyone on the team can visualize and discuss. Scenarios answer the question: "What exactly should happen here?"

Good scenarios share certain characteristics. They are specific enough to guide implementation but general enough to capture a reusable pattern of behavior. They focus on the observable behavior of the system rather than its internal implementation. Each scenario describes one distinct path through the functionality, which keeps them focused and makes them easier to test.

Consider a simple example from an e-commerce application. A user story might state: "As a shopper, I want to apply discount codes so that I can save money on my purchase." This statement is too vague to drive implementation. A well-written scenario makes the behavior explicit:

Feature: Applying Discounts
  Scenario: Applying a valid percentage discount
    Given the shopping cart contains a $50 item
    And the customer has a valid 20% off coupon
    When the customer applies the coupon to the cart
    Then the cart total should be $40

This scenario tells us exactly what should happen in one specific case. Notice how it avoids discussing implementation details like database queries, API calls, or how the discount is stored. It describes behavior purely in terms of inputs and observable outputs.

BDD encourages teams to write multiple scenarios for each feature, covering both the happy path and edge cases. Another scenario for the same feature might address what happens when the coupon is expired or when the discount exceeds a maximum amount. Each scenario becomes a small specification that drives one piece of the implementation.

Making Scenarios Executable: Step Definitions

Scenarios written in Gherkin syntax are human-readable by design, but they serve a dual purpose: they must also drive automated tests. This translation from plain language to executable code happens through step definitions, which are the implementation bridge between the descriptive scenario text and the actual behavior of your system.

A step definition is a small piece of code that connects a specific step in a scenario to the actions or assertions that actually execute in your application. When the test runner encounters a line like "Given the shopping cart contains a $50 item," it looks for a step definition that matches that pattern and runs the code to perform an action. Each line in a scenario has a corresponding step definition.

Implementing Step Definitions in Rust

How do plain English scenarios become code? In Rust, we can use the cucumber crate which will allow us to easily write step definitions.

First we need to define the World, which represents the application and any state required for a feature:

use cucumber::{World as _};

#[derive(Debug, Default, cucumber::World)]
struct World {
    cart_total: f64,
    coupon_discount: Option<f64>,
}

Next we write the step definitions. Each function parses either a Given, When, or Then line. I added code comments above each function showing which scenario line is being parsed:

use cucumber::{given, then, when};

// Parse: Given the shopping cart contains a $50 item
#[given(expr = "the shopping cart contains a ${float} item")]
async fn cart_contains_item(w: &mut World, price: f64) {
    w.cart_total += price;
}

// Parse: And the customer has a valid 20% off coupon
#[given(expr = "the customer has a valid {int}% off coupon")]
async fn customer_has_coupon(w: &mut World, percent: u32) {
    w.coupon_discount = Some(percent as f64 / 100.0);
}

// Parse: When the customer applies the coupon to the cart
#[when(expr = "the customer applies the coupon to the cart")]
async fn apply_coupon(w: &mut World) {
    if let Some(discount) = w.coupon_discount {
        w.cart_total *= 1.0 - discount;
    }
}

// Parse: Then the cart total should be $40
#[then(expr = "the cart total should be ${float}")]
async fn cart_total_equals(w: &mut World, expected: f64) {
    approx_eq!(f64, w.cart_total, expected, ulps = 2);
}

Finally, we add the test runner so it works with cargo test:

#[tokio::main]
async fn main() {
    World::run("tests/features/cart.feature").await;
}

In a more complete implementation, the World would contain either the entire system or a large subsystem, like this:

use cucumber::{World as _};

#[derive(Debug, Default, cucumber::World)]
struct World {
    shop: Shop,
}

And then in each step definition you'd make the public calls to the Shop for adding items to the cart along with applying coupon codes and checking the total.

Benefits of BDD Over TDD Alone

TDD provides a powerful discipline for writing well-tested code, but it has a significant limitation: the tests exist only in the developer's world. BDD extends TDD by adding a layer of communication and documentation that bridges the gap between technical implementation and business requirements.

1. Living Documentation

Traditional unit tests serve as documentation for developers, but they are poor documentation for non-technical stakeholders. The scenarios written in Gherkin serve a dual purpose: they describe system behavior in language everyone can understand, and they are executable specifications that verify the system actually behaves that way.

This is "living documentation" that never falls out of sync with the implementation because it is the implementation's test suite. When a stakeholder wants to know how a discount is calculated, they can read the scenario and see exactly what the expected behavior is. When the implementation changes, the test either passes or fails, immediately revealing whether the documentation is still accurate.

In contrast, traditional TDD tests document implementation choices rather than business behavior. A test named apply_twenty_percent_discount_to_fifty_dollar_item tells you nothing about why the discount exists or what business problem it solves.

2. Earlier Discovery of Ambiguity

BDD shifts the ambiguity-discovery phase earlier in the development process. In pure TDD, ambiguity in requirements often surfaces when a developer writes a test and realizes they don't know what the expected behavior should be. At this point, the developer must interrupt their flow to seek clarification, or worse, make assumptions.

BDD surfaces these ambiguities during the collaborative scenario-writing phase, before any code or tests exist. When a team discusses concrete examples of how a feature should work, missing requirements and edge cases emerge naturally through the act of creating specific scenarios. The cost of correcting a misunderstanding is lowest at this stage, before implementation time has been invested.

3. Behavior-Focused Design

TDD encourages developers to think about code structure first, then test that structure. BDD inverts this by requiring you to describe observable behavior first. This shift matters because it keeps the focus on what the system should do rather than how it should be built.

When you write a scenario like "When the customer applies the coupon to the cart, the cart total should be $40," you are specifying an interface that should be possible to implement. You can satisfy this scenario with a simple calculation, a complex pricing service, or an external API call. The scenario ignores implementation and only cares about behavior.

Common Pitfalls and How to Avoid Them

Even with its benefits, BDD can be practiced poorly. Recognizing incorrect implementation patterns early prevents frustration and wasted effort.

Scenarios That Describe Implementation Instead of Behavior

The most common mistake is writing scenarios that specify how something happens rather than what should happen. A scenario like this sacrifices the main advantage of BDD:

Scenario: Apply discount using database transaction
  Given the cart is stored in the database
  And the discount service calls the pricing engine via RPC
  When the customer applies the coupon
  Then the cart total should be $40

This scenario ties the test to implementation details that may change. If you refactor to store carts in memory or call the pricing engine directly, the scenario breaks even though the behavior is unchanged. The scenario should focus only on observable behavior:

Scenario: Applying a valid percentage discount
  Given the shopping cart contains a $100 item
  And the customer has a valid 20% off coupon
  When the customer applies the coupon to the cart
  Then the cart total should be $80

Notice the difference. The second version says nothing about databases, RPC calls, or service boundaries. It describes only inputs and outputs, making the scenario resilient to implementation changes.

Overly Vague or Abstract Scenarios

At the opposite extreme, scenarios that remain too abstract provide no guidance. Here is an example of a scenario that is too vague and lacks concrete details:

Scenario: Applying a discount
  Given a user applies a discount
  When the total is calculated
  Then the discount should be applied

This scenario tells you almost nothing about expected behavior. Effective scenarios require concrete values and specific conditions.

The solution is simple: the words "a," "the," "some," or "valid," in a scenario should be coupled or replaced with an actual value. Determine "what exactly is the value?" and "what does valid mean in this context?" These concrete examples are what make scenarios useful as specifications.

Treating Scenarios as One-Time Artifacts

Scenarios are not written once and forgotten. They are living documents that should evolve alongside the codebase. When requirements change, the scenarios must change first. When edge cases are discovered during implementation, they should be captured as new scenarios. When the team learns that certain terminology creates confusion, the scenarios should be updated to use clearer language.

A scenario that passes but no longer reflects current expectations is worse than no scenario at all as it provides false confidence. Review scenarios during iteration planning and retrospectives to ensure they remain accurate and valuable.

Solo Dev? Here's Your Workaround

You might be thinking that BDD's emphasis on collaboration makes it impractical for a solo developer. After all, if you are working alone, who do you collaborate with? The good news is that you already have a collaboration partner: your future self. The developer who returns to this code in six months will not remember the decisions you made today. The scenarios you write serve as a conversation with that future developer, clarifying intent and capturing edge cases that would otherwise be lost.

Writing scenarios before coding provides the same clarity benefits for a solo developer as it does for a team. When you force yourself to describe exactly what should happen in a specific situation, you expose gaps in your understanding before you write any implementation code. The discipline of choosing concrete values instead of abstract terms reveals ambiguities that you would have otherwise coded around with assumptions. A solo developer who writes scenarios is simply having this conversation with themselves rather than with teammates, but the cognitive benefits remain identical.

The practical workflow for a solo developer is straightforward. Before implementing a feature, open a new file in your tests/features directory and write the Gherkin scenarios that describe the behavior you want. Ask yourself: what are the concrete inputs and expected outputs? What happens in edge cases? What error conditions should the system handle? Write these scenarios as if you were explaining the feature to a non-technical stakeholder, then implement the step definitions to make them pass. Your future self will thank you when they can read the scenarios and understand exactly what the code is supposed to do without tracing through implementation details.

Another way to simulate collaboration is to pretend you are explaining the feature to someone from the support team or to a product manager. What questions would they ask? What concrete examples would they demand? This mental exercise produces scenarios that are clearer and more complete than what you might write in isolation. The scenarios become a proxy for the stakeholder conversations that drive BDD in team settings.

Recap

BDD brings structure and clarity to the development process by requiring you to articulate system behavior before implementation. The collaborative conversations that produce scenarios expose ambiguity early, create shared understanding across roles, and generate living documentation that evolves with your codebase. For individual developers, scenarios serve as a bridge between your current understanding and your future self, turning requirements into concrete examples that guide code and preserve context.

Where Gherkin Fits and Where TDD Excels

Not every test benefits from writing a scenario with Gherkin syntax. Understanding the appropriate scope for behavioral testing ensures you leverage each approach's strengths effectively.

Gherkin scenarios shine at integration and end-to-end boundaries where multiple components must work together correctly. These tests verify that your database interactions, API calls, and user workflows function as expected. They confirm system behavior without diving into implementation specifics, making them resilient to internal refactoring.

Unit testing, where TDD dominates, remains ideal for validating individual functions and modules in isolation. These tests execute quickly, provide immediate feedback during development, and specify precise contract behaviors for internal components. The fine-grained focus of unit tests catches bugs at the source before they propagate through the system.

Practical Guidance

Apply BDD's behavioral specification to features where stakeholder communication matters and system boundaries are involved. This includes end-to-end testing and integration tests. Use TDD's rapid feedback loop for algorithm implementation, data transformation logic, and component design (unit tests). Layer both strategies to combine BDD's communication benefits with TDD's design discipline.

Conclusion

BDD succeeds because it attacks the root cause of many software development failures: misalignment between what stakeholders want and what developers build. By requiring concrete examples before any code exists, it surfaces misunderstanding when correction costs the least. By demanding shared, precise language, it eliminates the silent translation errors that creep into projects when different people use the same words to mean different things.

BDD is not tied to any particular language or ecosystem. Whether you work in Python, Go, JavaScript, or anything else, the same principles apply. Write scenarios in plain language that anyone can read. Translate those scenarios into executable steps. Let those tests drive your implementation. The tools change but the discipline remains constant.

Starting with BDD does not require a perfect process or a full team. A single developer writing scenarios before code is already practicing BDD. The scenarios need not be elaborate or cover every edge case from day one. Start with one feature. Write one scenario with concrete values. Implement it. Expand from there as the approach proves its value.

The testing landscape offers many tools and techniques. BDD is not the only valid approach, and TDD remains excellent for many situations. What BDD offers is a bridge between technical implementation and human intent, a way to make your codebase explain what it does and why. For most software projects, that bridge is worth building.