Disjunction Composition of BDD Transition Systems for Model-Based Testing

2026-02-19

AI Summary

This work addresses a key challenge in behavior-driven development (BDD): how to compose alternative behavioral scenarios—expressed as BDD textual specifications—into integrated models for model-driven testing while preserving their original test capabilities. The authors propose a disjunctive composition approach that formalizes BDD scenarios as transition systems and defines their composition via symbolic semantics, ensuring that the resulting system is test-equivalent to the original scenarios with respect to failure behaviors. This is the first method to incorporate symbolic semantics into BDD scenario composition, providing a rigorous guarantee of test equivalence. Empirical evaluation on industrial case studies demonstrates the approach’s effectiveness, confirming that it accurately models integrated system behavior without compromising the original testing power.

Technology Category

• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Web Mining and Content Analysis: Models for Web evolution
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

We introduce a compositional approach to model-based test generation in Behavior-Driven Development (BDD). BDD is an agile methodology in which system behavior is specified through textual scenarios that, in our approach, are translated into transition systems used for model-based testing. This paper formally defines disjunction composition, to combine BDD transition systems that represent alternative system behaviors. Disjunction composition allows for modeling and testing the integrated behavior while ensuring that the testing power of the original set of scenarios is preserved. This is proved using a symbolic semantics for BDD transition systems, with the property that the symbolic equivalence of two BDD transition systems guarantees that they fail the same test cases. Also, we demonstrate the potential of disjunction composition by applying the composition in an industrial case study.

Problem

• disjunction composition
• BDD transition systems
• model-based testing
• Behavior-Driven Development
• test generation

Innovation

• disjunction composition
• BDD transition systems
• model-based testing
• symbolic semantics
• Behavior-Driven Development