Requirements Specification-by-Example Using a Multi-objective Evolutionary Algorithm

A task at the beginning of the software development process is the creation of a requirements specification. The requirements specification is usually created by a software engineering expert. We try to substitute this expert by a domain expert (the user) and formulate the problem of creating requirements specifications as a search-based software engineering problem. The domain expert provides only examples of event sequences that describe the behavior of the required software program. These examples are represented by simple sequence diagrams and are divided into two subsets: positive examples of required program behavior and negative examples of prohibited program behavior. The task is then to synthesize a generalized requirements specification that usefully describes the required software. We approach this problem by applying a genetic algorithm and evolve deterministic finite automata (DFAs). These DFAs take the sequence diagrams as input that should be either accepted (positive example) or rejected (negative example). The problem is neither to find the minimal nor the most general automaton. Instead, the user should be provided with several appropriate automata from which the user can select, or which help the user to refine the examples given initially. We present the context of our research ("On-The-Fly Computing"), present our approach, report results indicating its feasibility, and conclude with a discussion.