Generating Annotated Behavior Models from End-User Scenarios

Abstract — Requirements-related scenarios capture typical examples of system behaviors through sequences of desired interactions between the software-to-be and its environment. Their concrete, narrative style of expression makes them very effective for eliciting software requirements and for validating behavior models. However, scenarios raise coverage problems as they only capture partial histories of interaction among system component instances. Moreover, they often leave the actual requirements implicit. Numerous efforts have therefore been made recently to synthesize requirements or behavior models inductively from scenarios. Two problems arise from those efforts. On the one hand, the scenarios must be complemented with additional input such as state assertions along episodes or flowcharts on such episodes. This makes such techniques difficult to use by the non-expert end-users who provide the scenarios. On the other hand, the generated state machines may be hard to understand as their nodes generally convey no domain-specific properties. Their validation by analysts, complementary to model checking and animation by tools, may therefore be quite difficult. This paper describes tool-supported techniques that overcome those two problems. Our tool generates a labeled transition system (LTS) for each system component from simple forms of message sequence charts (MSC) taken as examples or counter-examples of desired behavior. No additional input is required. A global LTS for the entire system is synthesized first. This LTS covers all scenario examples and excludes all counter-examples. It is inductively generated through an interactive procedure that extends known learning techniques for grammar induction. The procedure is incremental on training examples. It interactively produce