Software-intensive systems often consist of multiple components that interact to realize complex requirements. An additional dimension of complexity arises when one designs many variants of a system at once, that is, a software product line (SPL). We propose a scenario-based approach to design SPLs, based on a combination of Modal Sequence Diagrams (MSDs) and a feature model. It consists in associating every MSD to the set of variants that have to satisfy its specification. Variability constitutes a new source of complexity, which can lead to inconsistencies in the specification of one or multiple variants. It is therefore crucial to detect these inconsistencies, and to produce a controller for each variant that makes it behave so that it satisfies its specification. We present a new controller synthesis technique that checks the absence of inconsistencies in all variants at once, thereby more radically exploiting the similarities between them. Our method first translates the MSD specification into a variability-aware Büchi game, and then solves this game for all variants in a single execution. We implemented the approach in ScenarioTools, a software tool which we use to evaluate our algorithms against competing methods.

Many software-intensive systems consist of components that interact to fulfill complex functionality. Moreover, often many variants of such systems have to be designed at once. This adds complexity to the design task. Recently, we proposed a scenario-based approach to design product lines, which combines feature diagrams and Modal Sequence Diagrams. We proposed a consistency-checking technique based on a dedicated product line model checker. One limitation of this technique is that it is incomplete, i.e., it may fail to show the consistency of some consistent specifications. In this paper we propose a new game-based approach that overcomes this incompleteness and, in addition, automatically synthesizes controllers for the consistent product specifications. We exploit the fact that many variants are similar and efficiently synthesize product controllers incrementally. We provide a prototype tool and evaluate the efficiency of the approach.