Dynamic UML models like sequence diagrams (SD) lack sufficient formal semantics, making it difficult to build automated tools for their analysis, simulation and validation. A common approach to circumvent the problem is to map these models to more formal representations. In this context, many works propose a rule-based approach to automatically translate SD into colored Petri nets (CPN). However, finding the rules for such SD-to-CPN transformations may be difficult, as the transformation rules are sometimes difficult to define and the produced CPN may be subject to state explosion. We propose a solution that starts from the hypothesis that examples of good transformation traces of SD-to-CPN can be useful to generate the target model. To this end, we describe an automated SD-to-CPN transformation method which finds the combination of transformation fragments that best covers the SD model, using heuristic search in a base of examples. To achieve our goal, we combine two algorithms for gl...
Marouane Kessentini, Arbi Bouchoucha, Houari A. Sa