Iterative and Incremental Model Generation by Logic Solvers

• Published in: Fundamental Approaches to Software Engineering pp. 87 - 103
• Main Authors: Semeráth, Oszkár, Vörös, András, Varró, Dániel
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2016
• Series: Lecture Notes in Computer Science
• Subjects: Domain-specific languages; Logic solvers; Model generation
• ISBN: 9783662496640; 366249664X
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-662-49665-7_6

The generation of sample instance models of Domain-Specific Language (DSL) specifications has become an active research line due to its increasing industrial relevance for engineering complex modeling tools by using large metamodels and complex well-formedness constraints. However, the synthesis of large, well-formed and realistic models is still a major challenge. In this paper, we propose an iterative process for generating valid instance models by calling existing logic solvers as black-box components using various approximations of metamodels and constraints to improve overall scalability. (1) First, we apply enhanced metamodel pruning and partial instance models to reduce the complexity of model generation subtasks and the retrieved partial solutions initiated in each step. (2) Then we propose an (over-)approximation technique for well-formedness constraints in order to interpret and evaluate them on partial (pruned) metamodels. (3) Finally, we define a workflow that incrementally generates a sequence of instance models by refining and extending partial models in multiple steps, where each step is an independent call to the underlying solver (the Alloy Analyzer in our experiments).