A graph solver for the automated generation of consistent domain-specific models

• Published in: 2018 IEEE/ACM 40th International Conference on Software Engineering (ICSE) pp. 969 - 980
• Main Authors: Semeráth, Oszkár, Nagy, András Szabolcs, Varró, Dániel
• Format: Conference Proceeding
• Language: English
• Published: New York, NY, USA ACM 27.05.2018
• Series: ACM Conferences
• Subjects: Analytical models; Biological system modeling; Domain Specific Modeling Languages; Graph generation; Graph Solver; IP networks; Logic Solver; Object oriented modeling; Test generation; Testing
• ISBN: 9781450356381; 1450356389
• ISSN: 1558-1225
• DOI: 10.1145/3180155.3180186

Many testing and benchmarking scenarios in software and systems engineering depend on the systematic generation of graph models. For instance, tool qualification necessitated by safety standards would require a large set of consistent (well-formed or malformed) instance models specific to a domain. However, automatically generating consistent graph models which comply with a metamodel and satisfy all well-formedness constraints of industrial domains is a significant challenge. Existing solutions which map graph models into first-order logic specification to use back-end logic solvers (like Alloy or Z3) have severe scalability issues. In the paper, we propose a graph solver framework for the automated generation of consistent domain-specific instance models which operates directly over graphs by combining advanced techniques such as refinement of partial models, shape analysis, incremental graph query evaluation, and rule-based design space exploration to provide a more efficient guidance. Our initial performance evaluation carried out in four domains demonstrates that our approach is able to generate models which are 1-2 orders of magnitude larger (with 500 to 6000 objects!) compared to mapping-based approaches natively using Alloy.