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- W2151184870 abstract "With the increasing use of models for software development and the emergence of model-driven engineering, it has become important to build accurate and precise models that present certain characteristics. Model transformation testing is a domain that requires generating a large number of models that satisfy coverage properties (cover the code of the transformation or the structure of the metamodel). However, manually building a set of models to test a transformation is a tedious task and having an automatic technique to generate models from a metamodel would be very helpful. We investigate the synthesis of models based on plans. Each plan comprises of a sequence of model synthesis rules (or mutation operators) specified as Graph Grammar (GG) rules. These mutation operators are primitive GG rules , automatically obtained from any meta-model. Such plans can be evolved by various artificial intelligence techniques to generate useful models for different tasks including model transformation testing." @default.
- W2151184870 created "2016-06-24" @default.
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- W2151184870 date "2006-11-01" @default.
- W2151184870 modified "2023-10-05" @default.
- W2151184870 title "Mutation-based Model Synthesis in Model Driven Engineering" @default.
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- W2151184870 doi "https://doi.org/10.1109/mutation.2006.12" @default.
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