Improving Grammar Inference by a Memetic Algorithm

A memetic algorithm, a novel approach for solving NP-hard problems, has been applied in this paper for grammatical inference in the field of domain-specific languages (DSLs). DSLs are often designed by domain experts who have no knowledge about the syntax and semantics of programming languages. However, they are able to write sample programs to accomplish their goals and illustrate the features of their language. Grammatical inference is a technique to infer a context-free grammar from a set of positive (and negative) samples. This paper shows that grammatical inference may assist domain experts and software language engineers in developing DSLs by automatically producing a grammar, which describes a set of sample DSL programs. A memetic-algorithm-based tool is developed, which greatly improves results and robustness of the inference process.