Attribute grammar paradigms—a high-level methodology in language implementation
ACM Computing Surveys (CSUR)
Stochastic Complexity in Statistical Inquiry Theory
Stochastic Complexity in Statistical Inquiry Theory
Semi-automatic grammar recovery
Software—Practice & Experience
Learning Context-Free Grammars with a Simplicity Bias
ECML '00 Proceedings of the 11th European Conference on Machine Learning
Regular Grammatical Inference from Positive and Negative Samples by Genetic Search: the GIG Method
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
When and how to develop domain-specific languages
ACM Computing Surveys (CSUR)
Unsupervised Learning of Probabilistic Context-Free Grammar using Iterative Biclustering
ICGI '08 Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications
AN UNSUPERVISED INCREMENTAL LEARNING ALGORITHM FOR DOMAIN-SPECIFIC LANGUAGE DEVELOPMENT
Applied Artificial Intelligence
An Introduction to Kolmogorov Complexity and Its Applications
An Introduction to Kolmogorov Complexity and Its Applications
Identifying hierarchical structure in sequences: a linear-time algorithm
Journal of Artificial Intelligence Research
Grammatical Inference: Learning Automata and Grammars
Grammatical Inference: Learning Automata and Grammars
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Context Free Grammars (CFGs) are widely used in programming language descriptions, natural language processing, compilers, and other areas of software engineering where there is a need for describing the syntactic structures of programs. Grammar inference (GI) is the induction of CFGs from sample programs and is a challenging problem. We describe an unsupervised GI approach which uses simplicity as the criterion for directing the inference process and beam search for moving from a complex to a simpler grammar. We use several operators to modify a grammar and use the Minimum Description Length (MDL) Principle to favor simple and compact grammars. The effectiveness of this approach is shown by a case study of a domain specific language. The experimental results show that an accurate grammar can be inferred in a reasonable amount of time.