Logic for problem-solving
Recent advances of grammatical inference
Theoretical Computer Science - Special issue on algorithmic learning theory
Logic-based genetic programming with definite clause translation grammars
New Generation Computing
Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
The Theory of Parsing, Translation, and Compiling
The Theory of Parsing, Translation, and Compiling
A Machine Learning Approach to Automatic Production of Compiler Heuristics
AIMSA '02 Proceedings of the 10th International Conference on Artificial Intelligence: Methodology, Systems, and Applications
Refining Complete Hypotheses in ILP
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Meta optimization: improving compiler heuristics with machine learning
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Incorporating linguistics constraints into inductive logic programming
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
An ILP Refinement Operator for Biological Grammar Learning
Inductive Logic Programming
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
Inferring grammar rules of programming language dialects
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
The tenjinno machine translation competition
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
Large scale inference of deterministic transductions: tenjinno problem 1
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
Incremental learning of cellular automata for parallel recognition of formal languages
DS'10 Proceedings of the 13th international conference on Discovery science
Gramin: a system for incremental learning of programming language grammars
Proceedings of the 4th India Software Engineering Conference
A memetic grammar inference algorithm for language learning
Applied Soft Computing
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This paper discusses machine learning of grammars and compilers of programming languages from samples of translation from source programs into object codes. This work is an application of incremental learning of definite clause grammars (DCGs) and syntax directed translation schema (SDTS), which is implemented in the Synapse system. The main experimental result is that Synapse synthesized a set of SDTS rules for translating extended arithmetic expressions with function calls and assignment operators into object codes from positive and negative samples of the translation. The object language is a simple intermediate language based on inverse Polish notation. These rules contain an unambiguous context free grammar for the extended arithmetic expressions, which specifies the precedence and associativity of the operators. This approach can be used for designing and implementing a new programming language by giving the syntax and semantics in the form of the samples of the translation.