WebSynthesizing program input grammars @article{Bastani2016SynthesizingPI, title={Synthesizing program input grammars}, author={Osbert Bastani and Rahul Sharma and Alexander Aiken and Percy Liang}, journal={Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation}, year={2016} } O. … WebAug 12, 2024 · REINAM is able to synthesize a grammar covering the entire valid input space for some benchmarks without decreasing the accuracy of the grammar. Discover the world's research 20+ million...

Trustworthy Machine Learning Group

WebJun 13, 2024 · “Synthesizing input grammars”: a replication study Authors: Bachir Bendrissou Rahul Gopinath The University of Sydney Andreas Zeller 0 20 0 Learn more about stats on ResearchGate Figures... WebIt shows quite convincingly that neural program synthesis methods can infer grammars like the one used in SCAN from a relatively small amount of examples. ... their model is very similar to the standard approach for neural program synthesis from input-output examples, which typically assumes that the number of input-output examples is small, e ... frith and happe 1994

Improving Symbolic Automata Learning with Concolic Execution

WebWe present an algorithm for synthesizing a context-free grammar encoding the language of valid program inputs from a set of in-put examples and blackbox access to the program. … WebWe present an algorithm for synthesizing a context-free grammar encoding the language of valid program inputs from a set of input examples and blackbox access to the program. … WebWe present an algorithm for synthesizing a context-free grammar encoding the language of valid program inputs from a set of input examples and blackbox access to the program. Our algorithm addresses shortcomings of existing grammar inference algorithms, which both severely overgeneralize and are prohibitively slow. frith ave normanhurst