Corpus ID: 46893130

Bayesian Inference of Regular Expressions from Human-Generated Example Strings

@article{Ouyang2018BayesianIO,
  title={Bayesian Inference of Regular Expressions from Human-Generated Example Strings},
  author={L. Ouyang},
  journal={ArXiv},
  year={2018},
  volume={abs/1805.08427}
}
In programming by example, users "write" programs by generating a small number of input-output examples and asking the computer to synthesize consistent programs. We consider a challenging problem in this domain: learning regular expressions (regexes) from positive and negative example strings. This problem is challenging, as (1) user-generated examples may not be informative enough to sufficiently constrain the hypothesis space, and (2) even if user-generated examples are in principle… Expand
1 Citations
Bootstrapping Automated Testing for RESTful Web Services

References

SHOWING 1-10 OF 18 REFERENCES
Grammatical Inference: Learning Automata and Grammars
Bayesian Grammar Induction for Language Modeling
Bayesian learning of probabilistic language models
Using Semantic Unification to Generate Regular Expressions from Natural Language
Inference of Regular Expressions for Text Extraction from Examples
Learning Semantic String Transformations from Examples
Automating string processing in spreadsheets using input-output examples
Colin de la Higuera: Grammatical inference: learning automata and grammars
...
1
2
...