Automatic generation of regular expressions from examples with genetic programming

  • Authors:
  • Alberto Bartoli;Giorgio Davanzo;Andrea De Lorenzo;Marco Mauri;Eric Medvet;Enrico Sorio

  • Affiliations:
  • DI3, University of Trieste, Italy, Trieste, Italy;DI3, University of Trieste, Italy, Trieste, Italy;DI3, University of Trieste, Trieste, Italy;DI3, University of Trieste, Italy, Trieste, Italy;DI3, University of Trieste, Italy, Trieste, Italy;DI3, University of Trieste, Italy, Trieste, Italy

  • Venue:
  • Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
  • Year:
  • 2012

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Abstract

We explore the practical feasibility of a system based on genetic programming (GP) for the automatic generation of regular expressions. The user describes the desired task by providing a set of labeled examples, in the form of text lines. The system uses these examples for driving the evolutionary search towards a regular expression suitable for the specified task. Usage of the system should require neither familiarity with GP nor with regular expressions syntax. In our GP implementation each individual represents a syntactically correct regular expression. We performed an experimental evaluation on two different extraction tasks applied to real-world datasets and obtained promising results in terms of precision and recall, even in comparison to an earlier state-of-the-art proposal.