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European Conference on Genetic Programming

EuroGP 2017: Genetic Programming pp 3–18Cite as

Evolutionary Program Sketching

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10196))

Abstract

Program synthesis can be posed as a satisfiability problem and approached with generic SAT solvers. Only short programs can be however synthesized in this way. Program sketching by Solar-Lezama assumes that a human provides a partial program (sketch), and that synthesis takes place only within the uncompleted parts of that program. This allows synthesizing programs that are overall longer, while maintaining manageable computational effort. In this paper, we propose Evolutionary Program Sketching (EPS), in which the role of sketch provider is handed over to genetic programming (GP). A GP algorithm evolves a population of partial programs, which are being completed by a solver while evaluated. We consider several variants of EPS, which vary in program terminals used for completion (constants, variables, or both) and in the way the completion outcomes are propagated to future generations. When applied to a range of benchmarks, EPS outperforms the conventional GP, also when the latter is given similar time budget.

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Notes

  1. 1.

    Technically, the solver may also time-out, which we interpret as lack of feasible completion too.

  2. 2.

    http://smtlib.cs.uiowa.edu/logics.shtml.

  3. 3.

    https://github.com/iwob.

  4. 4.

    https://github.com/kkrawiec.

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Acknowledgments

This work was supported by grant 2014/15/B/ST6/05205 funded by the National Science Centre, Poland.

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Authors and Affiliations

  1. Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965, Poznań, Poland

    Iwo Błądek & Krzysztof Krawiec

Authors
  1. Iwo Błądek
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  2. Krzysztof Krawiec
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Correspondence to Iwo Błądek .

Editor information

Editors and Affiliations

  1. University College Dublin , Dublin, Ireland

    James McDermott

  2. Universidade Nova de Lisboa , Lisbon, Portugal

    Mauro Castelli

  3. Brno University of Technology , Brno, Czech Republic

    Lukas Sekanina

  4. Vrije Universiteit Amsterdam , Amsterdam, The Netherlands

    Evert Haasdijk

  5. University of Cádiz , Cádiz, Spain

    Pablo García-Sánchez

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Błądek, I., Krawiec, K. (2017). Evolutionary Program Sketching. In: McDermott, J., Castelli, M., Sekanina, L., Haasdijk, E., García-Sánchez, P. (eds) Genetic Programming. EuroGP 2017. Lecture Notes in Computer Science(), vol 10196. Springer, Cham. https://doi.org/10.1007/978-3-319-55696-3_1

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  • DOI: https://doi.org/10.1007/978-3-319-55696-3_1

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