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Exploring Fitness and Edit Distance of Mutated Python Programs

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Book cover Genetic Programming (EuroGP 2017)

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

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Abstract

Genetic Improvement (GI) is the process of using computational search techniques to improve existing software e.g. in terms of execution time, power consumption or correctness. As in most heuristic search algorithms, the search is guided by fitness with GI searching the space of program variants of the original software. The relationship between the program space and fitness is seldom simple and often quite difficult to analyse. This paper makes a preliminary analysis of GI’s fitness distance measure on program repair with three small Python programs. Each program undergoes incremental mutations while the change in fitness as measured by proportion of tests passed is monitored. We conclude that the fitnesses of these programs often does not change with single mutations and we also confirm the inherent discreteness of bug fixing fitness functions. Although our findings cannot be assumed to be general for other software they provide us with interesting directions for further investigation.

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Notes

  1. 1.

    Code blocks are defined by indentation in Python and not by {} as in JAVA/C.

  2. 2.

    The programs and their test suites are available on https://github.com/saemundo/Exploring-Fitness-and-Edit-Distance-of-Mutated-Python-Programs.git.

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Acknowledgements

The work presented in this paper is part of the DAASE project which is funded by the EPSRC. The authors would like to thank Janus Rehabilitation Centre for allowing the use of their software in the experiments and consequently making the relevant part of the source code available for others to use in their experiments.

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Authors and Affiliations

  1. University of Stirling, Stirling, FK9 4LA, Scotland

    Saemundur O. Haraldsson, John R. Woodward, Alexander E. I. Brownlee & David Cairns

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  1. Saemundur O. Haraldsson
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  2. John R. Woodward
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  3. Alexander E. I. Brownlee
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Correspondence to Saemundur O. Haraldsson .

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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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Haraldsson, S.O., Woodward, J.R., Brownlee, A.E.I., Cairns, D. (2017). Exploring Fitness and Edit Distance of Mutated Python Programs. 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_2

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