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Genetic improvement: taking real-world source code and improving it using genetic programming

Published:08 July 2020Publication History
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References

  1. S.O. Haraldsson, John R. Woodward, Alexander E. I. Brownlee, and Kristin Siggeirsdottir. 2017. Fixing bugs in your sleep: how genetic improvement became an overnight success. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '17). ACM, New York, NY, USA, 1513--1520. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. S. O. Haraldsson, J. R. Woodward and A. I. E. Brownlee, "The Use of Automatic Test Data Generation for Genetic Improvement in a Live System," 2017 IEEE/ACM 10th International Workshop on Search-Based Software Testing (SBST), Buenos Aires, 2017, pp. 28--31. Google ScholarGoogle ScholarCross RefCross Ref
  3. S.O. Haraldsson, 2017. 'Genetic Improvement of Software: From Program Landscapes to the Automatic Improvement of a Live System', PhD thesis, University of Stirling, Stirling. http://hdl.handle.net/1893/26007Google ScholarGoogle Scholar
  4. S.O. Haraldsson, John R. Woodward, Alexander E. I. Brownlee, Albert V. Smith, and Vilmundur Gudnason. 2017. Genetic improvement of runtime and its fitness landscape in a bioinformatics application. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '17). ACM, New York, NY, USA, 1521--1528. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. S.O. Haraldsson, 2017. 'Genetic Improvement of Software: From Program Landscapes to the Automatic Improvement of a Live System', PhD thesis, University of Stirling, Stirling. http://hdl.handle.net/1893/26007Google ScholarGoogle Scholar
  6. S. O. Haraldsson, R. D. Brynjolfsdottir, J. R. Woodward, K. Siggeirsdottir and V. Gudnason, "The use of predictive models in dynamic treatment planning," 2017 IEEE Symposium on Computers and Communications (ISCC), Heraklion, 2017, pp. 242--247. Google ScholarGoogle ScholarCross RefCross Ref
  7. S. O. Haraldsson, R. D. Brynjolfsdottir, V. Gudnason, K. Tomasson and K. Siggeirsdottir, "Predicting changes in quality of life for patients in vocational rehabilitation," 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), Rhodes, 2018, pp. 1--8. Google ScholarGoogle ScholarCross RefCross Ref
  8. Siggeirsdottir, K., Brynjolfsdottir, R.D., Haraldsson, S.O., Vidar, S., Gudmundsson, E.G., Brynjolfsson, J.H., Jonsson, H., Hjaltason, O. and Gudnason, V., 2016. Determinants of outcome of vocational rehabilitation. Work, 55(3), pp.577--583. Google ScholarGoogle ScholarCross RefCross Ref
  9. J. Petke, B. Alexander, E.T. Barr, A.E.I. Brownlee, M. Wagner, and D.R. White, 2019. 'A survey of genetic improvement search spaces'. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '19). ACM, New York, NY, USA, 1715--1721. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. A.E.I. Brownlee, J. Petke, B. Alexander, E.T. Barr, M. Wagner, and D.R. White, 2019. 'Gin: genetic improvement research made easy'. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '19). ACM, New York, NY, USA, 985--993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. M.A. Bokhari, B. Alexander, and M. Wagner, 2019. 'In-vivo and offline optimisation of energy use in the presence of small energy signals: A case study on a popular Android library'. In Proceedings of the EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous '18), ACM, New York, NY, USA, 207--215. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. M.A. Bokhari, B. Alexander, and M. Wagner, 2020. 'Towards Rigorous Validation of Energy Optimisation Experiments'. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '20). ACM, New York, NY, USA. URL: https://arxiv.org/abs/2004.04500v1Google ScholarGoogle Scholar
  13. M.A. Bokhari, B.R. Bruce, B. Alexander, and M. Wagner, 2017. 'Deep parameter optimisation on Android smartphones for energy minimisation: a tale of woe and a proof-of-concept'. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '17). ACM, New York, NY, USA, 1501--1508. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. M.A. Bokhari, L. Weng, M. Wagner, and B. Alexander, 2019. 'Mind the gap - a distributed framework for enabling energy optimisation on modern smart-phones in the presence of noise, drift, and statistical insignificance'. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC '19). IEEE, 1330--1337. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. A. Agrawal, T. Menzies, L. Minku, M. Wagner, and Z. Yu, 2020. 'Better software analytics via "DUO": Data mining algorithms using/used-by optimizers'. Empirical Software Engineering, Springer. Published 22 April 2020. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. V. Nair, A. Agrawal, J. Chen, W. Fu, G. Mathew, T. Menzies, L. Minku, M. Wagner, and Z. Yu, 2018. 'Data-driven search-based software engineering'. In Proceedings of the International Conference on Mining Software Repositories (MSR '18), ACM, New York, NY, USA, 341--352. Google ScholarGoogle ScholarDigital LibraryDigital Library

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          cover image ACM Conferences
          GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion
          July 2020
          1982 pages
          ISBN:9781450371278
          DOI:10.1145/3377929

          Copyright © 2020 Owner/Author

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          • Published: 8 July 2020

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