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While Genetic Improvement (GI) is a useful paradigm to improve functional and nonfunctional aspects of software, existing techniques tended to use the same set of mutation operators for differing objectives, due to the difficulty of writing custom mutation operators.
W. Weimer, T. Nguyen, C. L. Goues, and S. Forrest, “Automatically finding patches using genetic programming,” in Proceedings of the 31st IEEE International Conference on Software Engineering (ICSE ’09) . Vancouver, Canada: IEEE, 16-24 May 2009, pp. 364–374
2009
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W. B. Langdon and M. Harman, “Genetically improving 50,000 lines of C++,” Department of Computer Science, University College London, Tech. Rep. RN/12/09, 2012
2012
Earlier work this paper cites.
A. Hindle, E. T. Barr, Z. Su, M. Gabel, and P. Devanbu, “On the naturalness of software,” in Proceedings of the 34th International Conference on Software Engineering , ser. ICSE ’12. Piscataway, NJ, USA: IEEE Press, 2012, pp. 837–847
2012
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J. Petke, W. B. Langdon, and M. Harman, “Applying genetic improvement to minisat,” in International Symposium on Search Based Software Engineering . Springer, 2013, pp. 257–262
2013
Earlier work this paper cites.
J. Petke, M. Harman, W. B. Langdon, and W. Weimer, “Using genetic improvement and code transplants to specialise a C++ program to a problem class,” in 17th European Conference on Genetic Programming , ser. LNCS, M. Nicolau, K. Krawiec, M. I. Heywood, M. Castelli, P. Garcia-Sanchez, J. J. Merelo, V. M. Rivas Santos, and K. Sim, Eds., vol. 8599. Springer, 2014, pp. 137–149
2014
Cited alongside, same era.
B. R. Bruce, J. Petke, and M. Harman, “Reducing energy consumption using genetic improvement,” in Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation , ser. GECCO ’15. New York, NY, USA: ACM, 2015, pp. 1327–1334. [Online]. Available: http://doi.acm.org/10.1145/2739480.2754752
2015
Cited alongside, same era.
S. O. Haraldsson, J. R. Woodward, A. E. I. Brownlee, and K. Siggeirsdottir, “Fixing bugs in your sleep: How genetic improvement became an overnight success,” in Proceedings of the Genetic and Evolutionary Computation Conference Companion , ser. GECCO ’17. New York, NY, USA: ACM, 2017, pp. 1513–1520
2017
Cited alongside, same era.
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal et al. , “Language models are few-shot learners,” Advances in neural information processing systems , vol. 33, pp. 1877–1901, 2020
2020
Later among the works it cites.
2021
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A. Sarkar, A. Gordon, C. Negreanu, C. Poelitz, S. Srinivasa Ragavan, and B. Zorn, “What is it like to program with artificial intelligence?” 08 2022
2022
Later among the works it cites.
E. R. Winter, V. Nowack, D. Bowes, S. Counsell, T. Hall, S. Haraldsson et al. , “Towards developer-centered automatic program repair: Findings from bloomberg,” in Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering , ser. ESEC/FSE 2022. New York, NY, USA: ACM, 2022, pp. 1578–1588
2022
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J. Petke, S. Haraldsson, M. Harman, w. langdon, D. White, and J. Woodward, “Genetic improvement of software: a comprehensive survey,” IEEE Transactions on Evolutionary Computation , vol. 22, no. 3, pp. 415–432, 2018
2018
Cited alongside, same era.
Later among the works it cites.