Enhancing Genetic Improvement Mutations Using Large Language Models
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-48796-5_13
Reference19 articles.
1. Artifact of Enhancing Genetic Improvement Mutations Using Large Language Models. Zenodo (2023). https://doi.org/10.5281/zenodo.8304433
2. Böhme, M., Soremekun, E.O., Chattopadhyay, S., Ugherughe, E., Zeller, A.: Where is the bug and how is it fixed? an experiment with practitioners. In: Proceedings of ACM Symposium on the Foundations of Software Engineering, pp. 117–128 (2017)
3. Brownlee, A.E., Petke, J., Alexander, B., Barr, E.T., Wagner, M., White, D.R.: Gin: genetic improvement research made easy. In: GECCO, pp. 985–993 (2019)
4. Brownlee, A.E., Petke, J., Rasburn, A.F.: Injecting shortcuts for faster running Java code. In: IEEE CEC 2020, pp. 1–8 (2020)
5. Chen, M., et al.: Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374 (2021)
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