Can You Improve My Code? Optimizing Programs with Local Search

Fatemeh Abdollahi; Saqib Ameen; Matthew E. Taylor; Levi H. S. Lelis

IJCAI 2023poster0 citations

Can You Improve My Code? Optimizing Programs with Local Search

Fatemeh Abdollahi, Saqib Ameen, Matthew E. Taylor, Levi H. S. Lelis

Abstract

This paper introduces a local search method for improving an existing program with respect to a measurable objective. Program Optimization with Locally Improving Search (POLIS) exploits the structure of a program, defined by its lines. POLIS improves a single line of the program while keeping the remaining lines fixed, using existing brute-force synthesis algorithms, and continues iterating until it is unable to improve the program's performance. POLIS was evaluated with a 27-person user study, where participants wrote programs attempting to maximize the score of two single-agent games: Lunar Lander and Highway. POLIS was able to substantially improve the participants' programs with respect to the game scores. A proof-of-concept demonstration on existing Stack Overflow code measures applicability in real-world problems. These results suggest that POLIS could be used as a helpful programming assistant for programming problems with measurable objectives.

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BibTeX

@inproceedings{ijcai2023p328,
  title     = {Can You Improve My Code? Optimizing Programs with Local Search},
  author    = {Abdollahi, Fatemeh and Ameen, Saqib and Taylor, Matthew E. and Lelis, Levi H. S.},
  booktitle = {Proceedings of the Thirty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-23}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Edith Elkind},
  pages     = {2940--2948},
  year      = {2023},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2023/328},
  url       = {https://doi.org/10.24963/ijcai.2023/328},
}