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Can You Improve My Code? Optimizing Programs with Local Search

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arxiv 2307.05603 v1 pith:RALGPDZP submitted 2023-07-10 cs.SE cs.LGcs.PL

classification cs.SEcs.LGcs.PL
keywords polisprogramexistingimproveprogramssearchcodeimproving
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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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Cited by 1 Pith paper

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  1. Learning Game-Playing Agents with Generative Code Optimization

    cs.LG 2025-08 conditional novelty 5.0 of 10

    LLM-guided refinement of Python policies reaches competitive Atari scores with fewer environment interactions than standard deep RL, on Pong, Breakout, and Space Invaders.

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