Evaluating GPT's Programming Capability Through CodeWars' Katas

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Author(s)
Zhang, Zizhuo
Wen, Lian
Zhang, Shaoyang
Chen, David
Jiang, Yanfei
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Cao, C

Chen, H

Zhao, L

Arshad, J

Asyhari, T

Wang, Y

Date
2024
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Birmingham, United Kingdom

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Abstract

Understanding the capabilities and limitations of programming-oriented AI models is crucial. This paper evaluates the programming proficiency of GPT-3.5 and GPT-4 using Codewars coding problems of varying difficulty. The experiments reveal a distinct boundary at the 3kyu level, beyond which these models struggle. This led to proposing a complexity measure that includes problem difficulty and solution time. The research emphasizes the need for validation and creative thinking in AI models to better emulate human problem-solving. Future work aims to refine the complexity measure, enhance AI capabilities, and develop an objective programming problem difficulty measure. These insights are valuable for advancing AI programming and problem-solving abilities.

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Knowledge Science, Engineering and Management: 17th International Conference, KSEM 2024, Birmingham, UK, August 16–18, 2024, Proceedings, Part V

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14888

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This work is covered by copyright. You must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a specified licence, refer to the licence for details of permitted re-use. If you believe that this work infringes copyright please make a copyright takedown request using the form at https://www.griffith.edu.au/copyright-matters.

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Information and computing sciences

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Zhang, Z; Wen, L; Zhang, S; Chen, D; Jiang, Y, Evaluating GPT's Programming Capability Through CodeWars' Katas, Knowledge Science, Engineering and Management: 17th International Conference, KSEM 2024, Birmingham, UK, August 16–18, 2024, Proceedings, Part V, 2024, 14888, pp. 17-26