Assessing LLM code generation quality through path planning tasks
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908343807770624 |
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| author | Chen, Wanyi Su, Meng-Wen Cummings, Mary L. |
| author_facet | Chen, Wanyi Su, Meng-Wen Cummings, Mary L. |
| contents | As LLM-generated code grows in popularity, more evaluation is needed to assess the risks of using such tools, especially for safety-critical applications such as path planning. Existing coding benchmarks are insufficient as they do not reflect the context and complexity of safety-critical applications. To this end, we assessed six LLMs' abilities to generate the code for three different path-planning algorithms and tested them on three maps of various difficulties. Our results suggest that LLM-generated code presents serious hazards for path planning applications and should not be applied in safety-critical contexts without rigorous testing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_21276 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Assessing LLM code generation quality through path planning tasks Chen, Wanyi Su, Meng-Wen Cummings, Mary L. Software Engineering Artificial Intelligence As LLM-generated code grows in popularity, more evaluation is needed to assess the risks of using such tools, especially for safety-critical applications such as path planning. Existing coding benchmarks are insufficient as they do not reflect the context and complexity of safety-critical applications. To this end, we assessed six LLMs' abilities to generate the code for three different path-planning algorithms and tested them on three maps of various difficulties. Our results suggest that LLM-generated code presents serious hazards for path planning applications and should not be applied in safety-critical contexts without rigorous testing. |
| title | Assessing LLM code generation quality through path planning tasks |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2504.21276 |