Assessing LLM code generation quality through path planning tasks
April 30, 2025 Β· Declared Dead Β· π arXiv.org
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Authors
Wanyi Chen, Meng-Wen Su, Mary L. Cummings
arXiv ID
2504.21276
Category
cs.SE: Software Engineering
Cross-listed
cs.AI
Citations
1
Venue
arXiv.org
Last Checked
5 months ago
Abstract
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.
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