LLM Code Smells: A Taxonomy and Detection Approach
arXiv 2605.22976•5689f3322f0b6d812ba42b6c6299c8a7d7e25820d647196629d31a3742a95c72
Branch-Flip-AnalysisKubernetesLLM-generated-codeLLM-securityQueryZenSpecDetect4LLMagent-breakageagentic-operationscode-smellsdatabase-performanceempirical-studysoftware-supply-chainstatic-analysistoolingvulnerability-assessment
Paper metadata
- arXiv ID
- 2605.22976
- Version
- Not specified by this published record
- Category
- Computer Science — Software Engineering (cs.SE)
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Evidence and limitations
- Source ID
- arxiv_cs_se
- Record identifier
- 5689f3322f0b6d812ba42b6c6299c8a7d7e25820d647196629d31a3742a95c72
- Enrichment time
- 2026-05-25T08:52:19Z
- AI-assisted enrichment
- Yes
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