Beyond "What to Retrieve": Uncertainty in Retrieval-Augmented Code Generation

2026-07-29T08:51:39Z54a95db5012a75c0b951f9b5cf85004dd96c07565f1431dc53903cae89f07488
AI-assisted codingDevOpsDockerJavaScriptLLMagent skillsautomated bug findingcode generationcontainer securitydeployment securitydeveloper editsformal verificationnetwork segmentationrepository contextretrieval-augmented generationsecrets managementsecurity requirementssoftware engineeringsupply-chain securitytraceability

What happened

A collection of newly published software-engineering research covering uncertainty-aware retrieval for code generation, JavaScript testability, GenAI-assisted literature reviews, agent skill authoring, developer edits of AI-generated code, specification-driven DevOps, NFR-to-code traceability, autonomous formal verification, and repository-context systems for coding agents. Security-relevant findings include deployment-intent gaps in LLM-generated configurations, difficulty tracing security requirements to implementation, third-party agent-skill trust concerns, and automated discovery of bugs,

Why it matters

A reviewed impact interpretation has not been published for this record.

Evidence and limitations

Source ID
arxiv_cs_se
Record identifier
54a95db5012a75c0b951f9b5cf85004dd96c07565f1431dc53903cae89f07488
Enrichment time
2026-07-29T08:51:39Z
AI-assisted enrichment
Yes

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Record · Beyond "What to Retrieve": Uncertainty in Retrieval-Augmented Code Generation · Baitaphish