{"ID":2823091,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2601.01199","arxiv_id":"2601.01199","title":"Abductive Vibe Coding (Extended Abstract)","abstract":"When software artifacts are generated by AI models (\"vibe coding\"), human engineers assume responsibility for validating them. Ideally, this validation would be done through the creation of a formal proof of correctness. However, this is infeasible for many real-world vibe coding scenarios, especially when requirements for the AI-generated artifacts resist formalization. This extended abstract describes ongoing work towards the extraction of analyzable, semi-formal rationales for the adequacy of vibe-coded artifacts. Rather than deciding correctness directly, our framework produces a set of conditions under which the generated code can be considered adequate. We describe current efforts towards implementing our framework and anticipated research opportunities.","short_abstract":"When software artifacts are generated by AI models (\"vibe coding\"), human engineers assume responsibility for validating them. Ideally, this validation would be done through the creation of a formal proof of correctness. However, this is infeasible for many real-world vibe coding scenarios, especially when requirements...","url_abs":"https://arxiv.org/abs/2601.01199","url_pdf":"https://arxiv.org/pdf/2601.01199v1","authors":"[\"Logan Murphy\",\"Aren A. Babikian\",\"Marsha Chechik\"]","published":"2026-01-03T14:57:20Z","proceeding":"cs.SE","tasks":"[\"cs.SE\"]","methods":"[]","has_code":false}