Abductive Vibe Coding (Extended Abstract)

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Authors: Logan Murphy, Aren A. Babikian, Marsha Chećhik
Cited by: 0

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.

Fields of Study & Subjects

Software Engineering Research Advanced Software Engineering Methodologies Logic programming and type systems

Publication details

Journal / source
arXiv (Cornell University)
Publication date
3 January 2026
Document type
Preprint