Toward Defensible System Behavior for AI-Generated Software Artifacts
TL;DR
This vision paper argues that trustworthy AI-assisted software engineering requires behavioural accountability: making implicit assumptions explicit, surfacing behavioural violations, and producing auditable evidence for developers and CI pipelines.
Abstract
AI-generated software artifacts often lack explicit design rationale and globally consistent behavioural assumptions, as independently generated fragments may embed locally plausible but mutually inconsistent assumptions. Existing verification techniques provide strong guarantees when relevant properties are explicitly specified, but may not capture undocumented assumptions or behavioural conflicts emerging only after artifact composition. This vision paper argues that trustworthy AI-assisted software engineering requires behavioural accountability: making implicit assumptions explicit, surfacing behavioural violations, and producing auditable evidence. We outline a conceptual deductive layer over behavioural abstractions of AI-generated artifacts, complementing testing and verification with structured accountability evidence for developers and CI pipelines.
