Toward Spec-Driven Code Review Vision: Orchestrating Human–AI Collaboration in Code Review

ACM AIWare 2026 Conference Submission58 Authors

Keywords: Code review, Spec-Driven Development

TL;DR: A new vision for code review based on spec first paradigm

Abstract:

Code review enforces software standards, architectural constraints, API contracts, and quality expectations in modern development workflows. However, while projects define numerous specifications, current review tools remain largely diff-centric and provide limited support for operationalizing these standards during review. As systems scale and teams become increasingly distributed, enforcing specifications consistently becomes difficult, leading to repeated debates, implicit assumptions, and fragmented knowledge.

The emergence of agentic AI systems introduces new opportunities to structure review more systematically. Rather than merely generating comments or detecting defects, AI agents can assist in identifying relevant specifications, synthesizing validation plans, and executing targeted checks. Inspired by the philosophy of Spec-Driven Development, we argue that code review should be explicitly structured around specifications, in particular specification-driven review planning.

We introduce Spec-Driven Code Review (SDCR), a framework that organizes review into three phases: Review Planning, Review Execution, and Review Artefact Persistence. SDCR treats specifications as first-class review artifacts, enabling human--AI collaboration to produce structured review plans, evidence-linked assessments, and reusable review knowledge. By reframing review as a planning-centric, specification-aware process, SDCR aims to improve scalability, consistency, and accountability in human--AI code review systems.

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Paper Type: Short papers (i.e., vision, new ideas, and position papers). 2–4 pages

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Submission Number: 58