{
  "id": 5220,
  "url": "https://arxiv.org/abs/2604.26615v1",
  "title": "TDD Governance for Multi-Agent Code Generation via Prompt Engineering",
  "summary": "Large language models (LLMs) accelerate software development but often exhibit instability, non-determinism, and weak adherence to development discipline in unconstrained workflows. While test-driven development (TDD) provides a structured Red-Green-Refactor process, existing LLM-based approaches typically use tests as auxiliary inputs rather than enforceable process constraints. We present an AI-native TDD framework that operationalizes classical TDD principles as structured prompt-level and wo",
  "authors": "Tarlan Hasanli, Shahbaz Siddeeq, Bishwash Khanal, Pyry Kotilainen, Tommi Mikkonen, Pekka Abrahamsson",
  "category": "research",
  "topics": "regulation,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-04-29T12:43:22.000Z",
  "fetched_at": "2026-07-14T16:31:35.575Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/5220",
  "original_url": "https://arxiv.org/abs/2604.26615v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}