TDD Governance for Multi-Agent Code Generation via Prompt Engineering
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
Record details
Published: 29 April 2026
Source: arXiv
Category: Research
Topics: Regulation · Agents & autonomy
Retrieved: 14 July 2026
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ethics.ai (29 April 2026), “TDD Governance for Multi-Agent Code Generation via Prompt Engineering,” evidence record 5220, https://ethics.ai/record/5220 (originally published by arXiv).
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