arXiv AI
Oct 12

Don't Guess, Just Ask: Evaluating Interactive Requirement Clarification for Repository-Level Software Development

The paper introduces ReqClarifyBench, an interactive benchmark for evaluating how well large language models (LLMs) can clarify vague user intent into clear requirements in repository-level software development. It includes 341 tasks across game, miniapp, and web development, each with a vague intent, a human-validated requirement document, and code evaluation artifacts, and uses LLM-based user simulators with diverse personas. The study evaluates six LLMs on clarification effectiveness and requirement quality, finding that stronger clarification does not always yield better documents, performance varies by persona, and coding-agent harnesses do not improve document quality over base LLMs.

By Mingyu Chen, Zhiqing Zhong, Manyi Wang, Linxi Liang, Rouyu Chen, Pinjia He