ReArch-Coder: Requirement Alignment and Architecture Design for Reliable Repository-Level Code Generation

Open-source language models offer low cost and flexible deployment, making them attractive for practical coding agents. Yet they still struggle to generate executable repositories reliably from requirement documents. Existing approaches use harness engineering to organize repository generation, with closed-source frontier models serving as the underlying base models. However, applying these approaches to open-source models exposes two limitations: (1) Models may misinterpret requirements and implement functionality that departs from user needs. (2) Their limited architecture design capabilities can lead to flawed repository designs that prevent modules from working together. To address these challenges, we propose ReArch-Coder, a method for requirement alignment and repository architecture design optimization in open-source models. First, ReArch-Coder aligns the target model’s understanding of the requirement document through diagnostic questions and answers and factual hints. Then, it formulates architecture design as a trainable agentic decision-making process and optimizes it using GRPO with rewards based on requirement coverage and dependency modularity. Experimental results on representative repository-level code generation benchmarks demonstrate the effectiveness of our method. For example, ReArch-Coder outperforms the strongest coding-agent baseline on RepoGenesis by 21.8 percentage points in Passed and 19.6 percentage points in Resolved.