这篇论文搞了个CodeSpec，让代码智能体在仓库里加新功能时先建可执行规范，在FeatureBench上用DeepSeek-V4-Pro跑到70.7%通过率，比Claude Code靠谱不少。
CodeSpec提出双可执行规范方法，从子需求语义与仓库架构配对构建可靠功能链，并编译为互补的架构和行为规范。在FeatureBench上，使用DeepSeek-V4-Pro达到70.7%、55.0%和49.9%的通过率，优于Claude Code等基线。在NL2Repo-Bench上验证了泛化性。该方法通过可执行规范保证长周期开发中设计与实现的一致性。
CodeSpec: Dual Executable Specifications for Agentic Long-Horizon Feature Development
LLM-based code agents have advanced repository-level software development through iterative interaction with codebases and tools. However, feature development requires integrating new behaviors into existing architectures through coherent cross-component functional chains. Existing agents typically derive such chains through free-form reasoning, often producing unreliable feature designs with incomplete functional chains. Moreover, textual designs are difficult to verify and enforce, making it challenging to maintain design-implementation consistency throughout long-horizon development. We propose CodeSpec, a dual executable specification method for repository-level feature development. It builds reliable functional chains from evidence pairing sub-requirement semantics with repository architectures, then compiles them into complementary architecture and behavior specifications that check chain completeness and correctness while preserving design-implementation consistency over long interactions. On FeatureBench, which targets feature development in existing repositories, CodeSpec achieves 70.7%, 55.0%, and 49.9% pass rates under DeepSeek-V4-Pro, outperforming representative baselines such as Claude Code. Results on the repository generation benchmark NL2Repo-Bench further demonstrate its generalizability.