arXiv AI
Oct 1

E2E-SWE: Benchmarking LLMs on Building Working Codebases from Scratch

E2E-SWE is a benchmark that tests large language models’ ability to create complete, functional software repositories from scratch. It includes 186 tasks across 11 programming languages, each requiring an agent to build an installable project based solely on a natural‑language specification and an empty workspace, while passing a hidden test suite. The benchmark was crafted by software engineers and LLMs, then refined through iterative verification by autonomous agents to ensure clarity and solvability.

By Hantian Ding, Chloe Bi, Jiacheng Zhu, John Yang, Matt Deitke, Pengcheng Yin, Zijian Wang, Rui Hou
arXiv AI
Aug 11

A Unified Issue Resolution Benchmark for Requirement Clarification, Planning, and Code Generation for Coding Agents

arXiv:2608. 09072v1 Announce Type: cross Abstract: Large language model-powered coding agents are increasingly used to modify existing code repositories, for example, by adding features or fixing bugs.

By Xin Zhou, Chun Yong Chong, Kisub Kim, Yun Peng, Rui Shu, Zihan Wu, Xu Han, Guowen Yuan, Zeyang Zhuang, Jounghoon Kim, Jeongjin Ju, Seongmin Ju, Taein Yoon, David Lo
arXiv AI
Oct 1

Zero2Repo: Can Coding Agents Build Repositories from Scratch?

arXiv:2609.38269v1 Announce Type: cross Abstract: Coding agents are increasingly asked to build software rather than patch it, yet benchmarks for from-scratch repository construction are mostly limit...

By Pei Yang, Tianyu Shi, Yuhang Yao, Wanyi Chen, Tongyun Yang, Dun Pei, Haonan Wang, Pengbin Feng, Guanxu Yu, Jingchun Huang, Zeyu Zhang, Shuhan Sun, Hao Li, Xiang Li, Jie Xiao, Xinyu Wang, Hanxin Chen, Daqi Li, Qi Jia, Hongshan Lin, Zhizhou Gu, Zijun Tian, Weizhi Du, Lynn Ai, Eric Yang
arXiv Machine Learning
Aug 6

ReCodeAgent: A Multi-agent Workflow for Language-Agnostic Translation and Validation of Large-Scale Repositories

arXiv:2604. 07341v2 Announce Type: replace-cross Abstract: Most repository-level code translation and validation techniques have been evaluated on a single source-target programming language (PL) pair, owing to the complex engineering effort required to adapt new PL pairs.

By Ali Reza Ibrahimzada, Brandon Paulsen, Daniel Kroening, Reyhaneh Jabbarvand