10 papers
Evaluating Repository-level Software Documentation via Question Answering and Feature-Driven Development
Xinchen Wang, Ruida Hu, Cuiyun Gao +2
Software documentation is crucial for repository comprehension. While Large Language Models (LLMs) advance documentation generation from code snippets to entire repositories, exist…
Evaluating LLM-Based 0-to-1 Software Generation in End-to-End CLI Tool Scenarios
Ruida Hu, Xinchen Wang, Chao Peng +2
The evolution of Large Language Models (LLMs) has catalyzed a paradigm shift towards intent-driven software development, where autonomous agents are expected to design and deliver…
Benchmarking LLMs for Fine-Grained Code Review with Enriched Context in Practice
Ruida Hu, Xinchen Wang, Xin-Cheng Wen +5
Code review is a cornerstone of software quality assurance, and recent advances in Large Language Models (LLMs) have shown promise in its automation. However, existing benchmarks f…
AXIOM: Benchmarking LLM-as-a-Judge for Code via Rule-Based Perturbation and Multisource Quality Calibration
Ruiqi Wang, Xinchen Wang, Cuiyun Gao +3
Large language models (LLMs) have been increasingly deployed in real-world software engineering, fostering the development of code evaluation metrics to study the quality of LLM-ge…
CodeVisionary: An Agent-based Framework for Evaluating Large Language Models in Code Generation
Xinchen Wang, Pengfei Gao, Chao Peng +2
Large language models (LLMs) have demonstrated strong capabilities in code generation, underscoring the critical need for rigorous and comprehensive evaluation. Existing evaluation…
Repo2Run: Automated Building Executable Environment for Code Repository at Scale
Ruida Hu, Chao Peng, Xinchen Wang +2
Scaling up executable code data is significant for improving language models' software engineering capability. The intricate nature of the process makes it labor-intensive, time-co…