1 citations · 1 across the 3 of their papers we have counts for
7 papers
Advances and Frontiers of LLM-based Issue Resolution in Software Engineering: A Comprehensive Survey
Caihua Li, Lianghong Guo, Yanlin Wang +9
Issue resolution, a complex Software Engineering (SWE) task integral to real-world development, has emerged as a compelling challenge for artificial intelligence. The establishment…
SWE-Factory: Your Automated Factory for Issue Resolution Training Data and Evaluation Benchmarks
Lianghong Guo, Yanlin Wang, Caihua Li +6
Constructing large-scale datasets for the GitHub issue resolution task is crucial for both training and evaluating the software engineering capabilities of Large Language Models (L…
SimpleDevQA: Benchmarking Large Language Models on Development Knowledge QA
Jing Zhang, Lianghong Guo, Yanlin Wang +7
The Development Knowledge Question Answering (Dev Knowledge QA) task aims to provide natural language answers to knowledge-seeking questions during software development. To investi…
OmniGIRL: A Multilingual and Multimodal Benchmark for GitHub Issue Resolution
Lianghong Guo, Wei Tao, Runhan Jiang +7
The GitHub issue resolution task aims to resolve issues reported in repositories automatically. With advances in large language models (LLMs), this task has gained increasing atten…
Towards an Understanding of Large Language Models in Software Engineering Tasks
Zibin Zheng, Kaiwen Ning, Qingyuan Zhong +5
Large Language Models (LLMs) have drawn widespread attention and research due to their astounding performance in text generation and reasoning tasks. Derivative products, like Chat…
You Augment Me: Exploring ChatGPT-based Data Augmentation for Semantic Code Search
Yanlin Wang, Lianghong Guo, Ensheng Shi +8
Code search plays a crucial role in software development, enabling developers to retrieve and reuse code using natural language queries. While the performance of code search models…