978 citations · 1.7k across the 38 of their papers we have counts for
8 papers · 1 filter
DSCodeBench: A Realistic Benchmark for Data Science Code Generation
Shuyin Ouyang, Dong Huang, Jingwen Guo +3
We introduce DSCodeBench, a new benchmark designed to evaluate large language models (LLMs) on complicated and realistic data science code generation tasks. DSCodeBench consists of…
Directional Diffusion-Style Code Editing Pre-training
Qingyuan Liang, Zeyu Sun, Qihao Zhu +6
Code pre-trained models have shown promising effectiveness in various software engineering tasks. Among these tasks, many tasks are related to software evolution and/or code editin…
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
DeepSeek-AI, Qihao Zhu, Daya Guo +37
We present DeepSeek-Coder-V2, an open-source Mixture-of-Experts (MoE) code language model that achieves performance comparable to GPT4-Turbo in code-specific tasks. Specifically, D…
On the Evaluation of Large Language Models in Unit Test Generation
Lin Yang, Chen Yang, Shutao Gao +8
Unit testing is an essential activity in software development for verifying the correctness of software components. However, manually writing unit tests is challenging and time-con…
DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence
Daya Guo, Qihao Zhu, Dejian Yang +10
The rapid development of large language models has revolutionized code intelligence in software development. However, the predominance of closed-source models has restricted extens…
CupCleaner: A Hybrid Data Cleaning Approach for Comment Updating
Qingyuan Liang, Zeyu Sun, Qihao Zhu +4
Comment updating is an emerging task in software evolution that aims to automatically revise source code comments in accordance with code changes. This task plays a vital role in m…
Lyra: A Benchmark for Turducken-Style Code Generation
Qingyuan Liang, Zeyu Sun, Qihao Zhu +4
Recently, neural techniques have been used to generate source code automatically. While promising for declarative languages, these approaches achieve much poorer performance on dat…
A Syntax-Guided Edit Decoder for Neural Program Repair
Qihao Zhu, Zeyu Sun, Yuan-an Xiao +4
Automated Program Repair (APR) helps improve the efficiency of software development and maintenance. Recent APR techniques use deep learning, particularly the encoder-decoder archi…