4 papers
Learning to Guarantee Type Correctness in Code Generation through Type-Guided Program Synthesis
Zhechong Huang, Zhao Zhang, Ruyi Ji +6
Language models have shown remarkable proficiency in code generation; nevertheless, ensuring type correctness remains a challenge. Although traditional methods, such as constrained…
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…
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…
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…