6 papers
Mitigating Implicit Inconsistencies in Patch Porting
Shengyi Pan, Zhongxin Liu, Jiayuan Zhou +3
Promptly porting patches from a source codebase to its variants (e.g., forks and branches) is essential for mitigating propagated defects and vulnerabilities. Recent studies have e…
Forecasting Developer Environments with GenAI: A Research Perspective
Raula Gaikovina Kula, Christoph Treude, Xing Hu +28
Generative Artificial Intelligence (GenAI) models are achieving remarkable performance in various tasks, including code generation, testing, code review, and program repair. The ab…
Intention Chain-of-Thought Prompting with Dynamic Routing for Code Generation
Shen Li, Li Huang, Shaoxiong Zhan +4
Large language models (LLMs) exhibit strong generative capabilities and have shown great potential in code generation. Existing chain-of-thought (CoT) prompting methods enhance mod…
B4: Towards Optimal Assessment of Plausible Code Solutions with Plausible Tests
Mouxiang Chen, Zhongxin Liu, He Tao +4
Selecting the best code solution from multiple generated ones is an essential task in code generation, which can be achieved by using some reliable validators (e.g., developer-writ…
Exploring the Capabilities of LLMs for Code Change Related Tasks
Lishui Fan, Jiakun Liu, Zhongxin Liu +3
Developers deal with code-change-related tasks daily, e.g., reviewing code. Pre-trained code and code-change-oriented models have been adapted to help developers with such tasks. R…
Automating Zero-Shot Patch Porting for Hard Forks
Shengyi Pan, You Wang, Zhongxin Liu +3
Forking is a typical way of code reuse, which provides a simple way for developers to create a variant software (denoted as hard fork) by copying and modifying an existing codebase…