Zobrazeno 1 - 10
of 757
pro vyhledávání: '"LIU, MINGWEI"'
Recent advances in large language models (LLMs) have shown significant capabilities in code translation, often evaluated using benchmarks like CodeTransOcean. However, these evaluations typically focus on simple, function-level translations without c
Externí odkaz:
http://arxiv.org/abs/2411.13990
Code search is crucial for code reuse, enabling developers to efficiently locate relevant snippets. Current methods rely on encoder-based models, which suffer from limitations such as poor generalization and restricted input lengths. Decoder-only lar
Externí odkaz:
http://arxiv.org/abs/2410.22240
Python's dynamic typing system offers flexibility and expressiveness but can lead to type-related errors, prompting the need for automated type inference to enhance type hinting. While existing learning-based approaches show promising inference accur
Externí odkaz:
http://arxiv.org/abs/2407.02095
Publikováno v:
ILR Review. Oct2024, Vol. 77 Issue 5, p813-824. 12p.
Large language models (LLMs) have brought a paradigm shift to the field of code generation, offering the potential to enhance the software development process. However, previous research mainly focuses on the accuracy of code generation, while coding
Externí odkaz:
http://arxiv.org/abs/2407.00456
Autor:
Du, Xueying, Zheng, Geng, Wang, Kaixin, Feng, Jiayi, Deng, Wentai, Liu, Mingwei, Chen, Bihuan, Peng, Xin, Ma, Tao, Lou, Yiling
Vulnerability detection is essential for software quality assurance. In recent years, deep learning models (especially large language models) have shown promise in vulnerability detection. In this work, we propose a novel LLM-based vulnerability dete
Externí odkaz:
http://arxiv.org/abs/2406.11147
Repository-level code completion is challenging as it involves complicated contexts from multiple files in the repository. To date, researchers have proposed two technical categories to enhance LLM-based repository-level code completion, i.e., retrie
Externí odkaz:
http://arxiv.org/abs/2406.10018
Crash bugs cause unexpected program behaviors or even termination, requiring high-priority resolution. However, manually resolving crash bugs is challenging and labor-intensive, and researchers have proposed various techniques for their automated loc
Externí odkaz:
http://arxiv.org/abs/2312.10448
Autor:
Liu, Mingwei
In contemporary world, the global energy crisis and raise of greenhouse gas concentration in atmosphere necessitate the energy conservation and emission reduction. Hybrid electric vehicles (HEVs) can achieve great promise in reducing fuel consumption
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-323953
Library migration, which re-implements the same software behavior by using a different library instead of using the current one, has been widely observed in software evolution. One essential part of library migration is to find an analogical API that
Externí odkaz:
http://arxiv.org/abs/2308.11422