专题：Software Engineering Research

This cluster of papers focuses on empirical studies in software engineering, covering topics such as refactoring, code clone detection, software defect prediction, requirements traceability, static code attributes, machine learning, software maintenance, source code analysis, bug localization, and API usage patterns.
最新文献
近5年高被引文献
Large Language Models for Software Engineering: A Systematic Literature Review

review Full Text OpenAlex 820 FWCI116.9094

ProtGPT2 is a deep unsupervised language model for protein design

article Full Text OpenAlex 807 FWCI51.5082

A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT

preprint Full Text OpenAlex 804 FWCI0

Augmenting large language models with chemistry tools

article Full Text OpenAlex 676 FWCI58.4458

PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation

conference-paper Full Text OpenAlex 640 FWCI270.171

Expectation vs. Experience: Evaluating the Usability of Code Generation Tools Powered by Large Language Models

conference-paper Full Text OpenAlex 607 FWCI126.8972

UniXcoder: Unified Cross-Modal Pre-training for Code Representation

conference-paper Full Text OpenAlex 596 FWCI126.1448

Learning design to support student-AI collaboration: perspectives of leading teachers for AI in education

article Full Text OpenAlex 588 FWCI93.2924

Can Open Large Language Models Catch Vulnerabilities?

preprint Full Text OpenAlex 525 FWCI0

A systematic evaluation of large language models of code

conference-paper Full Text OpenAlex 515 FWCI116.8459