ACM Transactions on Software Engineering and Methodology 2024 — papers
The works of ACM Transactions on Software Engineering and Methodology published in 2024 that our library holds (publisher: Association for Computing Machinery): 1 work, listed below with the most cited first; each has a page with our summary, its key points and its references.
Most cited papers
- Large Language Models for Software Engineering: A Systematic Literature Review ↗Xinyi Hou, Yanjie Zhao, Yue Liu et al.981 citations
- Self-Collaboration Code Generation via ChatGPTYihong Dong, Xue Jiang, Zhi Gang Jin et al.250 citations · our summary
- An Empirical Study of the Non-Determinism of ChatGPT in Code Generation ↗Shuyin Ouyang, Jie M. Zhang, Mark Harman et al.247 citations
- Navigating the Complexity of Generative AI Adoption in Software Engineering ↗Daniel Russo215 citations
- Self-Planning Code Generation with Large Language ModelsXue Jiang, Yihong Dong, L. F. Wang et al.153 citations · our summary
- Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues ↗Yue Liu, Thanh Le-Cong, Ratnadira Widyasari et al.146 citations
- Structured Chain-of-Thought Prompting for Code Generation ↗Jia Li, Ge Li, Yongmin Li et al.141 citations
- Large Language Model for Vulnerability Detection and Repair: Literature Review and the Road Ahead ↗Xin Zhou, Sicong Cao, Xiaobing Sun et al.132 citations
- Fairness Testing: A Comprehensive Survey and Analysis of Trends ↗Zhenpeng Chen, Jie M. Zhang, Max Hort et al.98 citations
- Toward Enhancing Privacy Preservation of a Federated Learning CNN Intrusion Detection System in IoT: Method and Empirical Study ↗Damiano Torre, Anitha Chennamaneni, JaeYun Jo et al.96 citations
All works of the year (269)
- Large Language Models for Software Engineering: A Systematic Literature Review ↗Xinyi Hou, Yanjie Zhao, Yue Liu et al.981 citations
- Self-Collaboration Code Generation via ChatGPTYihong Dong, Xue Jiang, Zhi Gang Jin et al.250 citations · our summary
- An Empirical Study of the Non-Determinism of ChatGPT in Code Generation ↗Shuyin Ouyang, Jie M. Zhang, Mark Harman et al.247 citations
- Navigating the Complexity of Generative AI Adoption in Software Engineering ↗Daniel Russo215 citations
- Self-Planning Code Generation with Large Language ModelsXue Jiang, Yihong Dong, L. F. Wang et al.153 citations · our summary
- Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues ↗Yue Liu, Thanh Le-Cong, Ratnadira Widyasari et al.146 citations
- Structured Chain-of-Thought Prompting for Code Generation ↗Jia Li, Ge Li, Yongmin Li et al.141 citations
- Large Language Model for Vulnerability Detection and Repair: Literature Review and the Road Ahead ↗Xin Zhou, Sicong Cao, Xiaobing Sun et al.132 citations
- Fairness Testing: A Comprehensive Survey and Analysis of Trends ↗Zhenpeng Chen, Jie M. Zhang, Max Hort et al.98 citations
- Toward Enhancing Privacy Preservation of a Federated Learning CNN Intrusion Detection System in IoT: Method and Empirical Study ↗Damiano Torre, Anitha Chennamaneni, JaeYun Jo et al.96 citations
- When ChatGPT Meets Smart Contract Vulnerability Detection: How Far Are We? ↗Chong Chen, Jianzhong Su, Jiachi Chen et al.85 citations
- CodeScore: Evaluating Code Generation by Learning Code Execution ↗Yihong Dong, Jiazheng Ding, Xue Jiang et al.64 citations
- On the Effectiveness of Large Language Models in Domain-Specific Code Generation ↗Xiaodong Gu, Meng Chen, Yalan Lin et al.56 citations
- Automatic Programming: Large Language Models and Beyond ↗Michael Rung-Tsong Lyu, Baishakhi Ray, Abhik Roychoudhury et al.49 citations
- Efficient and Green Large Language Models for Software Engineering: Literature Review, Vision, and the Road Ahead ↗Jieke Shi, Zhou Yang, David Lo42 citations
- Exploring the Capabilities of LLMs for Code-Change-Related Tasks ↗Lishui Fan, Jiakun Liu, Zhongxin Liu et al.40 citations
- Revisiting Sentiment Analysis for Software Engineering in the Era of Large Language Models ↗Ting Zhang, Ivana Clairine Irsan, Ferdian Thung et al.40 citations
- DeepGD: A Multi-Objective Black-Box Test Selection Approach for Deep Neural Networks ↗Zohreh Aghababaeyan, Manel Abdellatif, Mahboubeh Dadkhah et al.37 citations
- Unveiling Code Pre-Trained Models: Investigating Syntax and Semantics Capacities ↗Wei Ma, Shangqing Liu, Mengjie Zhao et al.36 citations
- Towards Effective Detection of Ponzi Schemes on Ethereum with Contract Runtime Behavior Graph ↗Ruichao Liang, Jing Chen, Cong Wu et al.35 citations
- sGuard+: Machine Learning Guided Rule-Based Automated Vulnerability Repair on Smart Contracts ↗Cuifeng Gao, Wenzhang Yang, Jiaming Ye et al.34 citations
- A Novel Refactoring and Semantic Aware Abstract Syntax Tree Differencing Tool and a Benchmark for Evaluating the Accuracy of Diff Tools ↗Pouria Alikhanifard, Nikolaos Tsantalis33 citations
- Interpretable Failure Localization for Microservice Systems Based on Graph Autoencoder ↗Yongqian Sun, Zihan Lin, Binpeng Shi et al.33 citations
- Large Language Model Supply Chain: A Research Agenda ↗Shenao Wang, Yanjie Zhao, Xinyi Hou et al.33 citations
- Test Optimization in DNN Testing: A Survey ↗Qiang Hu, Yuejun Guo, Xiaofei Xie et al.33 citations
See all 269 papers in ACM Transactions on Software Engineering and Methodology 2024 — papers →
Works with our summary in our library (1)
- A Survey on Large Language Models for Code GenerationACM Transactions on Software Engineering and MethodologyJuyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 367 citations
Top topics
Language models & pretraining (1)Code & programming languages (1)
Fields
Arts and Humanities (1)Computer Science (1)
Top authors
Top institutions
🎓Hong Kong University of Science and TechnologyHong Kong ·
China1 work here🏢NAVER CloudSeongnam-si ·
South Korea1 work here🎓The Hong Kong University of Science and Technology (Guangzhou)Guangzhou ·
China1 work here
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