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ORCIDAutomated Software Engineering, Volume 33
Volume 33, Number 1, June 2026
- Rui He, Liang Zhang, Liangqing Lyu, Changbin Xue:
Enhancing the ability of LLMs for spaceborne equipment code generation via retrieval-augmented generation and contrastive learning. 1 - Haitao Sun, Ying Wang, Hai Yu, Zhiliang Zhu:
Enhanced neighborhood metric for spreadsheet fault prediction. 2 - Yinan Chen, Yuan Huang, Xiangping Chen, Pengfei Shen, Lei Yun:
GPTVD: vulnerability detection and analysis method based on LLM's chain of thoughts. 3 - Maha Alharbi, Mohammad R. Alshayeb:
Automatic Code Generation Techniques: A Systematic Literature Review. 4 - Mengliang Li, Qiang Shen, Xiaoxue Ren, Han Fu, Zhuo Li, Jianling Sun:
HMF: Enhancing reentrancy vulnerability detection and repair with a hybrid model framework. 5 - Ming Zhong, Zisheng Zeng, Yijia Guo, Dandan Zhao, Bo Zhang, Shenghong Li, Hao Peng, Zhiguo Ding:
Intelligent test case generation method for fuzzing IoT protocols based on LLM. 6 - Zhenyu Qi, Haotang Li, Hao Qin, Kebin Peng, Sen He, Xue Qin:
Harnessing large language models for virtual reality exploration testing: a case study. 7 - Omur Sahin, Man Zhang, Andrea Arcuri:
Causes and effects of fitness landscapes in system test generation: a replication study. 8 - Jiayin Song, Yike Li, Yunzhe Tian, Haoxuan Ma, Honglei Li, Jie Zuo, Jiqiang Liu, Wenjia Niu:
Investigating the bugs in reinforcement learning programs: Insights from Stack Overflow and GitHub. 9 - Yayun Zhang, Yuying Li, Minying Fang, Xing Yuan, Junwei Du:
BRMDS: an LLM-based multi-dimensional summary generation approach for bug reports. 10 - Xiangyue Liu, Xinwei Liu, Lili Bo, Xiaoxue Wu, Yun Yang, Xiaobing Sun, Feng Zhou:
PIONEER: improving the robustness of student models when compressing pre-trained models of code. 11
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