ASE 2025
Sun 16 - Thu 20 November 2025 Seoul, South Korea

This program is tentative and subject to change.

Mon 17 Nov 2025 12:10 - 12:20 at Grand Hall 5 - Log & Dependency

Configuration dependencies arise when multiple technologies in a software system require coordinated settings for correct interplay. Existing approaches for detecting such dependencies often yield high false-positive rates, require additional validation mechanisms, and are typically limited to specific projects or technologies. Recent work that incorporates large language models (LLMs) for dependency validation still suffers from inaccuracies due to project- and technology-specific variations, as well as from missing contextual information.

In this work, we propose to use retrieval-augmented generation (RAG) systems for configuration dependency validation, which allows us to incorporate additional project- and technology-specific context information. Specifically, we evaluate whether RAG can improve LLM-based validation of configuration dependencies and what contextual information are needed to overcome the static knowledge base of LLMs. To this end, we conducted a large empirical study on validating configuration dependencies using RAG. Our evaluation shows that vanilla LLMs already demonstrate solid validation abilities, while RAG has only marginal or even negative effects on the validation performance of the models. By incorporating tailored contextual information into the RAG system–derived from a qualitative analysis of validation failures–we achieve significantly more accurate validation results across all models, with an average precision of 0.84 and recall of 0.70, representing improvements of 35% and 133% over vanilla LLMs, respectively. In addition, these results offer two important insights: Simplistic RAG systems may not benefit from additional information if it is not tailored to the task at hand, and it is often unclear upfront what kind of information yields improved performance.

This program is tentative and subject to change.

Mon 17 Nov

Displayed time zone: Seoul change

11:00 - 12:40
11:00
10m
Talk
LogMoE: Lightweight Expert Mixture for Cross-System Log Anomaly Detection
Research Papers
Jiaxing Qi Beihang University, Zhongzhi Luan Beihang University, Shaohan Huang Beihang University, Carol Fung Concordia University, Yuchen Wang Beihang University, Aibin Wang Beihang University, Hongyu Zhang Chongqing University, Hailong Yang Beihang University, China, Depei Qian Beihang University, China
11:10
10m
Talk
Improving LLM-based Log Parsing by Learning from Errors in Reasoning Traces
Research Papers
Wang Jialai National University of Singapore, Juncheng Lu Southeast University, Jie Yang Wuhan University, Junjie Wang Institute of Software at Chinese Academy of Sciences, Zeyu Gao Tsinghua University, Chao Zhang Tsinghua University, Zhenkai Liang NUS, Ee-Chien Chang School of Computing, NUS
11:20
10m
Talk
LogUpdater: Automated Detection and Repair of Specific Defects in Logging Statements
Journal-First Track
Renyi Zhong The Chinese University of Hong Kong, Yichen LI ByteDance, Jinxi Kuang The Chinese University of Hong Kong, Wenwei Gu The Chinese University of Hong Kong, Yintong Huo Singapore Management University, Singapore, Michael Lyu The Chinese University of Hong Kong
11:30
10m
Talk
LogAction: Consistent Cross-system Anomaly Detection through Logs via Active Domain Adaptation
Research Papers
Chiming Duan Peking University, Minghua He Peking University, Pei Xiao Peking University, Tong Jia Institute for Artificial Intelligence, Peking University, Beijing, China, Xin Zhang Peking University, Zhewei Zhong Bytedance, Xiang Luo Bytedance, Yan Niu Bytedance, Lingzhe Zhang Peking University, China, Yifan Wu Peking University, Siyu Yu The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), Weijie Hong Peking university, Ying Li School of Software and Microelectronics, Peking University, Beijing, China, Gang Huang Peking University
11:40
10m
Talk
Diplomatist: What Do Cross-language Dependencies Reflect Software Ecosystem Health?
Research Papers
Fanyi Meng Shenyang University of Technology, Ying Wang Northeastern University, Chun Yong Chong Monash University Malaysia, Hai Yu Northeastern University, China, Zhiliang Zhu Northeastern University, China
11:50
10m
Talk
Defects4Log: Benchmarking LLMs for Logging Code Defect Detection and Reasoning
Research Papers
Xin Wang Changsha University of Science and Technology, Zhenhao Li York University, Zishuo Ding The Hong Kong University of Science and Technology (Guangzhou)
12:00
10m
Talk
Which Is Better For Reducing Outdated And Vulnerable Dependencies: Pinning Or Floating?
Research Papers
Imranur Rahman North Carolina State University, Jill Marley North Carolina State University, William Enck North Carolina State University, Laurie Williams North Carolina State University
12:10
10m
Talk
On Automating Configuration Dependency Validation via Retrieval-Augmented Generation
Research Papers
Sebastian Simon Leipzig University, Alina Mailach Leipzig University, Johannes Dorn Leipzig University, Norbert Siegmund Leipzig University
Pre-print
12:20
10m
Talk
CollaborLog: Efficient-Generalizable Log Anomaly Detection via Large-Small Model Collaboration in Software Evolution
Research Papers
Pei Xiao Peking University, Chiming Duan Peking University, Minghua He Peking University, Tong Jia Institute for Artificial Intelligence, Peking University, Beijing, China, Yifan Wu Peking University, Jing Xu ByteDance, Gege Gao ByteDance, Lingzhe Zhang Peking University, China, Weijie Hong Peking university, Ying Li School of Software and Microelectronics, Peking University, Beijing, China, Gang Huang Peking University
12:30
10m
Talk
On the Robustness Evaluation of 3D Obstacle Detection Against Specifications in Autonomous Driving
Research Papers
Tri Minh-Triet Pham Concordia University, Bo Yang Concordia University, Jinqiu Yang Concordia University