SANER 2025 (series) / Industrial Track /
RADICE: Causal Graph Based Root Cause Analysis for System Performance Diagnostic
Thu 6 MarDisplayed time zone: Eastern Time (US & Canada) change
Thu 6 Mar
Displayed time zone: Eastern Time (US & Canada) change
14:00 - 15:30 | Defect Prediction & AnalysisResearch Papers / Industrial Track / Journal First Track at L-1710 Chair(s): Rrezarta Krasniqi University of North Carolina at Charlotte | ||
14:00 15mTalk | An ensemble learning method based on neighborhood granularity discrimination index and its application in software defect prediction Research Papers Yuqi Sha College of Information Science and Technology,Qingdao University of Science and Technology, Feng Jiang College of Information Science and Technology,Qingdao University of Science and Technology, Qiang Hu College of Information Science and Technology, Qingdao University of Science and technology, Yifan He Institute of Cosmetic Regulatory Science,Beijing Technology and Business University | ||
14:15 15mTalk | ALOGO: A Novel and Effective Framework for Online Cross-project Defect Prediction Research Papers Rongrong Shi Beijing Jiaotong University, Yuxin He Beijing Jiaotong University, Ying Liu Beijing Jiaotong University, Zonghao Li Beijing Jiaotong University, Jingxin Su Beijing Jiaotong University, Haonan Tong Beijing Jiaotong University | ||
14:30 15mTalk | Cross-System Software Log-based Anomaly Detection Using Meta-Learning Research Papers Yuqing Wang University of Helsinki, Finland, Mika Mäntylä University of Helsinki and University of Oulu, Jesse Nyyssölä University of Helsinki, Ke Ping University of Helsinki, Liqiang Wang University of Wyoming Pre-print | ||
14:45 15mTalk | RADICE: Causal Graph Based Root Cause Analysis for System Performance Diagnostic Industrial Track Andrea Tonon Huawei Ireland Research Center, Meng Zhang Shandong University, Bora Caglayan Huawei Ireland Research Center, Fei Shen Huawei Nanjing Research Center, Tong Gui , Mingxue Wang Huawei Ireland Research Center, Rong Zhou | ||
15:00 15mTalk | Can We Trust the Actionable Guidance from Explainable AI Techniques in Defect Prediction? Research Papers | ||
15:15 15mTalk | Making existing software quantum safe: A case study on IBM Db2 Journal First Track Lei Zhang University of Maryland Baltimore County, Andriy Miranskyy Toronto Metropolitan University (formerly Ryerson University), Walid Rjaibi IBM Canada Lab, Greg Stager IBM Canada Lab, Michael Gray IBM, John Peck IBM |