Node.js has become a widely-used event-driven architecture for server-side and desktop applications. Node.js provides an effective asynchronous event-driven programming model, and supports asynchronous tasks and multi-priority event queues. Unexpected races among events and asynchronous tasks can cause severe consequences. Existing race detection approaches in Node.js applications mainly adopt random fuzzing technique, and can miss races due to large testing space and suffer from large overhead.
In this paper, we propose a dynamic race detection approach \emph{NRace} for Node.js applications. In NRace, we build precise happens-before relations among events and asynchronous tasks in Node.js applications, which also take multi-priority event queues into consideration. We further develop a predictive race detection technique based on these relations. We evaluate NRace on 10 real-world Node.js applications. The experimental result shows that NRace can precisely detect 6 races, and 5 of them have been confirmed by developers.
Wed 17 NovDisplayed time zone: Hobart change
19:00 - 20:00 | DetectionResearch Papers / NIER track at Kangaroo Chair(s): Cuiyun Gao Harbin Institute of Technology | ||
19:00 20mTalk | Race Detection for Event-Driven Node.js Applications Research Papers Xiaoning Chang Institute of Software, Chinese Academy of Sciences, Wensheng Dou Institute of Software at Chinese Academy of Sciences; University of Chinese Academy of Sciences, Jun Wei Institute of Software at Chinese Academy of Sciences; University of Chinese Academy of Sciences, Tao Huang Institute of Software Chinese Academy of Sciences, Jinhui Xie Tencent Inc., Yuetang Deng Tencent, Jianbo Yang Tencent Inc., Jiaheng Yang Tencent Inc. | ||
19:20 20mTalk | Log-based Anomaly Detection Without Log Parsing Research Papers Link to publication DOI Pre-print | ||
19:40 10mTalk | Log Anomaly to Resolution: AI Based Proactive Incident Remediation NIER track | ||
19:50 10mTalk | HyperGI: Automated Detection and Repair of Information Flow Leakage NIER track Ibrahim Mesecan Iowa State University, Daniel Blackwell University College London, David Clark University College London, Myra Cohen Iowa State University, Justyna Petke University College London Pre-print |