Dads: Dynamic Slicing Continuously-Running Distributed Programs with Budget Constraints
We present Dads, the first distributed, online, scalable, and cost-effective dynamic slicer for continuously-running distributed programs with respect to user-specified budget constraints. Dads is distributed by design to exploit distributed and parallel computing resources. With an online analysis, it avoids tracing hence the associated time and space costs. Most importantly, Dads achieves and maintains practical scalability and cost-effectiveness tradeoffs according to a given budget on analysis time by continually and automatically adjusting the configuration of its analysis algorithm on the fly via reinforcement learning. Against eight real-world Java distributed systems, we empirically demonstrated the scalability and cost-effectiveness merits of Dads. The open-source tool package of Dads with a demo video is publicly available.
Tue 10 NovDisplayed time zone: (UTC) Coordinated Universal Time change
01:30 - 02:00 | |||
01:30 5mTalk | A Study of Call Graph Construction for JVM-Hosted Languages Journal First Karim Ali University of Alberta, Xiaoni Lai Google, Zhaoyi Luo Microsoft, Ondřej Lhoták University of Waterloo, Julian Dolby IBM Research, USA, Frank Tip Northeastern University Pre-print Media Attached | ||
01:33 1mTalk | Change Impact Analysis in Simulink Designs of Embedded Systems Industry Papers Bennett Mackenzie McMaster University, Canada, Vera Pantelic McMaster University, Canada, Gordon Marks McMaster University, Canada, Stephen Wynn-Williams McMaster University, Canada, Gehan Selim McMaster University, Canada, Mark Lawford McMaster, Alan Wassyng McMaster University, Canada, Moustapha Diab FCA, USA, Feisel Weslati FCA, USA DOI | ||
01:35 1mTalk | Dads: Dynamic Slicing Continuously-Running Distributed Programs with Budget Constraints Tool Demos Xiaoqin Fu Washington State University, Haipeng Cai Washington State University, USA, Li Li Monash University, Australia DOI | ||
01:37 1mTalk | JShrink: In-Depth Investigation into Debloating Modern Java Applications Research Papers Bobby Bruce University of California at Davis, USA, Tianyi Zhang Harvard University, USA, Jaspreet Arora University of California at Los Angeles, USA, Guoqing Harry Xu University of California at Los Angeles, Miryung Kim University of California at Los Angeles, USA DOI | ||
01:39 1mTalk | Making Symbolic Execution Promising by Learning Aggressive State-Pruning Strategy Research Papers DOI | ||
01:41 19mTalk | Conversations on Analysis 2 Research Papers Karim Ali University of Alberta, Pengyu Nie University of Texas at Austin, USA, SooYoung Chae , Xiaoqin Fu Washington State University, Hoda Khalil Carleton University, M: Shin Hwei Tan Southern University of Science and Technology | ||