Low-overhead and fully automated statistical debugging with abstraction refinement

Abstract

Cooperative statistical debugging is an effective approach for diagnosing production-run failures. To quickly identify failure predictors from the huge program predicate space, existing techniques rely on random or heuristics-guided predicate sampling at the user side. However, none of them can satisfy the requirements of low cost, low diagnosis latency, and high diagnosis quality simultaneously, which are all indispensable for statistical debugging to be practical.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 19, 2016
Source ID
10.1145/3022671.2984005

Entities

People

  • Guoqing Xu
  • Lu Fang
  • Shan Lu
  • Siau-cheng Khoo
  • Zhiqiang Zuo

Organizations

  • Alfred P. Sloan Foundation
  • Division of Computer and Network Systems
  • Division of Computing and Communication Foundations
  • National University of Singapore
  • Office of Naval Research
  • University of California, Irvine
  • University of Chicago

Tags

Fields of Study

  • Computer science
  • Engineering

Readers

  • Distributed Systems and Data Platform Development
  • Oncology and Biomarker-Based Cancer Detection.
  • Parallel and Distributed Computing.

Technology Areas

  • Space