Wok: Statistical program slicing in production

Bogdan Alexandru Stoica, Swarup K. Sahoo, James R. Larus, Vikram S. Adve

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Dynamic program slicing can significantly reduce the amount of code developers need to inspect by focusing only on program statements relevant to their investigation. However, it is still not ready for production-level use either in terms of runtime or storage efficiency. We propose statistical program slicing, a novel hybrid dynamic-static slicing technique which explores the tradeoffs between runtime overhead, accuracy, and storage costs. Our approach relies on modern hardware support for control-flow tracing and selective heap memory instrumentation distributed across multiple executions combined with static program analysis for data-flow tracking.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE/ACM 41st International Conference on Software Engineering
Subtitle of host publicationCompanion, ICSE-Companion 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages324-325
Number of pages2
ISBN (Electronic)9781728117645
DOIs
StatePublished - May 2019
Event41st IEEE/ACM International Conference on Software Engineering: Companion, ICSE-Companion 2019 - Montreal, Canada
Duration: May 25 2019May 31 2019

Publication series

NameProceedings - 2019 IEEE/ACM 41st International Conference on Software Engineering: Companion, ICSE-Companion 2019

Conference

Conference41st IEEE/ACM International Conference on Software Engineering: Companion, ICSE-Companion 2019
Country/TerritoryCanada
CityMontreal
Period5/25/195/31/19

Keywords

  • Data-Flow Analysis
  • Hardware Debugging Support
  • Intel Processor Trace
  • Program Slicing
  • Runtime Tracing

ASJC Scopus subject areas

  • Organizational Behavior and Human Resource Management
  • Software
  • Safety, Risk, Reliability and Quality
  • Education

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