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  • DSN_2020_paper (1)

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Trace Sanitizer: Eliminating the Effects of Non-Determinism of Error Propagation Analysis

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
  • Habib Saissi
  • Stefan Winter
  • Oliver Schwahn
  • K. Pattabiraman
  • Neeraj Suri
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Publication date23/06/2020
Host publication2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)
PublisherIEEE
Number of pages12
ISBN (electronic)9781728158099
ISBN (print)9781728158105
<mark>Original language</mark>English
EventIEEE/IFIP International Conference on Dependable Systems and Networks -
Duration: 29/06/20202/07/2020
Conference number: 50
https://dsn2020.webs.upv.es/

Conference

ConferenceIEEE/IFIP International Conference on Dependable Systems and Networks
Abbreviated titleDSN
Period29/06/202/07/20
Internet address

Conference

ConferenceIEEE/IFIP International Conference on Dependable Systems and Networks
Abbreviated titleDSN
Period29/06/202/07/20
Internet address

Abstract

Modern computing systems typically relax execution determinism, for instance by allowing the CPU scheduler to inter- leave the execution of several threads. While beneficial for performance, execution non-determinism affects programs' execution traces and hampers the comparability of repeated executions. We present TraceSanitizer, a novel approach for execution trace comparison in Error Propagation Analyses (EPA) of multi-threaded programs. TraceSanitizer can identify and compensate for non- determinisms caused either by dynamic memory allocation or by non-deterministic scheduling. We formulate a condition under which TraceSanitizer is guaranteed to achieve a 0% false positive rate, and automate its verification using Satisfiability Modulo Theory (SMT) solving techniques. TraceSanitizer is comprehensively evaluated using execution traces from the PARSEC and Phoenix benchmarks. In contrast with other approaches, Trace- Sanitizer eliminates false positives without increasing the false negative rate (for a specific class of programs), with reasonable performance overheads.

Bibliographic note

©2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.