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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

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Trace Sanitizer : Eliminating the Effects of Non-Determinism of Error Propagation Analysis. / Saissi, Habib; Winter, Stefan; Schwahn, Oliver et al.

2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE, 2020.

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

Harvard

Saissi, H, Winter, S, Schwahn, O, Pattabiraman, K & Suri, N 2020, Trace Sanitizer: Eliminating the Effects of Non-Determinism of Error Propagation Analysis. in 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE, IEEE/IFIP International Conference on Dependable Systems and Networks, 29/06/20. https://doi.org/10.1109/DSN48063.2020.00025

APA

Saissi, H., Winter, S., Schwahn, O., Pattabiraman, K., & Suri, N. (2020). Trace Sanitizer: Eliminating the Effects of Non-Determinism of Error Propagation Analysis. In 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) IEEE. https://doi.org/10.1109/DSN48063.2020.00025

Vancouver

Saissi H, Winter S, Schwahn O, Pattabiraman K, Suri N. Trace Sanitizer: Eliminating the Effects of Non-Determinism of Error Propagation Analysis. In 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE. 2020 doi: 10.1109/DSN48063.2020.00025

Author

Saissi, Habib ; Winter, Stefan ; Schwahn, Oliver et al. / Trace Sanitizer : Eliminating the Effects of Non-Determinism of Error Propagation Analysis. 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE, 2020.

Bibtex

@inproceedings{14cc88042045439f8c69885a652a7ff8,
title = "Trace Sanitizer: Eliminating the Effects of Non-Determinism of Error Propagation Analysis",
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.",
author = "Habib Saissi and Stefan Winter and Oliver Schwahn and K. Pattabiraman and Neeraj Suri",
note = "{\textcopyright}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. ; IEEE/IFIP International Conference on Dependable Systems and Networks, DSN ; Conference date: 29-06-2020 Through 02-07-2020",
year = "2020",
month = jun,
day = "23",
doi = "10.1109/DSN48063.2020.00025",
language = "English",
isbn = "9781728158105",
booktitle = "2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)",
publisher = "IEEE",
url = "https://dsn2020.webs.upv.es/",

}

RIS

TY - GEN

T1 - Trace Sanitizer

T2 - IEEE/IFIP International Conference on Dependable Systems and Networks

AU - Saissi, Habib

AU - Winter, Stefan

AU - Schwahn, Oliver

AU - Pattabiraman, K.

AU - Suri, Neeraj

N1 - Conference code: 50

PY - 2020/6/23

Y1 - 2020/6/23

N2 - 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.

AB - 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.

U2 - 10.1109/DSN48063.2020.00025

DO - 10.1109/DSN48063.2020.00025

M3 - Conference contribution/Paper

SN - 9781728158105

BT - 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)

PB - IEEE

Y2 - 29 June 2020 through 2 July 2020

ER -