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

Saissi, Habib and Winter, Stefan and Schwahn, Oliver and Pattabiraman, K. and Suri, Neeraj (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. ISBN 9781728158105

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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.