Data Race Detection on Compressed Traces

07/23/2018
by   Dileep Kini, et al.
0

We consider the problem of detecting data races in program traces that have been compressed using straight line programs (SLP), which are special context-free grammars that generate exactly one string, namely the trace that they represent. We consider two classical approaches to race detection --- using the happens-before relation and the lockset discipline. We present algorithms for both these methods that run in time that is linear in the size of the compressed, SLP representation. Typical program executions almost always exhibit patterns that lead to significant compression. Thus, our algorithms are expected to result in large speedups when compared with analyzing the uncompressed trace. Our experimental evaluation of these new algorithms on standard benchmarks confirms this observation.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/07/2019

Predicting All Data Race Pairs for a Specific Schedule (extended version)

We consider the problem of data race prediction where the program's beha...
research
05/26/2019

Data Race Prediction for Inaccurate Traces

Happens-before based data race prediction methods infer from a trace of ...
research
11/09/2021

Pattern Matching on Grammar-Compressed Strings in Linear Time

The most fundamental problem considered in algorithms for text processin...
research
10/06/2020

Static Race Detection for RTOS Applications

We present a static analysis technique for detecting data races in Real-...
research
02/05/2018

The Effect Race in Fine-Grained Concurrency

Most existed work require knowledge about the effect of program instruct...
research
01/25/2019

Fast, Sound and Effectively Complete Dynamic Race Detection

Writing concurrent programs is highly error-prone due to the nondetermin...
research
09/11/2017

A Planning Approach to Monitoring Behavior of Computer Programs

We describe a novel approach to monitoring high level behaviors using co...

Please sign up or login with your details

Forgot password? Click here to reset