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http://dx.doi.org/10.9708/jksci.2017.22.11.001

A Study on Filtering Techniques for Dynamic Analysis of Data Races in Multi-threaded Programs  

Ha, Ok-Kyoon (Dept. of Aeronautics & Software Engineering, Kyungwoon University)
Yoo, Hongseok (Dept. of Aeronautics & Software Engineering, Kyungwoon University)
Publication Information
Journal of the Korea Society of Computer and Information / v.22, no.11, 2017 , pp. 1-7 More about this Journal
Abstract
In this paper, we introduce three monitoring filtering techniques which reduce the overheads of dynamic data race detection. It is well known that detecting data races dynamically in multi-threaded programs is quite hard and troublesome task, because the dynamic detection techniques need to monitor all execution of a multi-threaded program and to analyse every conflicting memory and thread operations in the program. Thus, the main drawback of the dynamic analysis for detecting data races is the heavy additional time and space overheads for running the program. For the practicality, we also empirically compare the efficiency of three monitoring filtering techniques. The results using OpenMP benchmarks show that the filtering techniques are practical for dynamic data race detection, since they reduce the average runtime overhead to under 10% of that of the pure detection.
Keywords
Data races; Data race detection; Dynamic analysis; Monitoring filtering techniques; multi-threaded programs; Efficiency;
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