DocumentCode :
256407
Title :
PFinder: Efficiently detecting bugs in concurrent programs through parallelizing race verification
Author :
Zhendong Wu ; Kai Lu ; Xiaoping Wang ; Xu Zhou ; Chen Chen
Author_Institution :
Sci. & Technol. on Parallel & Distrib. Process. Lab., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2014
fDate :
22-23 Dec. 2014
Firstpage :
151
Lastpage :
156
Abstract :
Races hidden in concurrent programs can lead to harmful bugs. These bugs are difficult to detect due to their non-deterministic characteristics. Previous work has tried to dynamically verify races in actual executions to check whether they would lead to failures. However, it is inefficient to verify all the races to find the harmful bugs if there are a large number of races. To improve the efficiency, PFinder is the first technique that uses a parallel method to verify multiple races on multiple machines simultaneously. We have implemented PFinder as a prototype tool and have experimented on a number of real-world concurrent programs. All the known bugs in known benchmarks are detected. Also, PFinder could scale well as the number of machines increases. Additionally, the speedup of PFinder can be increased linearly with the number of machines.
Keywords :
concurrency (computers); parallel programming; program debugging; program verification; PFinder; bug detection; concurrent programs; multiple races verification; parallel method; parallelizing race verification; Field-flow fractionation; Lead; Oceans; concurrency bug detection; concurrent program; data race; harmful bug; parallel method; race verification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Engineering & Systems (ICCES), 2014 9th International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4799-6593-9
Type :
conf
DOI :
10.1109/ICCES.2014.7030948
Filename :
7030948
Link To Document :
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