• 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