Detecting Data Races in Sequential Programs with DIOTA

Ronsse, Michiel; Maebe, Jonas; Bosschere, Koenraad De

doi:10.1007/978-3-540-27866-5_11

Cited by 7 publications

(3 citation statements)

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“…Concurrency bugs are generally associated with multithreaded programs. However, researchers have shown that they also exist in sequential [14], interrupt-driven [15], and event-based programs [16]. The execution of signal-handlers, interrupt-handlers, and other asynchronously invoked eventhandlers interrupts the control flow of these programs and so introduces fine-grained concurrency.…”

Section: Replay Analysis For Diagnosing Concurrency Bugsmentioning

confidence: 99%

“…Unfortunately, no such bug database is available for sequential or event-based programs. We evaluated our proposed model of diagnosing concurrency bugs on a few real bugs caused by data races in concurrent signal-handlers reported in [14,27] as well as some other programs. Here, we discuss only three case studies, but we believe that these results are representative for the large domain of concurrency bugs in Linux programs.…”

Section: Debug Case Studiesmentioning

confidence: 99%

“…Ronsse et al [14] presented a method for detecting data races in sequential programs by adapting their existing data race detector for multithreaded programs. They use their dynamic instrumentation framework DIOTA to instrument and record all memory operations during runtime and to perform race detection during replayed execution.…”

Section: Diagnosing Concurrency Bugsmentioning

confidence: 99%

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Debugging Nondeterministic Failures in Linux Programs through Replay Analysis

Majeed

Ryu

2018

Scientific Programming

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Reproducing a failure is the first and most important step in debugging because it enables us to understand the failure and track down its source. However, many programs are susceptible to nondeterministic failures that are hard to reproduce, which makes debugging extremely difficult. We first address the reproducibility problem by proposing an OS-level replay system for a uniprocessor environment that can capture and replay nondeterministic events needed to reproduce a failure in Linux interactive and event-based programs. We then present an analysis method, called replay analysis, based on the proposed record and replay system to diagnose concurrency bugs in such programs. The replay analysis method uses a combination of static analysis, dynamic tracing during replay, and delta debugging to identify failure-inducing memory access patterns that lead to concurrency failure. The experimental results show that the presented record and replay system has low-recording overhead and hence can be safely used in production systems to catch rarely occurring bugs. We also present few concurrency bug case studies from real-world applications to prove the effectiveness of the proposed bug diagnosis framework.

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Section: Replay Analysis For Diagnosing Concurrency Bugsmentioning

confidence: 99%

Section: Debug Case Studiesmentioning

confidence: 99%

Section: Diagnosing Concurrency Bugsmentioning

confidence: 99%

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