High-coverage, unbounded sound predictive race detection

Roemer, Jake; Genç, Kaan; Bond, Michael D.

doi:10.1145/3192366.3192385

Cited by 25 publications

(41 citation statements)

References 78 publications

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“…Benchmarks. Our benchmark set is a standard one found in recent works on race detection (Huang et al 2014;Kini et al 2017;Mathur et al 2018;Yu et al 2018), and parts of it also exist in other works (Bond et al 2010;Flanagan and Freund 2009;Roemer et al 2018;Zhai et al 2012). It contains concurrent traces of various sizes, which are concrete executions of concurrent programs taken from standard benchmark suits: (i) the IBM Contest benchmark suite (Farchi et al 2003), (ii) the Java Grande forum benchmark suite (Smith et al 2001), (iii) the DaCapo benchmark suite (Blackburn et al 2006), and (iv) some standalone, real-world so ware.…”

Section: Methodsmentioning

confidence: 99%

“…We make a prototype implementation of our practical algorithm and evaluate it on a standard set of benchmark traces that contain hundreds of millions of events. We compare the performance of our tool against state-of-the-art, polynomial-time, partial-order-based methods, namely the HB (Lamport 1978), WCP (Kini et al 2017), DC (Roemer et al 2018) and SHB (Mathur et al 2018) methods. Our approach detects signi cantly more races than each of these methods, while it has comparable running time, and typically being faster.…”

Section: Our Contributionsmentioning

confidence: 99%

“…Indeed, this modeling approach has been taken in many other works, as e.g. in (Kini et al 2017;Mathur et al 2018;Roemer et al 2018;Smaragdakis et al 2012).…”

Section: Preliminariesmentioning

confidence: 99%

“…As HB is highly incomplete, there have been several e orts for constructing weaker partial orders that are e ciently computable, such as the causally-precedes partial order CP (Smaragdakis et al 2012). Partial-order techniques recently led to important advances in predictive race detection, based on the weakly-causally-precedes WCP (Kini et al 2017), schedulably-happens-before SHB (Mathur et al 2018) and doesn't-commute DC (Roemer et al 2018) partial orders. We next discuss these approaches in more detail and outline the motivation behind our work.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Fast, sound, and effectively complete dynamic race prediction

Pavlogiannis

2019

Proc. ACM Program. Lang.

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Writing concurrent programs is highly error-prone due to the nondeterminism in interprocess communication.e most reliable indicators of errors in concurrency are data races, which are accesses to a shared resource that can be executed concurrently. We study the problem of predicting data races in lock-based concurrent programs. e input consists of a concurrent trace t, and the task is to determine all pairs of events of t that constitute a data race. e problem lies at the heart of concurrent veri cation and has been extensively studied for over three decades. However, existing polynomial-time sound techniques are highly incomplete and can miss simple races.In this work we develop M2: a new polynomial-time algorithm for this problem, which has no false positives. In addition, our algorithm is complete for input traces that consist of two processes, i.e., it provably detects all races in the trace. We also develop su cient criteria for detecting completeness dynamically in cases of more than two processes. We make an experimental evaluation of our algorithm on a challenging set of benchmarks taken from recent literature on the topic. Our algorithm soundly reports hundreds of real races, many of which are missed by existing methods. In addition, using our dynamic completeness criteria, M2 concludes that it has detected all races in the benchmark set, hence the reports are both sound and complete. Finally, its running times are comparable, and o en smaller than the theoretically fastest, yet highly incomplete, existing methods. To our knowledge, M2 is the rst sound algorithm that achieves such a level of performance on both running time and completeness of the reported races. CCS Concepts: •So ware and its engineering → So ware veri cation and validation; • eory of computation → eory and algorithms for application domains; Program analysis; Additional

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Section: Methodsmentioning

confidence: 99%

Section: Our Contributionsmentioning

confidence: 99%

“…Indeed, this modeling approach has been taken in many other works, as e.g. in (Kini et al 2017;Mathur et al 2018;Roemer et al 2018;Smaragdakis et al 2012).…”

Section: Preliminariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fast, sound, and effectively complete dynamic race prediction

Pavlogiannis

2019

Proc. ACM Program. Lang.

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“…Vector clocks have been very useful in designing linear time algorithms for dynamic analysis of multi-threaded systems [14,23,24,27,43,50,52]. The broad principle behind these algorithms, is to assign vector timestamps to events as the trace is generated/observed so that the ordering between these assigned timestamps captures causal ordering.…”

Section: Challenges In Designing a Vector Clock Algorithmmentioning

confidence: 99%

Atomicity Checking in Linear Time using Vector Clocks

Mathur

Viswanathan

2020

Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Syste

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Multi-threaded programs are challenging to write. Developers often need to reason about a prohibitively large number of thread interleavings to reason about the behavior of software. A non-interference property like atomicity can reduce this interleaving space by ensuring that any execution is equivalent to an execution where all atomic blocks are executed serially. We consider the well studied notion of conflict serializability for dynamically checking atomicity. Existing algorithms detect violations of conflict serializability by detecting cycles in a graph of transactions observed in a given execution. The number of edges in such a graph can grow quadratically with the length of the trace making the analysis not scalable. In this paper, we present AeroDrome, a novel single pass linear time algorithm that uses vector clocks to detect violations of conflict serializability in an online setting. Experiments show that AeroDrome scales to traces with a large number of events with significant speedup. CCS Concepts. • Software and its engineering → Dynamic analysis; Software testing and debugging.

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Efficient noise injection for exposing hidden data races

Bae

2019

J Supercomput

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The happens-before (HB) relation is widely used to precisely detect data races, which are among the major causes of concurrency bugs. However, the HB relation is sensitive to thread interleaving; thus, hidden races that can be revealed in other thread interleavings may remain despite the repeated running of a program with an HB detector. In this paper, we propose a noise injection-based race detection technique (RaceInducer) that can expose and detect hidden races by using the runtime HB analysis result to determine the noise injection instants. RaceInducer delays a thread execution after the occurrence of the first no-lock non-racing accesses of three types (read-exclusive, write-exclusive, and read-shared) to a shared variable during a precise HB detection (FastTrack). Using this technique, RaceInducer can efficiently disturb the normal locking sequences between two threads that generate HB edges hiding data races. We implemented RaceInducer on the RoadRunner instrumentation framework for Java and evaluated its detection capability and runtime overheads on 12 real-world benchmark programs. The evaluation results showed that RaceInducer generated a lower runtime overhead compared to random noise injection that randomly injected noise for no-lock non-racing accesses and can detect more races with the same noise strength. RaceInducer generates particularly lower runtime overhead than the random noise injection for large programs that generates a high number of shared-memory accesses. In addition, we experimentally demonstrated that RaceInducer incurred lower runtime overheads than a current hidden-race detector (DrFinder) for programs with a relatively large number of locking operations.

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High-coverage, unbounded sound predictive race detection

Cited by 25 publications

References 78 publications

Fast, sound, and effectively complete dynamic race prediction

Fast, sound, and effectively complete dynamic race prediction

Atomicity Checking in Linear Time using Vector Clocks

Efficient noise injection for exposing hidden data races

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