Evaluating Ordering Heuristics for Dynamic Partial-Order Reduction Techniques

Lauterburg, Steven; Karmani, Rajesh K.; Marinov, Darko; Agha, Gul

doi:10.1007/978-3-642-12029-9_22

Cited by 40 publications

(44 citation statements)

References 21 publications

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“…Most related work is developed in the context of dynamic testing. The stream of papers devoted to further reduce the search space [1,10,18,22] is compatible with our work and the TCG framework can use the same algorithms and techniques, as we showed for the actor's stability of [3]. Dynamic symbolic execution consists in computing in parallel with symbolic execution a concrete test run.…”

Section: Related Work and Conclusionsupporting

confidence: 56%

“…This section reports on experimental results, which aim at demonstrating the applicability, effectiveness and impact of the proposed techniques during symbolic execution. The experiments have been performed using as benchmarks: (i) a set of classical actor programs borrowed from [18,21,22] and rewritten in ABS from ActorFoundry, and, (ii) some ABS models of typical concurrent systems. Specifically, QSort is a distributed version of the Quicksort algorithm, PSort is a modified version of the sorting algorithm used in the dCUTE study [21], RSim is a server registration simulation, DHT is a distributed hash table, Mail is an email client-server simulation, Cons resp.…”

Section: Implementation and Experimental Evaluationmentioning

confidence: 99%

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Test Case Generation of Actor Systems

Albert

Arenas

Gómez-Zamalloa

2015

Automated Technology for Verification and Analysis

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Abstract. Testing is a vital part of the software development process. It is even more so in the context of concurrent languages, since due to undesired task interleavings and to unexpected behaviours of the underlying task scheduler, errors can go easily undetected. Test case generation (TCG) is the process of automatically generating test inputs for interesting coverage criteria, which are then applied to the system under test. This paper presents a TCG framework for actor systems, which consists of three main elements, which are the original contributions of this work: (1) a symbolic execution calculus, which allows symbolically executing the program (i.e., executing the program for unknown input data), (2) improved techniques to avoid performing redundant computations during symbolic execution, (3) new termination and coverage criteria, which ensure the termination of symbolic execution and guarantee that the test cases provide the desired degree of code coverage. Finally, our framework has been implemented and evaluated within the aPET system.

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Section: Related Work and Conclusionsupporting

confidence: 56%

Section: Implementation and Experimental Evaluationmentioning

confidence: 99%

Test Case Generation of Actor Systems

Albert

Arenas

Gómez-Zamalloa

2015

Automated Technology for Verification and Analysis

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“…Our TransDPOR code is publicly available with Basset at http://mir.cs.illinois.edu/basset. We compare TransD-POR and DPOR (we previously adapted the original DPOR algorithm to work for actor systems [18]) on eight programs without bugs and three programs with bugs. The experimental results show that TransDPOR reduces the number of transitions executed during state space exploration by 2.39x on average and up to 163.80x over DPOR.…”

Section: Introductionmentioning

confidence: 99%

“…Our recent work [18] shows that the effectiveness of DPOR techniques is highly sensitive to the order in which messages are explored. However, one cannot easily determine before the exploration which order will work the best.…”

mentioning

confidence: 99%

TransDPOR: A Novel Dynamic Partial-Order Reduction Technique for Testing Actor Programs

Tasharofi

Karmani

Lauterburg

et al. 2012

Formal Techniques for Distributed Systems

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111

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Abstract. To detect hard-to-find concurrency bugs, current tools systematically explore all possible interleavings of the transitions in a program. Unfortunately, concurrent programs have a large number of possible interleavings due to nondeterminism. Speeding up such tools requires pruning the state space explored. Partial-order reduction (POR) techniques can substantially prune the number of explored interleavings. These techniques require defining a dependency relation on transitions in the program, and exploit independency among certain transitions to prune the state space. We observe that actor systems, a prevalent class of programs where computation entities communicate by exchanging messages, exhibit a dependency relation among co-enabled transitions with an interesting property: transitivity. This paper introduces a novel dynamic POR technique, TransDPOR, that exploits the transitivity of the dependency relation in actor systems. Empirical results show that leveraging transitivity speeds up exploration by up to two orders of magnitude compared to existing POR techniques.

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“…Recently, TransDPOR [16] extends DPOR to take advantage of the transitive dependency relations in actor systems to explore fewer configurations than DPOR. As noticed in [12,16], their effectiveness highly depend on the actor selection order. Our work enhances these approaches with novel strategies and heuristics to further prune redundant state exploration, and that can be easily integrated within the aforementioned algorithms.…”

Section: Introductionmentioning

confidence: 97%

Actor- and Task-Selection Strategies for Pruning Redundant State-Exploration in Testing

Albert

Arenas

Gómez-Zamalloa

2014

Formal Techniques for Distributed Objects, Components, and Systems

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Abstract. Testing concurrent systems requires exploring all possible non-deterministic interleavings that the concurrent execution may have. This is because any of the interleavings may reveal the erroneous behaviour. In testing of actor systems, we can distinguish two sources of non-determinism: (1) actor-selection, the order in which actors are explored and (2) task-selection, the order in which the tasks within each actor are explored. This paper provides new strategies and heuristics for pruning redundant state-exploration when testing actor systems by reducing the amount of unnecessary non-determinism. First, we propose a method and heuristics for actor-selection based on tracking the amount and the type of interactions among actors. Second, we can avoid further redundant interleavings in task-selection by taking into account the access to the shared-memory that the tasks make.

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Evaluating Ordering Heuristics for Dynamic Partial-Order Reduction Techniques

Cited by 40 publications

References 21 publications

Test Case Generation of Actor Systems

Test Case Generation of Actor Systems

TransDPOR: A Novel Dynamic Partial-Order Reduction Technique for Testing Actor Programs

Actor- and Task-Selection Strategies for Pruning Redundant State-Exploration in Testing

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