Parallel testing of distributed software

Lastovetsky, Alexey

doi:10.1016/j.infsof.2004.11.006

Cited by 19 publications

(11 citation statements)

References 8 publications

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“…However, analyses under such circumstances can be impractical due to numbers of test cases or the fault space, particularly in the case of simultaneous fault models that demand consideration of fault combinations. Research has addressed these problems through leveraging parallel architectures in the execution of the large number of fault injection experiments [12], [13], though more scalable techniques have focused on sampling strategies for the test cases and error spaces [14], [15], [16].…”

Section: Related Workmentioning

confidence: 99%

Simultaneous Fault Models for the Generation of Efficient Error Detection Mechanisms

Leeke

2017

2017 IEEE 28th International Symposium on Software Reliability Engineering (ISSRE)

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Section: Related Workmentioning

confidence: 99%

Simultaneous Fault Models for the Generation of Efficient Error Detection Mechanisms

Leeke

2017

2017 IEEE 28th International Symposium on Software Reliability Engineering (ISSRE)

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“…Alexey lastovetsky [2] focused on using parallel computing technologies to accelerate the testing of a complex distributed software system.Cyril Briquet [3] supported on evaluating the performance of scheduling algorithms. Performance is evaluated experimentally or through simulation.…”

Section: Related Workmentioning

confidence: 99%

Task Scheduling of a Distributed Computing Software in the Presence of Faults

Mishra¹,

Tripathi²

2013

IJCA

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Performance estimation of a distributed software is a challenging problem. A distributed software runs on multiple processing nodes interconnected in some fashion. In such a situation computational load of a software is distributed onto the processing nodes of the given system. Such a system makes use of an appropriate task scheduling algorithm for obtaining a good performance. The program used in this work emulates a distributed system . An emulator gives the result like an actual system. The emulator is of a fully connected distributed system in which any two processors can directly communicate. The objective of this experiment is to identify the task scheduling algorithm that also performs well in the presence of communication fault delay occured because of network failure or computation fault delay occured because of no response from processors in a distributed system.

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“…In the case study presented by Lastovetsky and Alexey [25] it was shown that parallelizing regression testing for a distributed programming system resulted in a speed up of up to 7.7 on two 4-processor workstations.…”

Section: Parallel Execution Of Testingmentioning

confidence: 99%

A Parallel Genetic Algorithm Based on Hadoop MapReduce for the Automatic Generation of JUnit Test Suites

Geronimo

Ferrucci

Murolo

et al. 2012

2012 IEEE Fifth International Conference on Software Testing, Verification and Validation

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Abstract-Software testing represents one of the most explored fields of application of Search-Based techniques and a range of testing problems have been successfully addressed using Genetic Algorithms. Nevertheless, to date Search-Based Software Testing (SBST) has found limited application in industry. As in other fields of Search-Based Software Engineering, this is principally due to the fact that when applied to large problems, Search-Based approaches may require too much computational efforts. In this scenario, parallelization may be a suitable way to improve the performance especially due to the fact that many of these techniques are "naturally parallelizable". Nevertheless, very few attempts have been provided for SBST parallelization. In this paper, we present a Parallel Genetic Algorithm for the automatic generation of test suites. The solution is based on Hadoop MapReduce since it is well supported to work also in the cloud and on graphic cards, thus being an ideal candidate for high scalable parallelization of Genetic Algorithms. A preliminary analysis of the proposal was carried out aiming to evaluate the speed-up with respect to the sequential execution. The analysis was based on a real world open source library.

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Parallel testing of distributed software

Cited by 19 publications

References 8 publications

Simultaneous Fault Models for the Generation of Efficient Error Detection Mechanisms

Simultaneous Fault Models for the Generation of Efficient Error Detection Mechanisms

Task Scheduling of a Distributed Computing Software in the Presence of Faults

A Parallel Genetic Algorithm Based on Hadoop MapReduce for the Automatic Generation of JUnit Test Suites

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