Advances in noise‐based testing of concurrent software

Fiedor, Jan; Hrubá, Vendula; Křena, Bohuslav; Letko, Zdeněk; Ur, Shmuel; Vojnar, Tomáš

doi:10.1002/stvr.1546

Cited by 11 publications

(11 citation statements)

References 64 publications

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“…As future work, other concurrent coverage criteria, e.g., [11], [13], [14] can be incorporated within the framework to characterize the test case diversity for multithreaded programs. From the experience in [4], domainspecific knowledge can be taken into account to further improve the inherent overhead in test input selection for multithreaded programs.…”

Section: Discussionmentioning

confidence: 99%

“…Empirical studies [14], [23] indicate moderate to strong correlations between coverage criteria and the test effectiveness and efficiency of active testing approaches. This lays a solid foundation for our coverage-based test case diversity metric.…”

Section: Related Workmentioning

confidence: 95%

“…Three categories of testing approaches have been developed for concurrent programs: stress testing [5], systematic testing [6]- [8] and active testing [9]- [14]. Analogously speaking, these testing approaches focus mainly on thread interleaving selection strategies, but not test input selection strategies.…”

Section: Introductionmentioning

confidence: 99%

“…Effective coverage criteria [11]- [14] have been proposed to determine whether the predicted thread interleavings are sufficient enough for spotting concurrency bugs. If no more thread interleavings can be located under one input, another input can be used to continue active testing until certain coverage criterion is met.…”

Section: Introductionmentioning

confidence: 99%

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Input-Driven Active Testing of Multi-threaded Programs

Han

Chen

et al. 2015

2015 Asia-Pacific Software Engineering Conference (APSEC)

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It is still a challenge to select "good" test inputs for concurrent programs within limited testing resources. We present in this paper a test case diversity metric for multi-threaded programs, which evaluates a test input with its effect in exposing concurrent thread interactions. We then propose an input-driven active testing approach with two test input selection strategies based on our test case diversity metric. We implement our testing approach based on Maple, an interleaving coverage-driven active testing tool. The effectiveness and efficiency of our testing approach are compared closely with Maple, which on its own is supplied with random test inputs. Experimental results show that our testing approach can outperform the original active testing approach in the number of test inputs executed and the time usage for fulfilling the interleaving coverage criterion of Maple. The selected test inputs based on our test case diversity metric are very cost-effective in exposing concurrent thread interactions and hence can help detect concurrency bugs with less cost and effort.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Input-Driven Active Testing of Multi-threaded Programs

Han

Chen

et al. 2015

2015 Asia-Pacific Software Engineering Conference (APSEC)

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“…The explosion of synchronization sequences in the testing of concurrent programs is similar to those found in model checking (GODEFROID; KHURSHID, 2004), in which different paths must be covered, and meta-heuristics are applied to solve it. In noise injection testing technique (FIEDOR et al, 2015) meta-heuristics are used to search the amount of noise should be inserted in a program and the best place to insert it during the execution to make the program follows different synchronization sequences. However, meta-heuristics were not applied to generate synchronization sequences.…”

Section: Motivationmentioning

confidence: 99%

Search based software testing for the generation of synchronization sequences for mutation testing of concurrent programs

Silva¹

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Firstly, I would like to thank God for the possibility to live every day with happiness and motivation. I would like to thank my family: my parents and to my brother and sister for supporting me throughout this PH.D. and all my life in general. Besides that, thank you for believing in my potential more than myself sometimes. I would like to express my sincere gratitude to my advisor Prof. Dr. Simone do Rocio Senger de Souza for the continuous support of my Ph.D. study, for her attention, availability, help and, mainly, for her patience. Her guidance helped me during this research and writing of this thesis. Also, I would like Prof. Dr. Paulo Sergio Lopes de Souza for the comments, encouragement, support and contribution to this research. My sincere thanks also go to Prof. Dr. Gordon Fraser who provided me an opportunity to join their team as an intern at the University of Sheffield, and who gave me access to the laboratory and research facilities. Thank you for your support and advice. His precious support during the internship was crucial for the results present in this thesis. I want to thank all the friends I made in Sheffield that helped me to feel more comfortable there and showed me how tasty is the meat pie at The Old House.

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Boosted decision trees for behaviour mining of concurrent programmes

Avros

Dudka

Křena

et al. 2017

Concurrency and Computation

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SummaryTesting of concurrent programmes is difficult since the scheduling nondeterminism requires one to test a huge number of different thread interleavings. Moreover, repeated test executions that are performed in the same environment will typically examine similar interleavings only. One possible way how to deal with this problem is to use the noise injection approach, which influences the scheduling by injecting various kinds of noise (delays, context switches, etc) into the common thread behaviour. However, for noise injection to be efficient, one has to choose suitable noise injection heuristics from among the many existing ones as well as to suitably choose values of their various parameters, which is not easy. In this paper, we propose a novel way how to deal with the problem of choosing suitable noise injection heuristics and suitable values of their parameters (as well as suitable values of parameters of the programmes being tested themselves). Here, by suitable, we mean such settings that maximize chances of meeting a given testing goal (such as, eg, maximizing coverage of rare behaviours and thus maximizing chances to find rarely occurring concurrency‐related bugs). Our approach is, in particular, based on using data mining in the context of noise‐based testing to get more insight about the importance of the different heuristics in a particular testing context as well as to improve fully automated noise‐based testing (in combination with both random as well as genetically optimized noise setting).

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Advances in noise‐based testing of concurrent software

Cited by 11 publications

References 64 publications

Input-Driven Active Testing of Multi-threaded Programs

Input-Driven Active Testing of Multi-threaded Programs

Search based software testing for the generation of synchronization sequences for mutation testing of concurrent programs

Boosted decision trees for behaviour mining of concurrent programmes

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