A Software Debugging Method Based on Pairwise Testing

Shi, Liang; Nie, Changhai; Xu, Bin

doi:10.1007/11428862_179

Cited by 29 publications

(29 citation statements)

References 5 publications

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“…In 2007 a Boolean satisfiability (SAT) solver has been introduced to handle Cohen DM et al [3] Cohen MB et al [8] Grindal et al [27] Kuhn et al [5] Nie et el. [32] Schroeder et al [26] constraints in a greedy [18] as well as an SA-based algorithm [7]. However, only in 2011 improvements introduced by Garvin et al [4] allowed for efficient constraint handling in an SA-based algorithm for covering array generation.…”

Section: Related Workmentioning

confidence: 97%

Practical Combinatorial Interaction Testing: Empirical Findings on Efficiency and Early Fault Detection

Petke

Cohen

Harman

et al. 2015

IIEEE Trans. Software Eng.

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Combinatorial Interaction Testing (CIT) is important because it tests the interactions between the many features and parameters that make up the configuration space of software systems. Simulated Annealing (SA) and Greedy Algorithms have been widely used to find CIT test suites. From the literature, there is a widely-held belief that SA is slower, but produces more effective tests suites than Greedy and that SA cannot scale to higher strength coverage. We evaluated both algorithms on 7 real-world subjects for the well-studied 2-way up to the rarely-studied 6-way interaction strengths. Our findings present evidence to challenge this current orthodoxy: real-world constraints allow SA to achieve higher strengths. Furthermore, there was no evidence that Greedy was less effective (in terms of time to fault revelation) compared to SA; the results for the greedy algorithm are actually slightly superior. However, the results are critically dependent on the approach adopted to constraint handling. Moreover, we have also evaluated a genetic algorithm for constrained CIT test suite generation. This is the first time strengths higher than 3 and constraint handling have been used to evaluate GA. Our results show that GA is competitive only for pairwise testing for subjects with a small number of constraints.

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Section: Related Workmentioning

confidence: 97%

Practical Combinatorial Interaction Testing: Empirical Findings on Efficiency and Early Fault Detection

Petke

Cohen

Harman

et al. 2015

IIEEE Trans. Software Eng.

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“…In previous works, an adaptive interaction fault location (we name it as AIFL) method, which adopts the delta debugging strategy [15] to locate interaction faults, have been proposed in [12]. It is also the first step of the iterative technique that will be proposed in this paper.…”

Section: A Previous Methodsmentioning

confidence: 99%

“…Colbourn and McClary proposed a non-adaptive method [13], which has a limitation that the predication of faults must be given firstly. Shi, Nie, and Xu proposed an adaptive method [12], which has a limitation that the precision score is not high enough for many circumstances. The methods that described in this paper belong to adaptive methods, and they have a higher precision score than existed adaptive method.…”

Section: Related Workmentioning

confidence: 99%

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Adaptive Interaction Fault Location Based on Combinatorial Testing

Wang

Chen

et al. 2010

2010 10th International Conference on Quality Software

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Combinatorial testing aims to detect interaction faults, which are triggered by interaction among parameters in system, by covering some specific combinations of parametric values. Most works about combinatorial testing focus on detecting such interaction faults rather than locating them. Based on the model of interaction fault schema, in which the interaction fault is described as a minimum fault schema and several corresponding parent-schemas, we propose an iterative adaptive interaction fault location technique for combinatorial testing. In order to locate interaction faults that detected in combinatorial testing, such technique utilizes delta debugging strategy to filtrate suspicious schemas by generating and running additional test cases iteratively. The properties, which include both recall and precision, of adaptive interaction fault location techniques are also analyzed in this paper. Analytical results suggest that the high scores in both recall and precision are guaranteed. It means that such technique can provide an efficient guidance for the applications of combinatorial testing.

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“…Some integrated tools have been developed to generate a minimal test suite T c . We have developed a tool named CTD (CT and Diagnosis) [Nie et al 2006a;Shi et al 2005].…”

Section: Design a Proper Test Suite T Cmentioning

confidence: 99%

The Minimal Failure-Causing Schema of Combinatorial Testing

Nie

Leung

2011

ACM Trans. Softw. Eng. Methodol.

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Combinatorial Testing (CT) involves the design of a small test suite to cover the parameter value combinations so as to detect failures triggered by the interactions among these parameters. To make full use of CT and to extend its advantages, this article first gives a model of CT and then presents a theory of the Minimal Failure-causing Schema (MFS), including the concept of the MFS, proof of its existence, some of its properties, and a method of finding the MFS. Then we propose a methodology for CT based on this MFS theory and the existing research. Our MFS-based methodology emphasizes that CT should work on accurate testing requirements, and has the following advantages: 1) Detect failure to the greatest degree with the least cost. 2) Effectiveness is improved by emphasizing mining of the information in software and making full use of the information gained from test design and execution. 3) Determine the root causes of failures and reveal related faults near the exposed ones. 4) Provide a foundation and model for regression testing and software quality evaluation of CT. A case study is presented to illustrate the MFS-based CT methodology, and an empirical study on a real software developed by us shows that the MFS really exists and the methodology based on MFS can considerably improve CT.

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A Software Debugging Method Based on Pairwise Testing

Cited by 29 publications

References 5 publications

Practical Combinatorial Interaction Testing: Empirical Findings on Efficiency and Early Fault Detection

Practical Combinatorial Interaction Testing: Empirical Findings on Efficiency and Early Fault Detection

Adaptive Interaction Fault Location Based on Combinatorial Testing

The Minimal Failure-Causing Schema of Combinatorial Testing

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