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Original scientific paper

https://doi.org/10.17559/TV-20170319045945

Large scale software test data generation based on collective constraint and weighted combination method

Dalin Zhang orcid id orcid.org/0000-0003-0346-7020 ; National Research Center of Railway Safety Assessment, Beijing Jiaotong University, Beijing, China
Jianwei Sui ; State Key Laboratory of Networking and Switching, University of Posts and Telecommunications, Beijing, China
Yunzhan Gong ; State Key Laboratory of Networking and Switching, University of Posts and Telecommunications, Beijing, China


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Abstract

Software reliability test is to test software with the purpose of verifying whether the software achieves reliability requirements and evaluating software reliability level. Statistical-based software reliability testing generally includes three parts: building usage model, test data generation and testing. The construction of software usage model should reflect user's real use as far as possible. A huge number of test cases are required to satisfy the probability distribution of the actual usage situation; otherwise, the reliability test will lose its original meaning. In this paper, we first propose a new method of structuring software usage model based on modules and constraint-based heuristic method. Then we propose a method for the testing data generation in consideration of the combination and weight of the input data, which reduces a large number of possible combinations of input variables to a few representative ones and improves the practicability of the testing method. To verify the effectiveness of the method proposed in this paper, four groups of experiments are organized. The goodness of fit index (GFI) shows that the proposed method is closer to the actual software use; we also found that the method proposed in this paper has a better coverage by using Java Pathfinder to analyse the four sets of internal code coverage.

Keywords

constraint; data generation; GFI; software reliability testing; usage model; weighted combination

Hrčak ID:

185493

URI

https://hrcak.srce.hr/185493

Publication date:

31.7.2017.

Article data in other languages: croatian

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