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Neural Computing and Applications

Erschienen in:

01.12.2014 | Original Article

An approach for test data generation using program slicing and particle swarm optimization

verfasst von: Shujuan Jiang, Dandan Yi, Xiaolin Ju, Lingsai Wang, Yingqi Liu

Erschienen in: Neural Computing and Applications | Ausgabe 7-8/2014

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Abstract

Heuristic search-based test data generation has a potential higher efficiency in software testing with path covering. However, these approaches are suffered in covering the long and complex path. In this paper, we propose a method for generating test data based on program slicing and particle swarm optimization. With the interest points selected from a target path, we perform a program slicing to remove the statements which are irrelevant to the interest points. Our method simplifies the target path and the actual path to get a better fitness value. After program slices obtained, the population is evolved using particle swarm optimization to improve the efficiency of test data generation.

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Titel: An approach for test data generation using program slicing and particle swarm optimization
verfasst von: Shujuan Jiang
Dandan Yi
Xiaolin Ju
Lingsai Wang
Yingqi Liu
Publikationsdatum: 01.12.2014
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 7-8/2014
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-014-1692-z

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