Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/13798
Title: Automatic, evolutionary test data generation for dynamic software testing
Authors: Andreou, Andreas S. 
Sofokleous, Anastasis A. 
Major Field of Science: Engineering and Technology
Field Category: Electrical Engineering - Electronic Engineering - Information Engineering
Keywords: Software testing;Automatic test cases generation;Genetic algorithms
Issue Date: Nov-2008
Source: Journal of Systems and Software, 2008, vol. 81, no. 11, pp. 1883-1898
Volume: 81
Issue: 11
Start page: 1883
End page: 1898
Journal: Journal of Systems and Software 
Abstract: This paper proposes a dynamic test data generation framework based on genetic algorithms. The framework houses a Program Analyser and a Test Case Generator, which intercommunicate to automatically generate test cases. The Program Analyser extracts statements and variables, isolates code paths and creates control flow graphs. The Test Case Generator utilises two optimisation algorithms, the Batch-Optimistic (BO) and the Close-Up (CU), and produces a near to optimum set of test cases with respect to the edge/condition coverage criterion. The efficacy of the proposed approach is assessed on a number of programs and the empirical results indicate that its performance is significantly better compared to existing dynamic test data generation methods.
URI: https://hdl.handle.net/20.500.14279/13798
ISSN: 01641212
DOI: 10.1016/j.jss.2007.12.809
Rights: © 2008 Elsevier
Type: Article
Affiliation : University of Cyprus 
Appears in Collections:Άρθρα/Articles

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