The limitations of genetic algorithms in software testing

Software test-data generation is the process of identifying a set of data, which satisfies a given testing criterion. For solving this difficult problem there were a lot of research works, which have been done in the past. The most commonly encountered are random test-data generation, symbolic test-...

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Bibliographic Details
Main Authors: Aljahdali, Sultan H, Ghiduk, Ahmed S, El-Telbany, Mohammed
Format: Conference Proceeding
Language:English
Subjects:
Biological cells
Classification algorithms
genetic algorithms
Genetics
Optimization
Software
Software testing
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Summary:Software test-data generation is the process of identifying a set of data, which satisfies a given testing criterion. For solving this difficult problem there were a lot of research works, which have been done in the past. The most commonly encountered are random test-data generation, symbolic test-data generation, dynamic test-data generation, and recently, test-data generation based on genetic algorithms. This paper gives a survey of the majority of software test-data generation techniques based on genetic algorithms. It compares and classifies the surveyed techniques according to the genetic algorithms features and parameters. Also, this paper shows and classifies the limitations of these techniques.
ISSN:2161-5322
2161-5330
DOI:10.1109/AICCSA.2010.5586984