DocumentCode :
2339274
Title :
The limitations of genetic algorithms in software testing
Author :
Aljahdali, Sultan H. ; Ghiduk, Ahmed S. ; El-Telbany, Mohammed
Author_Institution :
Coll. of Comput. & Inf. Sys, Taif Univ., Taif, Saudi Arabia
fYear :
2010
fDate :
16-19 May 2010
Firstpage :
1
Lastpage :
7
Abstract :
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.
Keywords :
genetic algorithms; program testing; dynamic test data generation; genetic algorithm; random test data generation; software test data generation; software testing; symbolic test data generation; Biological cells; Classification algorithms; Genetics; Optimization; Software; Software testing; genetic algorithms; software testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Systems and Applications (AICCSA), 2010 IEEE/ACS International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4244-7716-6
Type :
conf
DOI :
10.1109/AICCSA.2010.5586984
Filename :
5586984
Link To Document :
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