Genetic symbiosis algorithm generating test data for constraint automata

被引：0
|
作者：
Rezaee, Alireza [1 ,2 ]
机构：
[1] Buin Zahra Islamic Azad Univ, Tehran, Iran
[2] Amirkabir Univ Technol, Dept Elect Engn, Tehran, Iran
来源：
APPLIED AND COMPUTATIONAL MATHEMATICS | 2008年 / 7卷 / 01期
关键词：
constraint automata; automata testing; automatic test data generation; symbiotic evolutionary algorithms; genetic algorithms;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Constraint automata are a semantic model for XML modeling language. Testing correctness of mapping black-box components in XML to constraint automata is an important problem in analyzing the semantic model of XML and requires a collection of test data that cover different scenarios. In this paper, Genetic Algorithm (GA) is employed to generate such set of test cases. This test data generation is improved by Genetic Symbiosis Algorithms (GSA). The results show that GSA approach brings us a set of test data with full coverage of automata edges and states and also diversity of examined paths.
引用
收藏
页码：126 / 137
页数：12
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