Title :
Genetic Algorithm Based on Software Diagnosis Testing
Author :
Yang Shunkun ; Zeng Fuping ; Yan Lin
Author_Institution :
Sch. of Reliability & Syst. Eng., Beihang Univ., Beijing, China
Abstract :
Based on genetic algorithm, the problem of software diagnosis testing is considered in this paper to reproduce the failure for the kind of systems with multi-input/output variables. Firstly, the problem prototype is abstracted, and then solutions to the prototype problems are introduced. From the aspects of coding scheme, population initialization, genetic operation, selection of fitness function, and convergence criterion, etc., how genetic algorithm can be applied in such prototype problem as software fault reproduction is thoroughly described. The experimental result shows that the injected software failure can be reproduced rapidly in the given program.
Keywords :
genetic algorithms; program diagnostics; program testing; software fault tolerance; genetic algorithm; multi-input/output variables; prototype problem; software diagnosis testing; software fault reproduction; Encoding; Genetic algorithms; Genetics; Prototypes; Software; Testing; Vectors; fault diagnosis; genetic algorithm; software testing;
Conference_Titel :
Information Technology, Computer Engineering and Management Sciences (ICM), 2011 International Conference on
Conference_Location :
Nanjing, Jiangsu
Print_ISBN :
978-1-4577-1419-1
DOI :
10.1109/ICM.2011.291