Title :
Strategy for mutation testing using genetic algorithms
Author :
Masud, Md Mehedi ; Nayak, Amiya ; Zaman, Marzia ; Bansal, Nita
Author_Institution :
SITE, Ottawa Univ., Ont.
Abstract :
In this paper, we propose a model to reveal faults and kill mutant using genetic algorithms. The model first instruments the source and mutant program and divides in small units. Instead of checking the entire program, it tries to find fault in each unit or kills each mutant unit. If any unit survives, the new test data is generated using genetic algorithm with special fitness function. The output of each test for each unit is recorded to detect the faulty unit. In this strategy, the source program and the mutant are instrumented in such a way that the input and output behavior of each unit can be traced. A checker module is used to compare and trace the output of each unit. A complete architecture of the model is proposed in the paper
Keywords :
genetic algorithms; program testing; software fault tolerance; checker module; fitness function; genetic algorithms; mutation testing; Automatic testing; Computer architecture; Computer bugs; Fault detection; Genetic algorithms; Genetic mutations; Instruments; Performance evaluation; Software testing; System testing;
Conference_Titel :
Electrical and Computer Engineering, 2005. Canadian Conference on
Conference_Location :
Saskatoon, Sask.
Print_ISBN :
0-7803-8885-2
DOI :
10.1109/CCECE.2005.1557156