Title :
An improved quantum genetic algorithm for test suite reduction
Author :
Zhang, Yi-kun ; Liu, Ji-ceng ; Cui, Ying-an ; Hei, Xin-hong ; Zhang, Ming-hui
Author_Institution :
Sch. of Comput. Sci. & Eng., XAUT, Xi´´an, China
Abstract :
Test suite reduction is necessary to reduce the testing cost and increase efficiency, therefore, test suite reduction model is proposed, and test suite reduction problem is converted into a standard optimization problem. Additionally, an improved evolutionary algorithm is also proposed, which encodes the chromosome with quantum bit as its basic information bit. It achieves the individual evolution by improving the quantum rotating gates using adaptive rotation, and its convergence speed and global optimization ability is superior to the traditional evolutionary algorithm. Motivated by this, we propose a novel test suite reduction method using quantum evolutionary. Finally, experiments validate the technology with higher efficiency.
Keywords :
convergence; genetic algorithms; program testing; quantum gates; adaptive rotation; chromosome encoding; convergence speed; global optimization ability; quantum bit; quantum evolutionary; quantum genetic algorithm; quantum rotating gates; standard optimization problem; test suite reduction model; testing cost reduction; Biological cells; Convergence; Genetic algorithms; Logic gates; Quantum computing; Quantum entanglement; Testing; Quantum chromosome; Quantum genetic algorithm; Quantum rotating gates; Test suite reduction;
Conference_Titel :
Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-8727-1
DOI :
10.1109/CSAE.2011.5952443