222 A Review on Using of Quantum Calculation Techniques in Optimization of the Data System of Mutation Test and its Comparison with Normal Genetic Algorithm and Bacteriological

The science of quantum information is a class of calculation that's the result of a tie between Quantum Physics and Computer Science. Observing and studying the single quantum objects, is the basis of quantum calculations because these quantum items can be used as physical locations of quantum bits. In the quantum calculations, the basis that we introduce is the q-bit. The concept of quantum parallelism leads to development of quantum algorithm like the Shore Algorithm. These algorithms, using the new mechanisms and using the abilities of quantum mechanics can solve a great deal of problems more widely with more efficiency in comparison to classical algorithms. Such algorithms are very successful in doing repetitive calculations to decode the codes. Usually in order to optimize the development of test data is evolutionary algorithms are used. In this research, we are going to develop the efficiency of this mutation test optimization algorithms that's used in the optimizer segment. Then, we want to make a comparison with common optimizer algorithms such as usual genetics and bacteriological. In the end, we want to reduce some of the problems including getting stuck in the local minimums.