Based on this brief statement, comment on the flaws, strengths, weaknesses, and/

Question

Based on this brief statement, comment on the flaws, strengths, weaknesses, and/or potential for future work.

In this paper a method has been proposed to optimize the software testing efficiency using Genetic Algorithm and Mutation Analysis. First a program is written and intended some mutant in this program and then found most critical path and optimized test cases using genetic algorithm. These test cases are refined using genetic algorithm. A mutant function has been used for measuring the adequacy of the test case sets. This mutant function find a mutant score, on the bases of this mutation function 100% path coverage and boundary coverage achieved using mutation testing.

Based on this brief statement, comment on the flaws, strengths, weaknesses, and/or potential for future work.

Explanation / Answer

Genetic algorithm is one such algorithm in evolutionary algorithm. GA is a search algorithm that is inspired by the way nature evolves species using natural selection of the fittest individuals. Franz Rothlauf [5] explains more about evolutionary algorithms like genetic algorithms. The possible solution to a problem is represented by the population of the chromosomes. A chromosome is a string of binary digits and each digit that makes up a chromosome is called a gene. The initial population can be totally random or can be created manually using processes such as greedy algorithm. GA uses three operators in its population namely: (i) Selection, (ii) Crossover and (iii) Mutation. .

A selection scheme is applied to determine how individuals are chosen for mating based on their fitness. Fitness can be defined as a capability of an individual to survive and reproduce in an environment. Selection generates the new population from the old one, thus starting a new generation. Each chromosome is evaluated in present generation to determine its fitness value. The fitness value is used to select the better chromosomes from the population for the next generation.

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