改进的遗传算法及其在测试数据自动生成中的应用

Improved Genetic Algorithm and its Application in Test Data Automatic Generation

传统遗传算法在测试数据生成方面是一种实用的算法,但是其自身存在局限性,如过早收敛、优化效率低等。本文对遗传算法的自改进、与其他智能优化算法的混合改进方法以及改进后的算法在测试数据自动生成方面的能力的国内外研究现状进行了系统的研究与讨论,最后分析了相关算法改进的实质。

Traditional genetic algorithm is a kind of practical algorithm in test data generation. However, some inherent limitations of this algorithm exist, such as premature convergence, low optimization efficiency, etc. In this paper, the domestic and foreign researches of the self- improvement of traditional genetic algorithm, hybrid optimization algorithms which are based on combination of other intelligent optimization algorithms and the genetic algorithm and the abilities of automatic generating test data are systematic studied and presented.At last,the essence of the related algorithms improving is analyzed.