文件名称:liziqun
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分析了软件测试中测试用例自动生成技术的发展现状和粒子群优化算法的基本原理及实现步骤,并详细研究了几种重要的改进的粒子群优化算法。在此基础上,改进了基本粒子群优化算法,提出了基于改进的粒子群优化算法的测试用例自动生成系统框架,并给出了基于改进的粒子群优化算法的测试用例自动生成算法。
最后,采用matlab语言编程实现了基于改进的粒子群优化算法的测试用例自动生成算法,用具体实例对其进行了实验,并对结果数据进行了分析。
本文提出的基于改进的粒子群优化算法的测试用例自动生成算法具有简单、易实现、设置参数少和收敛速度快等特点。
实验结果表明,使用本文提出的算法测试用例自动生成的效果明显优于遗传算法等测试用例自动生成算法。
本文提出的基于改进的粒子群优化算法的测试用例自动生成算法提高了测试用例自动生成的效率,但该算法只实现了数值类型的数据,而且还存在手动操作问题,这将是作者下一步的主要研究方向。
还有些内容自己去www.YiFanglunwen.com看看。大概就是这些，比较浅显易懂的。-Software testing, test case automatic generation technology development status and particle swarm optimization of the basic principle and implementation steps, and a detailed study of several important improved particle swarm optimization algorithm. Based on improved particle swarm optimization, system fr a mework to automatically generate test cases based on improved particle swarm optimization, and automatic generation of test cases based on improved particle swarm optimization algorithm.
Finally, using matlab language programming automatically generate test cases based on improved particle swarm optimization algorithm, with specific examples of their experimental, and the results of the data analysis.
In this paper, based on improved particle swarm optimization test cases automatically generated algorithm has a simple, easy to implement, set a few parameters and fast convergence.
The experimental results show that better than genetic algorithm use the proposed algorithm
最后,采用matlab语言编程实现了基于改进的粒子群优化算法的测试用例自动生成算法,用具体实例对其进行了实验,并对结果数据进行了分析。
本文提出的基于改进的粒子群优化算法的测试用例自动生成算法具有简单、易实现、设置参数少和收敛速度快等特点。
实验结果表明,使用本文提出的算法测试用例自动生成的效果明显优于遗传算法等测试用例自动生成算法。
本文提出的基于改进的粒子群优化算法的测试用例自动生成算法提高了测试用例自动生成的效率,但该算法只实现了数值类型的数据,而且还存在手动操作问题,这将是作者下一步的主要研究方向。
还有些内容自己去www.YiFanglunwen.com看看。大概就是这些，比较浅显易懂的。-Software testing, test case automatic generation technology development status and particle swarm optimization of the basic principle and implementation steps, and a detailed study of several important improved particle swarm optimization algorithm. Based on improved particle swarm optimization, system fr a mework to automatically generate test cases based on improved particle swarm optimization, and automatic generation of test cases based on improved particle swarm optimization algorithm.
Finally, using matlab language programming automatically generate test cases based on improved particle swarm optimization algorithm, with specific examples of their experimental, and the results of the data analysis.
In this paper, based on improved particle swarm optimization test cases automatically generated algorithm has a simple, easy to implement, set a few parameters and fast convergence.
The experimental results show that better than genetic algorithm use the proposed algorithm
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