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A hybrid method for parameter estimation of software reliability growth model using Modified Genetic Swarm Optimization with the aid of logistic exponential testing effort function

机译:一种借助于逻辑指数测试努力使用修改遗传群优化的软件可靠性增长模型参数估计的混合方法

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The modern world is highly engaged with software systems. Determining the quality of a software system is a challenging task. Software reliability plays a vital role in the quality estimation of a software system and highly helped in achieving high-quality software. This paper proposes a hybrid method for estimating the parameters of Software Reliability Growth Model (SRGM) using Modified Genetic Swarm Optimization (MGSO) with the combination of logistic-exponential Testing Effort Function (TEF). Parameter estimation of SRGM is highly helped in reliability prediction which helps in determination of Software quality. Once the parameters are estimated, the parameters are optimized using MGSO. The proposed method implemented on working platform of JAVA and the effectiveness of proposed method estimated by comparing with existing methods.
机译:现代世界高度从事软件系统。确定软件系统的质量是一个具有挑战性的任务。软件可靠性在软件系统的质量估算中起着至关重要的作用,并且高度帮助实现了高质量的软件。本文提出了一种用改进的遗传群优化(MGSO)与逻辑指数测试工作函数(TEF)的组合估算软件可靠性增长模型(SRGM)参数的混合方法。 SRGM的参数估计在可靠性预测中高度有助于确定软件质量。一旦参数估计,参数使用MGSO进行优化。所提出的方法在Java的工作平台上实施以及通过与现有方法进行比较估计的提出方法的有效性。

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