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A Novel Method to Measure Comprehensive Complexity of Software Based on the Metrics Statistical Model

机译:基于度量统计模型的软件综合复杂度度量方法

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Calculating software complexity is one of the most challenging problems in the Software Engineering due to using them in estimating errors, having a landscape of software reliability, approximating costs of software implementation and maintenance, and delivering software with better quality. Most of the recent researches on calculating the softwareȁ9;s complexity focus on special directions and goals. This paper presents a novel method for measuring comprehensive complexity of software based on Statistical model evaluation of the existing complexity metrics through modules. To reach this purpose, the amount of comprehensive complexity is achieved for every module by identifying statistical distribution of complexity metric quantities, normalization and their combination. Afterward, the comprehensive complexity of the software is calculated by composition of the module''s complexity amounts. This method is applied on some samples of the "NASA Software Engineering laboratory" and some of its positive results are presented.
机译:计算软件的复杂度是软件工程中最具挑战性的问题之一,这是因为使用它们来估计错误,具有软件可靠性,估算软件实施和维护成本以及交付质量更好的软件是最困难的问题。最近有关计算软件9的复杂性的大多数研究都集中在特殊的方向和目标上。本文提出了一种通过模块对现有复杂性指标进行统计模型评估的一种衡量软件综合复杂性的新方法。为了达到这个目的,通过识别复杂度度量值,归一化及其组合的统计分布,可以为每个模块实现全面的复杂度。然后,通过模块的复杂度量的组成来计算软件的综合复杂度。此方法应用于“ NASA软件工程实验室”的一些样本,并给出了一些积极的结果。

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