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An Empirical Assessment and Validation of Redundancy Metrics Using Defect Density as Reliability Indicator
Scientific Programming ( IF 1.672 ) Pub Date : 2021-02-19 , DOI: 10.1155/2021/8325417
Dalila Amara 1 , Ezzeddine Fatnassi 1, 2 , Latifa Ben Arfa Rabai 1
Affiliation  

Software metrics which are language-dependent are proposed as quantitative measures to assess internal quality factors for both method and class levels like cohesion and complexity. The external quality factors like reliability and maintainability are in general predicted using different metrics of internal attributes. Literature review shows a lack of software metrics which are proposed for reliability measurement and prediction. In this context, a suite of four semantic language-independent metrics was proposed by Mili et al. (2014) to assess program redundancy using Shannon entropy measure. The main objective of these metrics is to monitor program reliability. Despite their important purpose, they are manually computed and only theoretically validated. Therefore, this paper aims to assess the redundancy metrics and empirically validate them as significant reliability indicators. As software reliability is an external attribute that cannot be directly evaluated, we employ other measurable quality factors that represent direct reflections of this attribute. Among these factors, defect density is widely used to measure and predict software reliability based on software metrics. Therefore, a linear regression technique is used to show the usefulness of these metrics as significant indicators of software defect density. A quantitative model is then proposed to predict software defect density based on redundancy metrics in order to monitor software reliability.

中文翻译:

使用缺陷密度作为可靠性指标的冗余度量的经验评估和验证

提出了与语言相关的软件度量,作为评估方法和类级别(如内聚性和复杂性)的内部质量因子的定量度量。通常使用不同的内部属性指标来预测诸如可靠性和可维护性之类的外部质量因素。文献综述表明,缺乏用于可靠性测量和预测的软件指标。在这种情况下,Mili等人提出了一套四个独立于语义语言的指标。(2014)使用Shannon熵测度评估程序冗余。这些指标的主要目的是监视程序的可靠性。尽管它们具有重要的目的,但它们是手动计算的,仅在理论上经过验证。所以,本文旨在评估冗余指标,并通过经验验证它们是重要的可靠性指标。由于软件可靠性是无法直接评估的外部属性,因此我们采用其他可衡量的质量因子来表示该属性的直接反映。在这些因素中,缺陷密度被广泛用于基于软件指标来测量和预测软件可靠性。因此,线性回归技术用于显示这些指标作为软件缺陷密度的重要指标的有用性。然后提出一个定量模型,以基于冗余度量来预测软件缺陷密度,以便监视软件可靠性。我们采用其他可衡量的质量因子来表示该属性的直接反映。在这些因素中,缺陷密度被广泛用于基于软件指标来测量和预测软件可靠性。因此,线性回归技术用于显示这些指标作为软件缺陷密度的重要指标的有用性。然后提出一个定量模型,以基于冗余度量来预测软件缺陷密度,以便监视软件可靠性。我们采用其他可衡量的质量因子来表示该属性的直接反映。在这些因素中,缺陷密度被广泛用于基于软件指标来测量和预测软件可靠性。因此,线性回归技术用于显示这些指标作为软件缺陷密度的重要指标的有用性。然后提出一个定量模型,以基于冗余度量来预测软件缺陷密度,以便监视软件可靠性。
更新日期:2021-02-19
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