一种面向对象多态复杂性的度量方法

提出了一种类级多态复杂性和系统级多态复杂性的度量方法。该方法对强制多态、重载多态、类型参数化多态和包含多态这四种类型的多态进行分析,得出反映类的多态复杂性的量度,即强制多态复杂性（CCPP）、重载复杂性（CMC）、参数多态复杂性（CPMP）、包含多态复杂性（CCTP）;然后通过整合得到度量系统级的多态复杂性。实验证明,该方法能够正确有效地度量面向对象软件的多态复杂性。     

面向对象程序复杂性度量层次模型

程序复杂性度量可以实现定量地分析程序复杂性，从而为估计成本提供一个标准。为了度量面向对象程序复杂性，在讨论了度量的定义．度量的理论基础后，提出了一种面向对象程序复杂性度量的层次模型。该模型分成5个层次：系统层、类簇层、类继承树层、类层和方法层，每个层次都有自己的度量方法。采用这种分层度量模型的好处是：它是一个框架，各度量方法归属到各层中；各层之间相互独立；一层中方法的修改并不影响其它层。     

基于继承图的面向对象软件复杂性度量研究

面向对象软件开发是一种新的可以减少成本、提高可用性和灵活性的高效的软件系统开发方法。复杂性度量在软件开发中起着非常重要的作用,它可减少整个开发周期的费用,但目前还没有成熟的用于面向对象软件复杂性的度量方法。文章首先通过继承图描述面向对象软件复杂性度量方法,然后讨论了单元重复继承算法,最后给出了具体实例。     

面向对象类的复杂性的度量方法

简要分析了已有的几种面向对象软件复杂性度量方法,指出了这些方法在反映类复杂性方面存在的不足,运用软件复杂性分解的思想,提出了一种新的类复杂性度量方法。该方法将类复杂性分解为类成员复杂性、类成员关系复杂性和封装复杂性三个复杂性分量,对各分量分别度量,进而得出总复杂性。其中,类成员复杂性采用类所实现的成员的复杂性SIMC、类接口复杂性之和SCIC反映;类成员关系复杂性通过对文中提出的伪二部图进行分析反映;封装复杂性采用成员可见率反映。最后,通过实例验证了该方法的有效性和可行性。     

面向对象软件测试及度量的研究

软件测试方法和度量是提高和保证软件质量的关键,文中介绍了一种认识面向对象软件集成测试和试想量的方法（URI）,以及一种继承树深度（DIT）的度量标准,从这一测试方法显示继承的过多使用将增加软件测试的复杂性,论文最后介绍了有待进一步研究的问题。     

基于继承的内聚度度量方法研究

本文首先介绍了面向对象软件的特征,然后具体分析了C＆K度量法,着重分析了其中与类继承相关的继承树深度（DIT）和孩子数目（NOC）度量准则。在此基础上,通过分析超类与其子类中元素（方法和属性）的继承关系,提出了基于继承的内聚度度量方法,从而克服了C＆K度量法中对类继承性、多态性方面度量的不足,为综合评价类的内聚度度提供了指南。     

面向对象软件度量学的研究

软件度量学是软件工程领域的一个重要研究方向。通过软件度量,可以降低软件开发的成本,提高软件开发的效率,保证软件能满足用户的需求,开发出高质量的软件。本文分析了面向对象软件度量的特点,在著名的C＆K度量方法及其它度量方法的基础上,着重阐述了针对各种不同层次的面向对象的软件度量,包括面向OO项目的度量、面向OO系统的度量、面向类继承树的度量、面向类层的度量、面向方法（操作）的度量。     

一种优化的面向对象软件复杂性度量方法

首先结合面向对象技术特性,对面向对象软件类级别的CK度量方法和系统级别的MOOD度量方法进行了分析,并就CK度量提出了优化的度量方法OCK。然后结合OCK度量和MOOD度量的优点提出了较优化的面向对象软件复杂性度量方法OSCM。OSCM度量可以有效地弥补CK度量和MOOD度量的不足,优化度量结果。     

基于UML类图的软件预测模型

针对面向对象软件开发过程中对软件进行复杂性预测的问题,提出一种在面向对象软件开发的初期阶段通过统一建模语言（UML）类图对软件的复杂性进行度量的模型,该模型运用多元线性方程和统计学原理。对比实验结果表明,为UML类图的可理解性和可修改性所生成的预测模型能建立在由关联和泛化所组成的早期度量标准上。     

一个面向对象软件度量工具的实现和度量实验研究

介绍了面向对象软件C&K度量学理论与方法,结合C++语言的特征,分析了C&K度量指标存在的缺点,提出了改进方法.然后描述了作者开发的基于改进C&K度量学理论与方法的针对C++的软件度量工具SMTCPP,该工具使用LL(1)分析法对源程序进行语法分析,从而提取程序中有关类、类成员、成员函数、对象等信息,计算出类的方法数、方法最大复杂度、继承树深度、子类数目、耦合度、响应集、相对内聚缺乏度等指标,以指导软件开发过程.这些度量结果还可以存放在数据库中,以便为建立软件质量评价模型收集充足的数据.论文最后对采用SMTCPP所做的3个实用软件度量实验结果进行了分析,表明了SMTCPP的实用性.     

Empirical evaluation of reuse sensitiveness of complexity metrics

Measuring software products and processes is essential for improving software productivity and quality. In order to evaluate the complexity of object-oriented software, several complexity metrics have been proposed. Among them, Chidamber and Kemerer’s metrics are the most well-known for object-oriented software. Their metrics evaluate the complexity of the classes in terms of internal, inheritance, and coupling complexity. Though the reused classes of the class library usually have better quality than the newly-developed ones, their metrics deal with inheritance and coupling complexity in the same way. This article first proposes a revision of the Chidamber and Kemerer’s metrics which can be applied to software which had been constructed by reusing software components. Then, we give an analysis of data collected from the development of an object-oriented software using a GUI framework. We compare the original metrics with the revised ones by evaluating the accuracy of estimating the effort to fix faults and show the validity and usefulness of the revised metrics.     

Metrics for Measuring the Quality of Modularization of Large-Scale Object-Oriented Software

The metrics formulated to date for characterizing the modularization quality of object-oriented software have considered module and class to be synonymous concepts. But a typical class in object oriented programming exists at too low a level of granularity in large object-oriented software consisting of millions of lines of code. A typical module (sometimes referred to as a superpackage) in a large object-oriented software system will typically consist of a large number of classes. Even when the access discipline encoded in each class makes for "clean" class-level partitioning of the code, the intermodule dependencies created by associational, inheritance-based, and method invocations may still make it difficult to maintain and extend the software. The goal of this paper is to provide a set of metrics that characterize large object-oriented software systems with regard to such dependencies. Our metrics characterize the quality of modularization with respect to the APIs of the modules, on the one hand, and, on the other, with respect to such object-oriented inter-module dependencies as caused by inheritance, associational relationships, state access violations, fragile base-class design, etc. Using a two-pronged approach, we validate the metrics by applying them to popular open-source software systems.     

A tool for measuring inheritance coupling in object-oriented systems

Analyzing object-oriented systems in order to evaluate their quality gains its importance as the paradigm continues to increase in popularity. Consequently, several object-oriented metrics have been proposed to evaluate different aspects of these systems such as class coupling. In object-oriented design, three types of coupling may exist between classes: inheritance coupling, interaction coupling, and component coupling. This paper presents a tool for measuring inheritance coupling in object-oriented systems.     

面向对象软件度量结果的分析方法与评价

软件度量是保证软件质量的重要方法,该文主要针对面向对象软件经过分析度量后得出结果进行分析与评价,分析与评价主要基于面向对象程序中类的耦合度、内聚度、继承性、复杂度等进行展开,从数学的角度来分析度量指标的可信度,以保证从整体上把握面向对象软件产品的质量。     

An evaluation of the MOOD set of object-oriented software metrics

This paper describes the results of an investigation into a set of metrics for object-oriented design, called the MOOD metrics. The merits of each of the six MOOD metrics is discussed from a measurement theory viewpoint, taking into account the recognized object-oriented features which they were intended to measure: encapsulation, inheritance, coupling, and polymorphism. Empirical data, collected from three different application domains, is then analyzed using the MOOD metrics, to support this theoretical validation. Results show that (with appropriate changes to remove existing problematic discontinuities) the metrics could be used to provide an overall assessment of a software system, which may be helpful to managers of software development projects. However, further empirical studies are needed before these results can be generalized