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。     

面向对象耦合性度量工具的设计与实现*

软件度量是保障软件质量的重要手段。结合软件度量技术,设计并实现一个面向对象耦合性度量工具,用于全面度量面向对象系统的耦合性。给出了此度量工具的体系结构,详细讲述了该工具各个模块的设计与实现方法,其中着重讲述了中间信息库的设计,给出了度量结果示例。最后介绍了该度量工具的特点。     

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。     

软件测评实验室软件测试项目的度量研究

对软件测评实验室承担的软件测试项目所需的度量进行了综述、分类和研究,列举了常用的项目度量、过程度量和产品度量,给出了典型度量的使用实例。     

开放网络环境完整性按需度量模型

完整性度量是可信计算的关键问题之一.首先分析了目前研究成果在开放网络环境下存在的问题及其原因.提出了一种开放网络环境下完整性按需度量模型.该模型由度量请求者根据具体要求定制完整性度量策略,完整性度量策略由程序指令度量策略和数据流度量策略组成,度量响应者根据度量策略来度量自身组件的完整性,并为每个度量请求构造相应的可信链实例.该模型动态地度量完整性,改善了度量结果的新鲜性,兼顾软件代码和用户数据的完整性度量,克服了度量目标的片面性.在该模型的基础上实现了远程证明及其原型系统.并在流媒体服务网络中进行实验测试,实验结果表明该模型以较低的资源开销解决了存在的问题,能够适应开放网络环境下完整性度量的要求.     

一个集成化软件过程度量系统的设计与实现*

为了使企业度量活动满足企业各层级角色的度量需求,提出了一个建立企业集成化软件过程度量体系的方法,给出了一个度量模型及其典型应用,描述了一个企业集成化软件过程度量系统的体系结构及功能。在系统支持下,企业度量活动的效率得到了有效提升。     

软件体系结构度量工具的研究与实现*

在软件体系结构层次应用度量技术对于保证最终产品的质量有重要意义。但体系结构度量领域普遍存在对于度量扩展支持不足的问题。针对该问题,采用新的思路实现了一个可支持度量扩展的软件体系结构度量工具。该工具支持一组基本度量,并支持较为丰富的组合运算,使用户可定制度量,从而在一定程度内解决了体系结构度量领域存在的问题。     

结合多元度量指标软件缺陷预测研究进展

软件缺陷预测可帮助开发人员提前预测缺陷程序,合理分配有限的测试资源。软件缺陷预测的准确度不仅依赖于预测方法的选择,更依赖于软件的度量指标。因此,结合多元度量指标进行软件缺陷预测已成为当前的研究热点。从度量指标出发,对传统度量指标、多元度量指标以及结合多元度量指标的缺陷预测的研究进展进行了系统介绍。主要工作包含：介绍了传统的代码和过程度量指标、基于传统度量指标的软件缺陷预测模型以及影响数据质量的因素;阐述了语义结构度量指标;分析列举了当前用于软件缺陷预测的评价指标;结合预测粒度、传统度量指标、语义结构度量指标、跨项目软件缺陷预测对多元度量指标软件缺陷预测未来的研究趋势进行了展望。     

基于策略嵌入和可信计算的完整性主动动态度量架构

针对已有的一些完整性度量方法在度量主动性、灵活性和运行效率等方面的不足,提出了基于策略嵌入和可信计算的完整性主动动态度量架构(PEDIAMA)。将度量策略嵌入到度量目标内部,因此不需要专门的内存空间来集中维护所有的策略,节省了策略的查询和维护成本,提高了运行效率。由于策略方便存取,制订灵活,不仅可以实时接收外部的度量请求,也可以依据内嵌的策略主动进行度量,主动防御性更强。同时,通过TPM硬件来保护度量架构和度量过程的安全,并对度量策略和相关度量结果进行签名保护,提高了整个系统的安全性。经过测试,PEDIAMA能够即时检测出针对运行实体的攻击,并且度量开销较小。     

一种基于过程改进的度量模型

如何提高软件质量始终是软件工程领域研究的重要方向,基于度量的量化管理是目前最有效的质量保证手段之一,过程度量是软件开发过程中实施软件质量保证(SQA)的一个重要课题。研究了软件过程度量的概念和范围,讨论了几种常用的度量和度量指标。最后提出了一种软件过程度量模型及其度量元。     

层次型Java软件质量度量模型研究

软件度量研究方兴未艾,构建软件度量模型是其中一个重要的研究方向。度量模型从本质上说,是一组对软件进行评价的标准。这个标准并不是仅仅为了用来证明软件的好坏优劣,也用来反映不同软件系统或者软件模块的特点,从而为不同的需求服务。计算机科学中没有绝对的概念,它从诞生起就是紧密围绕应用服务的,计算机科学的研究一定要和现实需求相关联,因此作为一种评价标准,度量模型同样是从不同方面来综合评测软件的属性,从而在不同需求面前提供可参考的选择。     

Construct specific coupling measurement for C++ software

Studies which consider the extent to which the encapsulation of a class is weakened by direct access to its hidden members (such as through the use of the friend construct in C++) are scarce, and those that do exist are based on metric suites where the enabling mechanism of the coupling is ignored. This can lead to conclusions of limited construct validity where incorrect causes of coupling are suggested.In this paper a suite of software metrics which measure the amount of coupling enabled by different C++ programming language constructs (such as friendship and inheritance) are proposed. The metrics presented are based on a formal data model which can be easily adapted for other OO languages. This formal approach removes the scope for ambiguity in the metric definitions. These metrics provide a more accurate reflection of the causative agents of coupling in Object Oriented Systems and their utility is illustrated in an empirical study towards the end of the paper.     

一种基于切片技术度量Java耦合性的框架

在研究面向对象的度量问题时,人们通过简单的统计方法和基于信息源的方法来度量其中的一些特征,例如基本度量、CK度量和AoKi度量等。文中采用一种基于程序切片的方法来度量Java的耦合性问题,通过对J ava源程序中存在的耦合关系的度量,得到了一种比传统方法更精确的耦合度量方法。     

A powertype-based metamodelling framework

Software development methodologies may be described in the context of an underpinning metamodel, but the precise mechanisms that permit them to be defined in terms of their metamodels are usually difficult to explain and do not cover all needs. For example, it is difficult to devise a way that allows the definition of properties of the elements that compose the methodology and, at the same time, of the entities (such as work products) created when the methodology is applied. This article introduces a new approach to constructing metamodels and deriving methodologies from them based on the concept of powertype. It combines key advantages of other metamodelling approaches and allows the seamless integration of process, modelling and documentational aspects of methodologies. With this approach, both methodology components and project entities can be described directly by the same metamodel. Cesar Gonzalez-Perez is a post-doctoral research fellow at the Faculty of Information Technology at UTS, where he works in object- and agent- oriented methodologies and metamodelling. Cesar is the author of over 40 publications and has led 12 successful software development projects. Cesar has previously worked in archaeology as well as biology, both in industry and academe. Cesar is the founder and former technical director of Neco, a company based in Spain specialising in software development support services, which include the deployment and use of the OPEN/Metis methodological framework at small and mid-sized organisations. Brian Henderson-Sellers is Director of the Centre for Object Technology Applications and Research and Professor of Information Systems at University of Technology, Sydney (UTS). He is author of eleven books on object technology and is well-known for his work in OO methodologies (MOSES, COMMA, OPEN, OOSPICE) and in OO metrics and, more recently, in agent-oriented methodologies. Brian has been Regional Editor of Object-Oriented Systems, a member of the editorial board of Object Magazine/Component Strategies and Object Expert for many years and is currently on the editorial board of Journal of Object Technology and Software and Systems Modelling. He is Editor of the International Journal on Agent-Oriented Software Engineering. He was the Founder of the Object-Oriented Special Interest Group of the Australian Computer Society (NSW Branch) and Chairman of the Computerworld Object Developers' Awards committee for ObjectWorld 94 and 95 (Sydney). He is a frequent, invited speaker at international OT conferences. In 1999, he was voted number 3 in the Who's Who of Object Technology (Handbook of Object Technology, CRC Press, Appendix N). He is a member of the Review Panel for the OMG's Software Process Engineering Model (SPEM) standards initiative and a member of the UML2.0 review team. In July 2001, Professor Henderson-Sellers was awarded a Doctor of Science (DSc) from the University of London for his research contributions in object-oriented methodologies.     

API-Based and Information-Theoretic Metrics for Measuring the Quality of Software Modularization

We present in this paper a new set of metrics that measure the quality of modularization of a non-object-oriented software system. We have proposed a set of design principles to capture the notion of modularity and defined metrics centered around these principles. These metrics characterize the software from a variety of perspectives: structural, architectural, and notions such as the similarity of purpose and commonality of goals. (By structural, we are referring to intermodule coupling-based notions, and by architectural, we mean the horizontal layering of modules in large software systems.) We employ the notion of API (application programming interface) as the basis for our structural metrics. The rest of the metrics we present are in support of those that are based on API. Some of the important support metrics include those that characterize each module on the basis of the similarity of purpose of the services offered by the module. These metrics are based on information-theoretic principles. We tested our metrics on some popular open-source systems and some large legacy-code business applications. To validate the metrics, we compared the results obtained on human-modularized versions of the software (as created by the developers of the software) with those obtained on randomized versions of the code. For randomized versions, the assignment of the individual functions to modules was randomized     

Software fault prediction metrics: A systematic literature review

ContextSoftware metrics may be used in fault prediction models to improve software quality by predicting fault location.ObjectiveThis paper aims to identify software metrics and to assess their applicability in software fault prediction. We investigated the influence of context on metrics’ selection and performance.MethodThis systematic literature review includes 106 papers published between 1991 and 2011. The selected papers are classified according to metrics and context properties.ResultsObject-oriented metrics (49%) were used nearly twice as often compared to traditional source code metrics (27%) or process metrics (24%). Chidamber and Kemerer’s (CK) object-oriented metrics were most frequently used. According to the selected studies there are significant differences between the metrics used in fault prediction performance. Object-oriented and process metrics have been reported to be more successful in finding faults compared to traditional size and complexity metrics. Process metrics seem to be better at predicting post-release faults compared to any static code metrics.ConclusionMore studies should be performed on large industrial software systems to find metrics more relevant for the industry and to answer the question as to which metrics should be used in a given context.     

Estimating software readiness using predictive models

In this study, defect tracking is used as a proxy method to predict software readiness. The number of remaining defects in an application under development is one of the most important factors that allow one to decide if a piece of software is ready to be released. By comparing predicted number of faults and number of faults discovered in testing, software manager can decide whether the software is likely ready to be released or not.The predictive model developed in this research can predict: (i) the number of faults (defects) likely to exist, (ii) the estimated number of code changes required to correct a fault and (iii) the estimated amount of time (in minutes) needed to make the changes in respective classes of the application. The model uses product metrics as independent variables to do predictions. These metrics are selected depending on the nature of source code with regards to architecture layers, types of faults and contribution factors of these metrics. The use of neural network model with genetic training strategy is introduced to improve prediction results for estimating software readiness in this study. This genetic-net combines a genetic algorithm with a statistical estimator to produce a model which also shows the usefulness of inputs.The model is divided into three parts: (1) prediction model for presentation logic tier (2) prediction model for business tier and (3) prediction model for data access tier. Existing object-oriented metrics and complexity software metrics are used in the business tier prediction model. New sets of metrics have been proposed for the presentation logic tier and data access tier. These metrics are validated using data extracted from real world applications. The trained models can be used as tools to assist software mangers in making software release decisions.     

Empirical analysis of CK metrics for object-oriented design complexity: implications for software defects

To produce high quality object-oriented (OO) applications, a strong emphasis on design aspects, especially during the early phases of software development, is necessary. Design metrics play an important role in helping developers understand design aspects of software and, hence, improve software quality and developer productivity. In this paper, we provide empirical evidence supporting the role of OO design complexity metrics, specifically a subset of the Chidamber and Kemerer (1991, 1994) suite (CK metrics), in determining software defects. Our results, based on industry data from software developed in two popular programming languages used in OO development, indicate that, even after controlling for the size of the software, these metrics are significantly associated with defects. In addition, we find that the effects of these metrics on defects vary across the samples from two programming languages-C++ and Java. We believe that these results have significant implications for designing high-quality software products using the OO approach.     

基于持续集成的软件度量

软件度量是针对软件开发项目、过程及产品进行数据定义、收集和分析的持续度量化过程;持续集成工具上的的构建工程每天自动完成从版本库更新代码、静态检查、编译、出包、自动化用例测试等任务,在进行集成构建的过程中可以为软件度量提供多种相关的度量数据;结合工作实践,叙述了基于持续集成的软件度量的原理;软件度量管理涉及到的角色;软件度量实现过程;叙述了基于持续集成的两种类型的软件度量指标的定义以及提取方法;最后详细叙述了在软件度量过程中遇到的几个典型案例;工作实践表明在软件的开发过程中做好软件度量工作有助于软件开发部门控制、预测、和改进软件产品的质量与软件开发过程;从而提高软件质量和软件开发效率,降低软件开发成本。