An Experimental Study of Software Metrics for Real-Time Software

The rising costs of software development and maintenance have naturally aroused intere5t in tools and measures to quantify and analyze software complexity. Many software metrics have been studied widely because of the potential usefulness in predicting the complexity and quality of software. Most of the work reported in this area has been related to nonreal-time software. In this paper we report and discuss the results of an experimental investigation of some important metrics and their relationship for a class of 202 Pascal programs used in a real-time distributed processing environment. While some of our observations confirm independent studies, we have noted significant differences. For instance the correlations between McCabe's control complexity measure and Halstead's metrics are low in comparison to a previous study. Studies of the type reported here are important for understanding the relationship between software metrics.     

面向对象软件度量的研究

软件度量是提高和保证软件质量的关键。在给出的面向对象软件度量的结构模型基础上,讨论了实现该模型要解决的关键问题。通过度量结果的分析和评价,能够有效地对面向对象软件的测试和提高软件质量提供科学的依据。     

面向对象软件度量学研究

软件度量学是软件工程的一个新分支,通过度量反馈的信息来控制开发过程,以提高软件质量,是一种行之有效的方法.传统的面向过程的软件将数据和操作分离,强调以算法为核心.近年来发展起来的面向对象软件的主要特性包括抽象性、封装性、继承性和多态性,将数据和操作封装,强调以对象为核心.因此,面向对象软件度量方法也随之发展起来,著名的是C& K度量方法.文中指出C& K度量方法的不足,并就面向对象度量学有待解决的问题提出了一些观点.     

面向对象软件度量学研究

软件度量学是软件工程的一个新分支，通过度量反馈的信息来控制开发过程，以提高软件质量，是一种行之有效的方法。传统的面向过程的软件将数据和操作分离，强调以算法为核心。近年来发展起来的面向对象软件的主要特性包括抽象性、封装性、继承性和多态性，将数据和操作封装，强调以对象为核心。因此，面向对象软件度量方法也随之发展起来，著名的是C＆K度量方法。文中指出C＆K度量方法的不足，并就面向对象度量学有待解决的问题提出了—些观点。     

面向对象软件度量工具体系框架研究

该文首先从系统分析、模型创建、度量计算以及结果表示四个方面讨论了面向对象软件度量工具的体系框架,然后介绍了度量工具信息库的设计,并就若干度量模型实例,对信息的覆盖范围做了统计分析。     

An Empirical Study of Analogy-based Software Effort Estimation

Conventional approaches to software cost estimation have focused on algorithmic cost models, where an estimate of effort is calculated from one or more numerical inputs via a mathematical model. Analogy-based estimation has recently emerged as a promising approach, with comparable accuracy to algorithmic methods in some studies, and it is potentially easier to understand and apply. The current study compares several methods of analogy-based software effort estimation with each other and also with a simple linear regression model. The results show that people are better than tools at selecting analogues for the data set used in this study. Estimates based on their selections, with a linear size adjustment to the analogue's effort value, proved more accurate than estimates based on analogues selected by tools, and also more accurate than estimates based on the simple regression model.     

软件质量与度量

该文首先讨论了软件质量度量模型,然后根据此模型分析了可靠性和可维护性、相应子特性,并描述了子特性的度量。给出了这些度量与质量子特性的关系。最后用一个实例说明使用度量对质量进行评测。     

软件度量学综述

该文将介绍软件度量学的发展历史、软件质量度量体系和软件度量方法。着重分析面向对象软件开发技术的发展对软件度量方法的影响。最后给出了下一步研究方向。     

Software Project Duration and Effort: An Empirical Study

Software projects frequently finish late and over budget. Much of the research to date has characterized this problem in terms of inadequate project estimation or incomplete requirements determination. In this study, we concentrate instead on understanding the relationship between project duration and project effort. Over time, a dynamic environment contributes to the expansion of project requirements, thus increasing the scope and effort required to complete the project, irrespective of initial requirements and anticipated project size. Further, frequent delays and interruptions in a project contribute to greater effort each time work is resumed. We develop and empirically evaluate a two-stage model to relate project duration and effort. Our results indicate a significant and positive relationship between project duration and effort, controlling for anticipated project size and other project characteristics. Our model also provides an estimate for the rate of environmental change while projects are in progress. We demonstrate the practical implications of our model by showing how it can be used in conjunction with time boxing techniques and new development methodologies to better scope software projects.     

面向对象度量的研究

度量技术是保证软件质量的重要手段,它定量地反映了软件某一方面的特征。随着面向对象技术的发展,传统的结构化度量不再适合面向对象的软件,因此出现了不少针对面向对象程序的度量,这些度量在一定程度上反映了面向对象软件的若干方面的特征。文章详细分析了面向对象软件的主要特征,在此基础上介绍了现在常见的几组面向对象度量和它们的应用价值,并且分析了它们的不足之处。最后,提出了几个构造面向对象度量应该遵循的准则。     

用动态度量方法加强软件开发过程管理

软件开发过程管理的研究远远落后于开发技术、工具等方面的研究。通过描述软件开发过程的动态度量的方法,从生产的概念出发,给出软件开发动态度量的流程、方法,论述了管理、度量和数据元素选择的原则,从动态度量方法加强软件开发过程的角度作了探索性研究。     

软件体系结构度量综述

基于软件体系结构度量的现状,从三个方面总结软件体系结构度量领域现有的研究成果,探讨其存在的不足和未来的发展趋势.     

An Investigation of Metrics for the In Situ Detection of Software Expertise

Task-based analysis is a common and effective way to measure expertise levels of software users. However, such assessments typically require in-person laboratory studies and inherently require knowledge of the user's task. Today, there is no accepted method for assessing a user's expertise levels outside of a lab, during a user's own home or work environment activities. In this article, we explore the feasibility of software applications automatically inferring a user's expertise levels, based on the user's in situ usage patterns. We outline the potential usage metrics that may be indicative of expertise levels and then perform a study, where we capture such metrics, by installing logging software in the participants' own workplace environments. We then invite those participants into a laboratory study and perform a more traditional task-based assessment of expertise. Our analysis of the study examines if metrics captured in situ, without any task knowledge, can be indicative of user expertise levels. The results show the existence of significant correlations between metrics calculated from in situ usage logs, and task-based user expertise assessments from our laboratory study. We discuss the implications of the results and how future software applications may be able to measure and leverage knowledge of the expertise of its users.     

软件测试过程的度量

过程中的跟踪和度量在软件开发中扮演着重要的角色,尤其是对软件测试。本文讨论了若干测试过程中度量方法,对每种度量法进行了介绍,并结合实测图示数据加以说明。最后对在质量管理中怎样使用过程度量方法给出了一些建议。     

The Use of Software Complexity Metrics in Software Maintenance

This paper reports on a modest study which relates seven different software complexity metrics to the experience of maintenance activities performed on a medium size software system. Three different versions of the system that evolved over a period of three years were analyzed in this study. A major revision of the system, while still in its design phase, was also analyzed.     

软件测试过程的度量

过程中的跟踪和度量在软件开发中扮演着重要的角色，尤其是对软件测试。本文讨论了若干测试过程中度量方法，对每种度量法进行了介绍，并结合实测图示数据加以说明。最后对在质量管理中怎样使用过程度量方法给出了一些建议。     

A Survey of Dynamic Software Metrics

Software metrics help us to make meaningful estimates for software products and guide us in taking managerial and technical decisions. However, conventional static metrics have been found to be inadequate for modern object-oriented software due to the presence of object-oriented features such as polymorphism, dynamic binding, inheritance and unused code. This fact motivates us to focus on dynamic metrics in place of traditional static metrics. Moreover, dynamic metrics are more precise than static metrics as they are able to capture the dynamic behaviour of the software system during measurement. These dynamic metrics are usually obtained from the execution traces of the code or from the executable models. In this paper, advantages of dynamic metrics over static metrics are discussed and then a survey of the existing dynamic metrics is carried out. These metrics are characterized into different categories such as dynamic coupling metrics, dynamic cohesion metrics. Towards end of the paper, potential research challenges and opportunities in the field of dynamic metrics are identified.     

基于度量的软件质量控制研究

软件度量和质量控制都是软件工程中活跃的研究领域.本文给出了一个基于度量的软件质量控制模型,定义了软件质量控制的流程,并从测试计划编制、测试用例和BUG的目标设定、质量评价、BUG曲线四个方面重点阐述了测试阶段的质量控制方法.本文的研究对于规范和改善组织的质量管理,提高组织对质量的控制能力,具有一定的指导意义和广泛的应用价值.     

Comparative Assessment of Software Quality Classification Techniques: An Empirical Case Study

Software metrics-based quality classification models predict a software module as either fault-prone (fp) or not fault-prone (nfp). Timely application of such models can assist in directing quality improvement efforts to modules that are likely to be fp during operations, thereby cost-effectively utilizing the software quality testing and enhancement resources. Since several classification techniques are available, a relative comparative study of some commonly used classification techniques can be useful to practitioners. We present a comprehensive evaluation of the relative performances of seven classification techniques and/or tools. These include logistic regression, case-based reasoning, classification and regression trees (CART), tree-based classification with S-PLUS, and the Sprint-Sliq, C4.5, and Treedisc algorithms. The use of expected cost of misclassification (ECM), is introduced as a singular unified measure to compare the performances of different software quality classification models. A function of the costs of the Type I (a nfp module misclassified as fp) and Type II (a fp module misclassified as nfp) misclassifications, ECM is computed for different cost ratios. Evaluating software quality classification models in the presence of varying cost ratios is important, because the usefulness of a model is dependent on the system-specific costs of misclassifications. Moreover, models should be compared and preferred for cost ratios that fall within the range of interest for the given system and project domain. Software metrics were collected from four successive releases of a large legacy telecommunications system. A two-way ANOVA randomized-complete block design modeling approach is used, in which the system release is treated as a block, while the modeling method is treated as a factor. It is observed that predictive performances of the models is significantly different across the system releases, implying that in the software engineering domain prediction models are influenced by the characteristics of the data and the system being modeled. Multiple-pairwise comparisons are performed to evaluate the relative performances of the seven models for the cost ratios of interest to the case study. In addition, the performance of the seven classification techniques is also compared with a classification based on lines of code. The comparative approach presented in this paper can also be applied to other software systems.