Measuring design complexity of semantic web ontologies

Ontology languages such as OWL are being widely used as the Semantic Web movement gains momentum. With the proliferation of the Semantic Web, more and more large-scale ontologies are being developed in real-world applications to represent and integrate knowledge and data. There is an increasing need for measuring the complexity of these ontologies in order for people to better understand, maintain, reuse and integrate them. In this paper, inspired by the concept of software metrics, we propose a suite of ontology metrics, at both the ontology-level and class-level, to measure the design complexity of ontologies. The proposed metrics are analytically evaluated against Weyuker’s criteria. We have also performed empirical analysis on public domain ontologies to show the characteristics and usefulness of the metrics. We point out possible applications of the proposed metrics to ontology quality control. We believe that the proposed metric suite is useful for managing ontology development projects.     

A set of complexity metrics for guiding the software test process

Software verification and validation is a domain which is covered by many dynamic test, static analysis, and formal verification techniques. This presents a problem to practitioners with respect to selecting those suitable techniques which can be used successfully. The basic idea of the methodology presented here is to select test techniques which fit the software under test. A dynamic test technique requires that certain program elements are covered, will be sensitive to errors associated with these elements, because executing an error location is a precondition for revealing the error. Furthermore, it is likely that the probability of errors increases with complexity. Complexity can be characterized in terms of several properties which can be used to suggest various testing strategies. The complexity of the various software properties can be measured using appropriate complexity metrics. Properties with unusual high complexity measures should be tested very throughly. The approach described in this paper permits the selection of test techniques based on the values of the metrics with respect to a particular software product.     

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。     

Deriving complexity information from a formal communication protocol specification

Communication software systems have become very large and complex. Recognizing the complexity of such software systems is a key element in their development activities. Software metrics are useful quantitative indicators for assessing and predicting software quality attributes, like complexity. However, most of existing metrics are extracted from source programs at the implementation phase of the software life cycle. They cannot provide early feedback during the specification phase; and subsequently it is difficult and expensive to make changes to the system, if so indicated by the metrics. It is therefore important to be able to measure system complexity at the specification phase. However, most software specifications are written in natural languages from which metrics information is very hard to extract. In this paper, we describe how complexity information can be derived from a formal communication protocol specification written in Estelle so that it is possible to predict the complexity of its implementation and subsequently its development can be better managed. © 1998 John Wiley & Sons, Ltd.     

Computing Cyclomatic Complexity with Cubic Flowgraphs

Two new methods for the computation of cyclomatic complexity especially for decomposable representations are introduced. Building software by integration is a developing paradigm, especially enabled by the emerging component technologies. Decomposition of the design for a top-down approach is a prerequisite for this paradigm. Cubic flowgraphs are instrumental in providing formalisms for decomposition and integration. Cyclomatic complexity analysis of a design representation that is decomposable is the goal of this research. In addition to introducing cyclomatic complexity computation using cubic flowgraphs, preservation of cyclomatic complexity in the decomposition of the cubic flowgraph is also presented.     

Applying Mccabe's complexity measure to multiple-exit programs

The traditional short-cut calculation for McCabe's complexity metric, π+1, does not handle the case of multiple-exit flowgraphs. An alternative short-cut calculation is presented that allows the metric to be applied to multiple-exit programs.     

基于复杂网络的软件结构度量方法综述

计算机软件复杂性与软件质量、开发成本和生产效率等密切相关,软件复杂性的度量和控制是计算机科学的挑战性问题之一.近年来复杂网络研究的兴起为研究软件系统结构复杂性提供了新的理论、方法和工具,该方法克服了传统软件结构度量方法侧重微观统计、缺乏全局性和整体性等缺点,构成了复杂网络与传统软件工程的交叉研究领域.对该领域的研究工作进展进行了介绍,从软件网络结构特征分析、建模以及研究成果的初步应用3个方面总结已有工作,并对今后有意义的研究方向进行了展望,如基于加权模型的软件网络建模、软件网络动态演化机制等.     

Investigating ARIMA models of software system quality

In this paper, we investigate how to incorporate program complexity measures with a software quality model. We collect software complexity metrics and fault counts from each build during the testing phase of a large commercial software system. Though the data are limited in quantity, we are able to predict the number of faults in the next build. The technique we used is called times series analysis and forecasting. The methodology assumes that future predictions are based on the history of past observations. We will show that the combined complexity quality model is an improvement over the simpler quality only model. Finally, we explore how the testing process used in this development may be improved by using these predictions and suggest areas for future research.     

PSAMS: a communication protocol specification assessment and measurement system

An obstacle to the uses of software metrics and size models, which we have developed for measuring the complexity and maintainability of a communication protocol specified in Estelle and for estimating the size of its specification and implementation, is the time‐consuming effort in collecting the metrics. To address this problem, a software system called PSAMS (protocol specification assessment and measurement system) for automatically calculating the metrics and sizes of specification and implementation has been developed. This paper describes the design of PSAMS, which provides five functionalities for a communication protocol Estelle specification: exploring its specification, measuring its complexity, assessing its maintainability, estimating its specification size and estimating its implementation size. To demonstrate the usefulness of PSAMS, we have applied it to measure the complexity and maintainability of 10 communication protocol Estelle specifications; the measurement results and decision support information provided by each functionality are presented in this paper. With PSAMS, communication protocol designers and developers are able to assess the complexity of a communication protocol early in the specification stage and have information which helps them manage a communication software project better. Copyright © 2002 John Wiley & Sons, Ltd.     

Avoiding metric monsters: A design metrics approach

Metric monsters are stumbling blocks that prevent software metrics-guided methodologies from attaining product and process improvement. Metric monsters can occur during the identification, collection or application of software metrics. In our research, we have developed and tested our design metrics over a five-year period and have found them to be excellent predictors of error-prone modules. Based on this research, we will identify some of the monsters that occur in the quantitative analyses of software and its development processes, and present our approach in formulating a design metrics model that avoids these monsters. This model consists of software tools, guidelines and actions for the application of software design metrics.     

分组密码统一描述模型研究

依据软件度量的思想和方法,提出数据库应用软件交互复杂性度量的概念。利用4个指标参量表征应用程序与数据库管理系统的交互过程,根据软件测试需要为指标指定权重向量,并通过指标向量与权重向量的乘积将4个指标归一化为一个复杂性度量值。通过实例验证表明,该方法能够客观、准确、灵活地度量数据库应用软件交互过程复杂性。     

数据库应用软件交互复杂性度量研究

依据软件度量的思想和方法,提出数据库应用软件交互复杂性度量的概念。利用4个指标参量表征应用程序与数据库管理系统的交互过程,根据软件测试需要为指标指定权重向量,并通过指标向量与权重向量的乘积将4个指标归一化为一个复杂性度量值。通过实例验证表明,该方法能够客观、准确、灵活地度量数据库应用软件交互过程复杂性。     

基于软件加权网络的软件结构复杂性度量

软件结构复杂性问题一直备受关注。随着软件规模的不断增大,传统的度量方法已很难适应软件的发展。为了有效地度量软件结构复杂性,以复杂网络理论为基础,分析软件加权网络的强度和紧密度特征参数之间的关系,并统计软件样本集的总体特征量。首先选取特征值较大的软件,研究其对应的软件加权网络中强度和紧密度数值较大的节点。然后对比分析排序差别较大的节点的属性和功能。最后评价两种软件结构复杂性度量方法,得出用强度可以度量软件局部结构的复杂性,紧密度能够度量软件整体结构的复杂性。     

Measuring complexity in C++ application software

This paper concerns the use of design/source-code complexity metrics in analysing C++ software. It describes the use of one suite of object-oriented metrics published by Chidamber and Kemerer¹ to evaluate a commercial C++ application. It provides an interpretation and critique of these metrics, including the use of two traditional metrics (Cyclomatic Complexity² and Software Science³) in association with these object-oriented metrics. The evolution, over a two and a half year period, of one commercial grade C++ application comprising 114 classes with 25,000 lines of code is studied. The efforts consumed in bug fixes and enhancements are correlated with the complexity measures on a per class basis, and results are presented. These results are compared to those from other workers. The paper provides a detailed analysis of the practical strengths and weaknesses of the metrics suite in the light of experiences with its use. © 1998 John Wiley & Sons, Ltd.     

A composite complexity approach for software defect modelling

An approach is proposed to develop defect models for software components based on a categorical multivariate regression analysis. This modelling technique is useful when the software components are sufficiently small so that the assumption of a continuous normally distributed defect distribution is not valid. Library unit aggregations from five Ada projects are analysed to yield a composite complexity measure which is a function of both software complexity characteristics and development environment characteristics. The probabilities of various numbers of defects are derived from this composite complexity measure. The probability distributions are used to calculate subsystem level defects which are then compared to the actual defects.     

软件迷惑变换的鲁棒性量化评价

为了方便程序员比较多种迷惑变换方案的优劣,提出了一种量化评价迷惑变换鲁棒性的方法.该方法从软件复杂度变化与代码功能模糊性两个相对独立的层面来刻画迷惑变换导致的鲁棒性.首先,从系统的复杂性与信息的多样性角度建立软件系统复杂度模型,模型包含软件结构、信息流、分支、循环以及元素的嵌套层次,力求从复杂性层面更准确地反映变换对软件的保护;之后,为量化描述迷惑变换的功能模糊度,根据专家指标评分法建立单种迷惑变换模糊度模型,在此基础上建立多种迷惑变换复合模糊度模型;然后,阐述了如何联合所提出的模型实现对单种迷惑变换技术有效性判定与多种迷惑方案的选优,也给出了模型的实现算法及一些示例;最后,通过实例仿真详细展示了模型的工作过程.     

Defect proneness estimation and feedback approach for software design quality improvement

Context

Modern software engineering demands professionals and researchers to proactively and collectively work towards exploring and experimenting viable and valuable mechanisms in order to extract all kinds of degenerative bugs, security holes, and possible deviations at the initial stage. Having understood the real need here, we have introduced a novel methodology for the estimation of defect proneness of class structures in object oriented (OO) software systems at design stage.

Objective

The objective of this work is to develop an estimation model that provides significant assessment of defect proneness of object oriented software packages at design phase of SDLC. This frame work enhances the efficiency of SDLC through design quality improvement.

Method

This involves a data driven methodology which is based on the empirical study of the relationship existing between design parameters and defect proneness. In the first phase, a mapping of the relationship between the design metrics and normal occurrence pattern of defects are carried out. This is represented as a set of non linear multifunctional regression equations which reflects the influence of individual design metrics on defect proneness. The defect proneness estimation model is then generated by weighted linear combination of these multifunctional regression equations. The weighted coefficients are evaluated through GQM (Goal Question Metric) paradigm.

Results

The model evaluation and validation is carried out with a selected set of cases which is found to be promising. The current study is successfully dealt with three projects and it opens up the opportunity to extend this to a wide range of projects across industries.

Conclusion

The defect proneness estimation at design stage facilitates an effective feedback to the design architect and enabling him to identify and reduce the number of defects in the modules appropriately. This results in a considerable improvement in software design leading to cost effective products.     

A quantitative analysis of parametric CAD model complexity and its relationship to perceived modeling complexity

Digital product data quality and reusability has been proven a critical aspect of the Model-Based Enterprise to enable the efficient design and redesign of products. The extent to which a history-based parametric CAD model can be edited or reused depends on the geometric complexity of the part and the procedure employed to build it. As a prerequisite for defining metrics that can quantify the quality of the modeling process, it is necessary to have CAD datasets that are sorted and ranked according to the complexity of the modeling process. In this paper, we examine the concept of perceived CAD modeling complexity, defined as the degree to which a parametric CAD model is perceived as difficult to create, use, and/or modify by expert CAD designers. We present a novel method to integrate pair-wise comparisons of CAD modeling complexity made by experts into a single metric that can be used as ground truth. Next, we discuss a comprehensive study of quantitative metrics which are derived primarily from the geometric characteristics of the models and the graph structure that represents the parent/child relationships between features. Our results show that the perceived CAD modeling complexity metric derived from experts’ assessment correlates particularly strongly with graph-based metrics. The Spearman coefficients for five of these metrics suggest that they can be effectively used to study the parameters that influence the reusability of models and as a basis to implement effective personalized learning strategies in online CAD training scenarios.     

Comparative aspects of software complexity metrics and program modules — a multidimensional scaling approach

A multivariate statistical procedure called multidimensional scaling is used to study the relationship of various software complexity metrics and program modules. The program modules that make up a software system are analysed and their effects towards the overall characteristics of a software are viewed. This multidimensional scaling technique is applied to a sample data set. The scaling procedure clustered the similar and dissimilar software complexity metrics. Program modules with low complexity and few errors clustered together, while modules which were complex were isolated. This technique shows promise in the identification of complex modules that potentially contain disproportionate errors prior to the testing phase. The ability of the scaling techniques to cluster similar and dissimilar characteristics is explained and graphically presented.