Steve Counsell

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.

A Comparative Study of Cost Estimation Models for Web Hypermedia Applications

Software cost models and effort estimates help project managers allocate resources, control costs and schedule and improve current practices, leading to projects finished on time and within budget. In the context of Web development, these issues are also crucial, and very challenging given that Web projects have short schedules and very fluidic scope. In the context of Web engineering, few studies have compared the accuracy of different types of cost estimation techniques with emphasis placed on linear and stepwise regressions, and case-based reasoning (CBR). To date only one type of CBR technique has been employed in Web engineering. We believe results obtained from that study may have been biased, given that other CBR techniques can also be used for effort prediction. Consequently, the first objective of this study is to compare the prediction accuracy of three CBR techniques to estimate the effort to develop Web hypermedia applications and to choose the one with the best estimates. The second objective is to compare the prediction accuracy of the best CBR technique against two commonly used prediction models, namely stepwise regression and regression trees. One dataset was used in the estimation process and the results showed that the best predictions were obtained for stepwise regression.

Experimental assessment of the effect of inheritance on the maintainability of object-oriented systems

In this paper, we describe an empirical investigation into the modifiability and understandability of object-oriented (OO) software. A controlled experiment was conducted to establish the effects of varying levels of inheritance on understandability and modifiability. The software used in this experiment consisted of a C++ system without any inheritance and a corresponding version containing three levels of inheritance, as well as a second larger C++ system without inheritance and a corresponding version with five levels of inheritance. For both of the systems, the application modelled a database for a University personnel system. A number of statistical hypotheses were tested. Results indicated that the systems without inheritance were easier to modify than the corresponding systems containing three or five levels of inheritance. Also, it was easier to understand the system without inheritance than a corresponding version containing three levels of inheritance. Results also indicated that larger systems are equally difficult to understand whether or not they contain inheritance. The results contained in this paper highlight the need for further empirical investigations in this area, particularly into the benefits of using inheritance.

Web metrics - estimating design and authoring effort

Like any software process, Web application development would benefit from early-stage effort estimates. Using an undergraduate university course as a case study, we collected metrics corresponding to Web applications, developers and tools. Then we used those metrics to generate models for predicting design and authoring effort for future Web applications.

Power law distributions in class relationships

Power law distributions have been found in many natural and social phenomena, and more recently in the source code and run-time characteristics of Object-Oriented (OO) systems. A power law implies that small values are extremely common, whereas large values are extremely rare. We identify twelve new power laws relating to the static graph structures of Java programs. The graph structures analyzed represented different forms of OO coupling, namely, inheritance, aggregation, interface, parameter type and return type. Identification of these new laws provides the basis for predicting likely features of classes in future developments. The research ties together work in object-based coupling and World Wide Web structures.

The interpretation and utility of three cohesion metrics for object-oriented design

The concept of cohesion in a class has been the subject of various recent empirical studies and has been measured using many different metrics. In the structured programming paradigm, the software engineering community has adopted an informal yet meaningful and understandable definition of cohesion based on the work of Yourdon and Constantine. The object-oriented (OO) paradigm has formalised various cohesion measures, but the argument over the most meaningful of those metrics continues to be debated. Yet achieving highly cohesive software is fundamental to its comprehension and thus its maintainability. In this article we subject two object-oriented cohesion metrics, CAMC and NHD, to a rigorous mathematical analysis in order to better understand and interpret them. This analysis enables us to offer substantial arguments for preferring the NHD metric to CAMC as a measure of cohesion. Furthermore, we provide a complete understanding of the behaviour of these metrics, enabling us to attach a meaning to the values calculated by the CAMC and NHD metrics. In addition, we introduce a variant of the NHD metric and demonstrate that it has several advantages over CAMC and NHD. While it may be true that a generally accepted formal and informal definition of cohesion continues to elude the OO software engineering community, there seems considerable value in being able to compare, contrast, and interpret metrics which attempt to measure the same features of software.

Empirical Studies of Object-Oriented Artifacts, Methods,and Processes: State of the Art and Future Directions

Object-Oriented technologies are becoming pervasive in many software development organizations. However, many methods, processes, tools, or notations are being used without thorough evaluation. Empirical studies aim at investigating the performance of such technologies and the quality of the resulting object-oriented (OO) software products. In other words, the goal is to provide a scientific foundation to the engineering of OO software. This paper summarizes the results of a working group at the Empirical Studies of Software Development and Evolution (ESSDE) workshop in Los Angeles in May 1999. The authors of this paper took part in the working group and have all been involved with various aspects of empirical studies of OO software development. We therefore hope to achieve a good coverage of the current state of the art. We provide an overview of the existing research and results, future research directions, and important issues regarding the methodology of conducting empirical studies. In Section 2, we cover existing empirical studies and we relate them to the claims usually associated with OO development technologies. Section 3 describes in depth what we believe are important directions for research and, more concretely, precise research questions. Section 4 identifies what we think are important methodological points and strategies to answer these questions.

Experimental assessment of software metrics using automated refactoring

A large number of software metrics have been proposed in the literature, but there is little understanding of how these metrics relate to one another. We propose a novel experimental technique, based on search-based refactoring, to assess software metrics and to explore relationships between them. Our goal is not to improve the program being refactored, but to assess the software metrics that guide the automated refactoring through repeated refactoring experiments. We apply our approach to five popular cohesion metrics using eight real-world Java systems, involving 300,000 lines of code and over 3,000 refactorings. Our results demonstrate that cohesion metrics disagree with each other in 55% of cases, and show how our approach can be used to reveal novel and surprising insights into the software metrics under investigation.

A comparison of development effort estimation techniques for Web hypermedia applications

Several studies have compared the prediction accuracy of different types of techniques with emphasis placed on linear and stepwise regressions, and case-based reasoning (CBR). We believe the use of only one type of CBR technique may bias the results, as there are others that can also be used for effort prediction. This paper has two objectives. The first is to compare the prediction accuracy of three CBR techniques to estimate the effort to develop Web hypermedia applications. The second objective is to compare the prediction accuracy of the best CBR technique, according to our findings, against three commonly used prediction models, namely multiple linear regression, stepwise regression and regression trees. One dataset was used in the estimation process and the results showed that different measures of prediction accuracy gave different results. MMRE and MdMRE showed better prediction accuracy for multiple regression models whereas box plots showed better accuracy for CBR.

A meta-analysis of relationships between organizational characteristics and IT innovation adoption in organizations

Adoption of IT in organizations is influenced by a wide range of factors in technology, organization, environment, and individuals. Researchers have identified several factors that either facilitate or hinder innovation adoption. Studies have produced inconsistent and contradictory outcomes. We performed a meta-analysis of ten organizational factors to determine their relative impact and strength. We aggregated their findings to determine the magnitude and direction of the relationship between organizational factors and IT innovation adoption. We found organizational readiness to be the most significant attribute and also found a moderately significant relationship between IT adoption and IS department size. Our study found weak significance of IS infrastructure, top management support, IT expertise, resources, and organizational size on IT adoption of technology while formalization, centralization, and product champion were found to be insignificant attributes. We also examined stage of innovation, type of innovation, type of organization, and size of organization as moderator conditions affecting the relationship between the organizational variables and IT adoption.