An Empirical investigation into metrics for object-oriented software

Object-Oriented methods have increased in popularity over the last decade, and are now the norm for software development in many application areas. Many claims were made for the superiority of object-oriented methods over more traditional methods, and these claims have largely been accepted, or at least not questioned by the software community. Such was the motivation for this thesis. One way of capturing information about software is the use of software metrics. However, if we are to have faith in the information, we must be satisfied that these metrics do indeed tell us what we need to know. This is not easy when the software characteristics we are interested in are intangible and unable to be precisely defined. This thesis considers the attempts to measure software and to make predictions regarding maintainabilty and effort over the last three decades. It examines traditional software metrics and considers their failings in the light of the calls for better standards of validation in terms of measurement theory and empirical study. From this five lessons were derived. The relatively new area of metrics for object-oriented systems is examined to determine whether suggestions for improvement have been widely heeded. The thesis uses an industrial case study and an experiment to examine one feature of objectorientation, inheritance, and its effect on aspects of maintainability, namely number of defects and time to implement a change. The case study is also used to demonstrate that it is possible to obtain early, simple and useful local prediction systems for important attributes such as system size and defects, using readily available measures rather than attempting predefined and possibly time consuming metrics which may suffer from poor definition, invalidity or inability to predict or capture anything of real use. The thesis concludes that there is empirical evidence to suggest a hypothesis linking inheritance and increased incidence of defects and increased maintenance effort and that more empirical studies are needed in order to test the hypothesis. This suggests that we should treat claims regarding the benefits of object-orientation for maintenance with some caution. This thesis also concludes that with the ability to produce, with little effort, accurate local metrics, we have an acceptable substitute for the large predefined metrics suites with their attendant problems

Structured Review of the Evidence for Effects of Code Duplication on Software Quality

This report presents the detailed steps and results of a structured review of code clone literature. The aim of the review is to investigate the evidence for the claim that code duplication has a negative effect on code changeability. This report contains only the details of the review for which there is not enough place to include them in the companion paper published at a conference (Hordijk, Ponisio et al. 2009 - Harmfulness of Code Duplication - A Structured Review of the Evidence)

Comprehension of object-oriented software cohesion: The empirical quagmire

Chidamber and Kemerer (1991) proposed an object-oriented (OO) metric suite which included the Lack of Cohesion Of Methods (LCOM) metric. Despite considerable effort both theoretically and empirically since then, the software engineering community is still no nearer finding a generally accepted definition or measure of OO cohesion. Yet, achieving highly cohesive software is a cornerstone of software comprehension and hence, maintainability. In this paper, we suggest a number of suppositions as to why a definition has eluded (and we feel will continue to elude) us. We support these suppositions with empirical evidence from three large C++ systems and a cohesion metric based on the parameters of the class methods; we also draw from other related work. Two major conclusions emerge from the study. Firstly, any sensible cohesion metric does at least provide insight into the features of the systems being analysed. Secondly however, and less reassuringly, the deeper the investigative search for a definitive measure of cohesion, the more problematic its understanding becomes; this casts serious doubt on the use of cohesion as a meaningful feature of object-orientation and its viability as a tool for software comprehension

Object-oriented cohesion as a surrogate of software comprehension: An empirical study

The concept of software cohesion in both the procedural and object-oriented paradigm is well known and documented. What is not so well known or documented is the perception of what empirically constitutes a cohesive 'unit' by software engineers. In this paper, we describe an empirical investigation using object-oriented (OO) classes as a basis. Twenty-four subjects (drawn from IT experienced and IT inexperienced groups) were asked to rate ten classes sampled from two industrial systems in terms of their overall cohesiveness; a class environment was used to carry out the study. Four key results were observed. Firstly, class size (when expressed in terms of number of methods) did not tend to influence the perception of cohesion by any subjects. Secondly, well-commented classes were rated most highly amongst both IT experienced and inexperienced subjects. Thirdly, the empirical study suggests that cohesion comprises a combination of various class factors including low coupling, small numbers of attributes and well-commented methods, rather than any single, individual class feature per se. Finally, the research supports the view that cohesion is a subjective concept reflecting a cognitive combination of class features; as such it is a surrogate for class comprehension

Using a Combination of Measurement Tools to Extract Metrics from Open Source Projects

Software measurement can play a major role in ensuring the quality and reliability of software products. The measurement activities require appropriate tools to collect relevant metric data. Currently, there are several such tools available for software measurement. The main objective of this paper is to provide some guidelines in using a combination of multiple measurement tools especially for products built using object-oriented techniques and languages. In this paper, we highlight three tools for collecting metric data, in our case from several Java-based open source projects. Our research is currently based on the work of Card and Glass, who argue that design complexity measures (data complexity and structural complexity) are indicators/predictors of procedural/cyclomatic complexity (decision counts) and errors (discovered from system tests). Their work was centered on structured design and our work is with object-oriented designs and the metrics we use parallel those of Card and Glass, being, Henry and Kafura's Information Flow Metrics, McCabe's Cyclomatic Complexity, and Chidamber and Kemerer Object-oriented Metrics

An empirical study of aspect-oriented metrics

Metrics for aspect-oriented software have been proposed and used to investigate the benefits and the disadvantages of crosscutting concerns modularisation. Some of these metrics have not been rigorously defined nor analytically evaluated. Also, there are few empirical data showing typical values of these metrics in aspect-oriented software. In this paper, we provide rigorous definitions, usage guidelines, analytical evaluation, and empirical data from ten open source projects, determining the value of six metrics for aspect-oriented software (lines of code, weighted operations in module, depth of inheritance tree, number of children, crosscutting degree of an aspect, and coupling on advice execution). We discuss how each of these metrics can be used to identify shortcomings in existing aspect-oriented software. (C) 2012 Elsevier B.V. All rights reserved.CNPq [140046/06-2]; Project CNPQ-PROSUL [490478/06-9]; Capes-Grices [2051-05-2]; FAPERGS [10/0470-1]; FCT MCTESinfo:eu-repo/semantics/publishedVersio