Showing papers on "Halstead complexity measures published in 2001"
01 Aug 2001
TL;DR: The Maintainability Index is a composite metric that incorporates a number of traditional source code metrics into a single number that indicates relative maintainability.
Abstract: For many years now, software practitioners have been collecting metrics from source code in an effort to better understand the software they are developing or changing. Maintainability Index (MI) is a composite metric that incorporates a number of traditional source code metrics into a single number that indicates relative maintainability. As originally proposed by Oman and Hagemeister, the MI is comprised of weighted Halstead metrics (effort or volume), McCabe's Cyclomatic Complexity, lines of code (LOC), and number of comments [1, 2]. Two equations were presented: one that considered comments and one that did not.
49 citations
07 Nov 2001
TL;DR: The main focus of the thesis was in the identification and validation, both theoretical and empirical, of Object-Oriented metrics for complexity, and then, effort estimation.
Abstract: In this paper an abstract of the Ph.D. thesis discussed at the University of Florence by the author is presented. The main focus of the thesis was in the identification and validation, both theoretical and empirical, of Object-Oriented metrics for complexity, and then, effort estimation. Complexity/effort metrics have been validated against test cases for verifying effectiveness of the estimation for evaluating development and maintenance effort.
8 citations
10 Oct 2001
TL;DR: An approach to using established object-oriented software metrics as complexity/coupling and thus risk indicators early in the system development lifecycle is discussed and a medium-scale inter-domain network and service management system, developed in UML, is subject to the metric assessment.
Abstract: Current use of software metrics in the industry focuses on the cost and effort estimation, while some research was carried out in the direction of their use as fault indicators. Empirical studies in software measurement are scarce, especially in the realm of object-oriented metrics, while there is no record of management system assessment using these metrics. We discuss an approach to using established object-oriented software metrics as complexity/coupling and thus risk indicators early in the system development lifecycle. Further, we subject a medium-scale inter-domain network and service management system, developed in UML, to the metric assessment, and present an analysis of these measurements. This system was developed in a European Commission-sponsored ACTS research project - TRUMPET. Results indicate that the highest level of complexity, and thus also risk, is exhibited at major interconnection points between autonomous management domains. Moreover, the results imply a strong ordinal correlation between the metrics.
6 citations