Extension of Object-Oriented Metrics Suite for Software Maintenance
Author(s) -
John Michura,
Miriam A. M. Capretz,
Shuying Wang
Publication year - 2013
Publication title -
isrn software engineering
Language(s) - English
Resource type - Journals
eISSN - 2090-7680
pISSN - 2090-7672
DOI - 10.1155/2013/276105
Subject(s) - maintainability , computer science , software metric , suite , software maintenance , set (abstract data type) , measure (data warehouse) , data mining , class (philosophy) , programming complexity , software , object oriented programming , software system , software engineering , software construction , artificial intelligence , programming language , archaeology , history
Software developers require information to understand the characteristics of systems, such as complexity and maintainability. In order to further understand and determine characteristics of object-oriented (OO) systems, this paper describes research that identifies attributes that are valuable in determining the difficulty in implementing changes during maintenance, as well as the possible effects that such changes may produce. A set of metrics are proposed to quantify and measure these attributes. The proposed complexity metrics are used to determine the difficulty in implementing changes through the measurement of method complexity, method diversity, and complexity density. The paper establishes impact metrics to determine the potential effects of making changes to a class and dependence metrics that are used to measure the potential effects on a given class resulting from changes in other classes. The case study shows that the proposed metrics provide additional information not sufficiently provided by the related existing OO metrics. The metrics are also found to be useful in the investigation of large systems, correlating with project outcomes.
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