Aspect Oriented Programming - Cognitive Complexity Metric Analysis Tool

Authors(2) :-G. Arockia Sahaya Sheela, Dr. A. Aloysius

Metrics extent assured properties of a software system by representing them to numbers (or to other symbols) rendering to well-defined, objective measurement rules. Examining aspect-oriented systems in order to estimate their quality advances its significance as the paradigm remains to increase in popularity. Subsequently, numerous aspect-oriented metrics have been proposed to estimate different aspects of these systems. Aspect Cognitive Complexity Metric are the newly arisen area of complexity metric. This paper describes AOP-CCMAT (Aspect Oriented Programming - Cognitive Complexity Metric Analysis Tool) that is meant for automatically calculate the Cognitive Complexity metrics. Evaluating the AO metrics based on cognitive complexity is supportive for expecting the maintainability of the software. The measurement of Cognitive Complexity is also necessary to calculate the software quality.

Authors and Affiliations

G. Arockia Sahaya Sheela
Assistant Professor, Department of Computer Science, Holy Cross College, Trichy, Tamil Nadu, India
Dr. A. Aloysius
Assistant Professor, Department of Computer Science,St. Joseph’s College, Trichy, Tamil Nadu, India

Aspect Cognitive Complexity Metric Analysis Tool, Cognitive Complexity, Software metrics, Software quality.

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Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 480-486
Manuscript Number : CSEIT183153
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

G. Arockia Sahaya Sheela, Dr. A. Aloysius, "Aspect Oriented Programming - Cognitive Complexity Metric Analysis Tool", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.480-486, January-February-2018.
Journal URL : http://ijsrcseit.com/CSEIT183153

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