%0 Journal Article
	%A Dr. L. Arockiam and  A. Aloysius
	%D 2011
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 58, 2011
	%T Attribute Weighted Class Complexity: A New Metric for Measuring Cognitive Complexity of OO Systems
	%U https://publications.waset.org/pdf/2886
	%V 58
	%X In general, class complexity is measured based on any
one of these factors such as Line of Codes (LOC), Functional points
(FP), Number of Methods (NOM), Number of Attributes (NOA) and so on. There are several new techniques, methods and metrics with
the different factors that are to be developed by the researchers for calculating the complexity of the class in Object Oriented (OO)
software. Earlier, Arockiam et.al has proposed a new complexity measure namely Extended Weighted Class Complexity (EWCC)
which is an extension of Weighted Class Complexity which is proposed by Mishra et.al. EWCC is the sum of cognitive weights of
attributes and methods of the class and that of the classes derived. In EWCC, a cognitive weight of each attribute is considered to be 1.
The main problem in EWCC metric is that, every attribute holds the
same value but in general, cognitive load in understanding the
different types of attributes cannot be the same. So here, we are proposing a new metric namely Attribute Weighted Class Complexity
(AWCC). In AWCC, the cognitive weights have to be assigned for the attributes which are derived from the effort needed to understand
their data types. The proposed metric has been proved to be a better
measure of complexity of class with attributes through the case studies and experiments
	%P 1151 - 1156