TY - JFULL AU - Dr. L. Arockiam and A. Aloysius PY - 2011/11/ TI - Attribute Weighted Class Complexity: A New Metric for Measuring Cognitive Complexity of OO Systems T2 - International Journal of Computer and Information Engineering SP - 1150 EP - 1156 VL - 5 SN - 1307-6892 UR - https://publications.waset.org/pdf/2886 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 58, 2011 N2 - 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 ER -