Limitations of an object-oriented metric: Weighted complexity measure

Abstract

Many computer science practitioners and software developers believes that the complexity of a program could be controlled more effectively by using object-oriented programming concepts. In addition to controlling complexity, the object-oriented approach allows faster development, reduction in costs, higher quality, easier maintenance, increased scalability, better information structures, and increased adaptability. As such, more and more programs are written using the object-oriented programming approach rather than using the traditional functional approach. This demand has spurred the provision for a number of object-oriented metrics. Out of them, Chidamber and Kemerers' metrics suite is one of the most prominent object-oriented metrics that has been proposed. It has been widely validated and has been accepted as a useful predictor of object-oriented design complexity. But it does not consider the complexities that occur due to factors such as the nesting level and type of control structures, and the size of the program. Thus, Chhillar and Bhasins' introduced the weighted complexity measure to address these issues. It is the only metric which considers the complexities that occur due to inheritance level of statements, nesting level and type of control structures, and the size of the program. However, weighted complexity measure also has some limitations. This paper attempts to draw the readers' attention to those limitations, with the hope that it will be further improved by addressing them.