  UML Class diagram is very important to visualize the whole software we are
working on and helps understand the whole system in the easiest way possible by
showing the system classes, its attributes, methods, and relations with other
objects. In the real world, there are two types of Class diagram engineers work
with namely 1) Forward Engineered Class Diagram (FwCD) which are hand-made as
part of the forward-looking development process, and 2). Reverse Engineered
Class Diagram (RECD) which are those diagrams that are reverse engineered from
the source code. In the software industry while working with new open software
projects it is important to know which type of class diagram it is. Which UML
diagram was used in a particular project is an important factor to be known? To
solve this problem, we propose to build a classifier that can classify a UML
diagram into FwCD or RECD. We propose to solve this problem by using a
supervised Machine Learning technique. The approach in this involves analyzing
the features that are useful in classifying class diagrams. Different Machine
Learning models are used in this process and the Random Forest algorithm has
proved to be the best out of all. Performance testing was done on 999 Class
diagrams.
