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

Classification of Reverse-Engineered Class Diagram and Forward-Engineered Class Diagram using Machine Learning