Browsing by Author "Gupta, Manjari"

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Citation - WoS: 14
Citation - Scopus: 25
Automatic Classification of UML Class Diagrams Using Deep Learning Technique: Convolutional Neural Network
(Mdpi, 2021) Gosala, Bethany; Chowdhuri, Sripriya Roy; Singh, Jyoti; Gupta, Manjari; Mishra, Alok
Unified Modeling Language (UML) includes various types of diagrams that help to study, analyze, document, design, or develop any software efficiently. Therefore, UML diagrams are of great advantage for researchers, software developers, and academicians. Class diagrams are the most widely used UML diagrams for this purpose. Despite its recognition as a standard modeling language for Object-Oriented software, it is difficult to learn. Although there exist repositories that aids the users with the collection of UML diagrams, there is still much more to explore and develop in this domain. The objective of our research was to develop a tool that can automatically classify the images as UML class diagrams and non-UML class diagrams. Earlier research used Machine Learning techniques for classifying class diagrams. Thus, they are required to identify image features and investigate the impact of these features on the UML class diagrams classification problem. We developed a new approach for automatically classifying class diagrams using the approach of Convolutional Neural Network under the domain of Deep Learning. We have applied the code on Convolutional Neural Networks with and without the Regularization technique. Our tool receives JPEG/PNG/GIF/TIFF images as input and predicts whether it is a UML class diagram image or not. There is no need to tag images of class diagrams as UML class diagrams in our dataset.
Citation - WoS: 1
Citation - Scopus: 1
Design Patterns Discovery in Source Code: Novel Technique Using Substring Match
(Assoc information Communication Technology Education & Science, 2021) Pande, Akshara; Pant, Vivekanand; Gupta, Manjari; Mishra, Alok
The role of design pattern mining is a very significant strategy of re-engineering as with the help of detection one could easily understand complex systems. Of course, identifying a design pattern is not always a simple task. Additionally, pattern recovering methods often encounter problems dealing with space outburst for extensive systems. This paper introduces a new way to discover a design pattern based on an Impact Analysis matrix followed by substring match. UML diagrams corresponding to codes are created using Visual Paradigm Enterprise. Impact Analysis matrices of these UML diagrams are converted to string format. Considering system code string as main string and design pattern string as a substring, the main string is further decomposed. A substring match technique is developed here to discover design patterns in the source code. Overall, this procedure has the potential to convert the representation of system design and design pattern in ingenious shapes. In addition, this method has the advantage of moderation in the size. Therefore, this approach is beneficial for Software professionals and researchers due to its simplicity.