Date of Award
Culminating Project Type
Computer Science: M.S.
Computer Science and Information Technology
School of Science and Engineering
Dr. Maninder Singh
Dr. Andrew A. Anda
Dr. Aleksandar Tomovic
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Keywords and Subject Headings
Object detection, Text Extraction, UML diagram, Faster-RCNN, Requirement Verification, Software Design
Unified Modeling Language (UML) class diagrams are widely used throughout software design lifecycle to model the Software Requirement Specifications in developing any software. In many cases these class diagrams are initially drawn, as well as subsequently revised using hand in a piece of paper, or a whiteboard. Although these hand-drawn class diagrams capture most of the specifications, they need a lot of revision and visual inspection by the software architects for verification of the captured requirements, of the system being modeled. Manually verifying the correctness and completeness of the class diagrams involves a lot of redundant work, and can raise issues due to human errors, for e.g., diagrams not drawn to scale, typeface issues, unclear handwriting, and even missing requirements etc. In this paper, we propose a state-of-the-art technique that pipelines the object detection, text extraction and replication phase to parse requirements incorporated within the user-drawn class diagrams. The parsed output from the proposed system, can be used to keyword-match the requirements in the Software Requirement Specification (SRS) document. We show that the proposed system can localize the UML classes and relationships in the diagram with 100% accuracy and can identify the localized objects of each type with maximum mean Average Precision of 0.8584. We also show that the text can be efficiently parsed from the diagrams with the character error rate of 0.3043.
Gautam, Sandip, "Parsing Structural and Textual Information from UML Class diagrams to assist in verification of requirement specifications" (2022). Culminating Projects in Computer Science and Information Technology. 38.