AnModeler: A tool for generating domain models from textual specifications

This paper presents AnModeler, a tool for generating analysis models from software requirements specified using use cases. The tool uses the Stanford natural language parser to extract type dependencies (TDs) and parts of speech tags (POS-tags) of sentences from input Use Case Specification (UCS). T...

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Bibliographic Details
Published in:Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering pp. 828 - 833
Main Authors: Thakur, Jitendra Singh, Gupta, Atul
Format: Conference Proceeding
Language:English
Published: ACM 01.09.2016
Subjects:
Analysis class diagram
Analytical models
Automated approach
Automated tool for analysis modeling
Industries
Java
Model transformation
Object oriented modeling
Problem level sequence diagram
Software
Template code
Unified modeling language
Visualization
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Summary:This paper presents AnModeler, a tool for generating analysis models from software requirements specified using use cases. The tool uses the Stanford natural language parser to extract type dependencies (TDs) and parts of speech tags (POS-tags) of sentences from input Use Case Specification (UCS). Then, it identifies sentence structures using a set of rules framed based on Hornby's verb patterns. With the information of the TDs, POS tags, and the identified sentence structures, the tool discovers domain elements, viz.: domain objects (including their attributes and operations) and interactions between them; it consolidates the domain information as a class diagram (as well as a sequence diagram). An experiment conducted on 10 UCSs with two industry experts as subjects showed that the analysis class diagrams generated by AnModeler were remarkably close to those generated by the two industry experts. Being lightweight and easy to use, the tool can also be used to assist students and young developers in acquiring object-oriented domain modeling skills quickly. Link to a short demonstration video: https://youtu.be/_Ct-qF4Y1fU.
DOI:10.1145/2970276.2970289