Intelligent Agent Based Mapping of Software Requirement Specification to Design Model


Automatically mapping a requirement specification to design model in Software Engineering is an open complex problem. Existing methods use a complex manual process that use the knowledge from the requirement specification/modeling and the design, and try to find a good match between them. The key task done by designers is to convert a natural language based requirement specification (or corresponding UML based representation) into a predominantly computer language based design model—thus the process is very complex as there is a very large gap between our natural language and computer language. Moreover, this is not just a simple language conversion, but rather a complex knowledge conversion that can lead to meaningful design implementation. In this paper, we describe an automated method to map Requirement Model to Design Model and thus automate/partially automate the Structured Design (SD) process. We believe, this is the first logical step in mapping a more complex requirement specification to design model. We call it IRTDM (Intelligent Agent based requirement model to design model mapping). The main theme of IRTDM is to use some AI (Artificial Intelligence) based algorithms, semantic representation using Ontology or Predicate Logic, design structures using some well known design framework and Machine Learning algorithms for learning over time. Semantics help convert natural language based requirement specification (and associated UML representation) into high level design model followed by mapping to design structures. AI method can also be used to convert high level design structures into lower level design which then can be refined further by some manual and/or semi automated process. We emphasize that automation is one of the key ways to minimize the software cost, and is very important for all, especially, for the Design for the Bottom 90% Peopleor BOP (Base of the Pyramid People).

Share and Cite:

E. Khan and M. Alawairdhi, "Intelligent Agent Based Mapping of Software Requirement Specification to Design Model," Journal of Software Engineering and Applications, Vol. 6 No. 12, 2013, pp. 630-637. doi: 10.4236/jsea.2013.612075.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] E. Khan, “Internet for Everyone: Reshaping the Glob-al Economy by Bridging the Digital Divide,” 2011.
[2] G. Abowd et al., “Structural Modeling: An Application Framework and Development Process for Flight Simulators,” CMU Technical Report CMU/SEI-93-TR-014, 1993.
[3] Structured Analysis.
[4] D. Garlan and M. Shaw, “An Introduction to Software Architecture,” Advances in Software Engineering and Knowledge Engineering, Vol. I, World Scientific Publishing Company, 1995.
[5] F. Buschmann, et al., “Pattern-Oriented Software Architecture, A System of Patterns,” Wiley, 2007.
[6] “Architecture Analysis and Design Language, Software (AADL),” Engineering Institute, Carnegie-Mellon University, 2004.
[7] P. Clements, “A Survey of Architectural Description Languages,” Paul C. Clements, Software Architecture, Software Engineering Institute, 1996.
[8] S. Greenspan, et al., “A Requirements Modeling Language and Its Logic,” Information Systems, Vol. 11, No. 1, 1986, pp. 9-23.
[9] J. Rumbaugh, et al., “The Unified Modeling Language Reference Manual,” 2nd Edition, Addison-Wesley, 2004.
[10] “Process Model Requirements Gap Analyzer,” 2012. Documents/PDF/Accenture-Process-Model-Requirements-Gap-Analyzer.pdf
[11] H. E. Okud, et al., “Experimental Development Based on Mapping Rule between Requirements Analysis Model and Web Framework Specific Design Model,” SpringerPlus Journal, Vol. 2, 2013, p. 123.
[12] R. Pressman, “Software Engineering: A Practitioner’s Approach,” McGrawHill, 2010.
[13] D. Jurafsky, et al., “Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition,” Pearson/ Prentice Hall, 2009.
[14] E. Khan, “Natural Language Based Human Computer Interaction: A Necessity for Mobile Devices,” International Journal of Computers and Communications, 2012.
[15] E. Khan, “Addressing Big Data Problems using Semantics and Natural Language Understanding,” 12th Wseas International Conference on Telecommunications and Informatics (Tele-Info ‘13), Baltimore, September 17-19, 2013.
[16] E. Khan, “Natural Language Understanding Using Brain-Like Approach: Word Objects and Word Semantics Based Approaches help Sentence Level Understanding,” Applied to US Patent Office, 2012.

Copyright © 2022 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.