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DOI: 10.14569/IJACSA.2011.020205
PDF

Knowledge-Based System’s Modeling for Software Process Model Selection

Author 1: Abdur Abdur Khan
Author 2: Zia Ur Rehman
Author 3: Hafeez Ullah Amin

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 2 Issue 2, 2011.

  • Abstract and Keywords
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Abstract: This paper depicts the knowledge-based system named as ESPMS (Expert System for Process Model Selection) through various models. A questionnaire was developed to identify important parameters, which were evaluated through domain experts in about all the universities of Pakistan. No exact system was found, which could guide Software Engineers for selection of a proper model during software development. This paper shows that how various technologies like Fuzzy Logic, Certainty Factors, and Analytical Hierarchy Process (AHP) can be adopted to develop the Expert System. Priorities assignments to critical factors have been shown for decision making in the model selection for a problem domain. This research work will be beneficial to both students and researchers for integrating Soft Computing Techniques and Software Engineering.

Keywords: ESPMS, Expert System, Analytical Hierarchy Process, Certainty Factors, Fuzzy Logic, Decision-Making

Abdur Abdur Khan, Zia Ur Rehman and Hafeez Ullah Amin. “Knowledge-Based System’s Modeling for Software Process Model Selection”. International Journal of Advanced Computer Science and Applications (IJACSA) 2.2 (2011). http://dx.doi.org/10.14569/IJACSA.2011.020205

@article{Khan2011,
title = {Knowledge-Based System’s Modeling for Software Process Model Selection},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2011.020205},
url = {http://dx.doi.org/10.14569/IJACSA.2011.020205},
year = {2011},
publisher = {The Science and Information Organization},
volume = {2},
number = {2},
author = {Abdur Abdur Khan and Zia Ur Rehman and Hafeez Ullah Amin}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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