An Application of Uncertain Reasoning to Requirements Engineering
Software Engineering
2013-01-30 v1 Artificial Intelligence
Abstract
This paper examines the use of Bayesian Networks to tackle one of the tougher problems in requirements engineering, translating user requirements into system requirements. The approach taken is to model domain knowledge as Bayesian Network fragments that are glued together to form a complete view of the domain specific system requirements. User requirements are introduced as evidence and the propagation of belief is used to determine what are the appropriate system requirements as indicated by user requirements. This concept has been demonstrated in the development of a system specification and the results are presented here.
Keywords
Cite
@article{arxiv.1301.6678,
title = {An Application of Uncertain Reasoning to Requirements Engineering},
author = {Philip S. Barry and Kathryn Blackmond Laskey},
journal= {arXiv preprint arXiv:1301.6678},
year = {2013}
}
Comments
Appears in Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI1999)