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Bayesian Networks applied to Software IV&V
Greenbelt, Maryland April 06-April 07
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SEW.2005.2029th Annual IEEE/NASA Software Engine ...
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Ganesh Pai, University of Virginia, Department of ECE, Charlottesville, Virginia, USA
Joanne Bechta-Dugan, University of Virginia, Department of ECE, Charlottesville, Virginia, USA
Khalid Lateef, TITAN Corporation, Greenbelt, Maryland, USA

In this paper, we describe how Bayesian networks can be used to merge quantitative and qualitative information to support IV&V of use cases. Essentially, simple metrics from the use cases are computed, which are then input to a Bayesian network. This network models the relationships between the observable parameters of an IV&V process for use cases, and the desired features of the requirements specifications. The output of the network is an assessment of the maturity of the requirements, in terms of the probability that they exhibit the desired properties. We apply our proposed approach to a real system: a software simulator built to test attitude control for an aerospace system, to illustrate how IV&V can be quantitatively supported.

Index Terms:
Use cases, software requirements speci.cations,probabilistic networks, independent veri.cation and validation, software reliability engineering.
Citation:
Ganesh Pai, Joanne Bechta-Dugan, Khalid Lateef, "Bayesian Networks applied to Software IV&V," sew, pp.293-304, 29th Annual IEEE/NASA Software Engineering Workshop, 2005
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