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29th Annual IEEE/NASA Software Engineering Workshop
Bayesian Networks applied to Software IV&V
Greenbelt, Maryland
April 06-April 07
ISBN: 0-7695-2306-4
ASCII Text
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Ganesh Pai, Joanne Bechta-Dugan, Khalid Lateef, "Bayesian Networks applied to Software IV&V," Software Engineering Workshop, Annual IEEE/NASA Goddard, pp. 293-304, 29th Annual IEEE/NASA Software Engineering Workshop, 2005.
 
 
BibTex
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@article{ 10.1109/SEW.2005.20,
author = {Ganesh Pai and Joanne Bechta-Dugan and Khalid Lateef},
title = {Bayesian Networks applied to Software IV&V},
journal ={Software Engineering Workshop, Annual IEEE/NASA Goddard},
volume = {0},
year = {2005},
isbn = {0-7695-2306-4},
pages = {293-304},
doi = {http://doi.ieeecomputersociety.org/10.1109/SEW.2005.20},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Software Engineering Workshop, Annual IEEE/NASA Goddard
TI - Bayesian Networks applied to Software IV&V
SN - 0-7695-2306-4
SP293
EP304
A1 - Ganesh Pai,
A1 - Joanne Bechta-Dugan,
A1 - Khalid Lateef,
PY - 2005
KW - Use cases
KW - software requirements speci.cations
KW - probabilistic networks
KW - independent veri.cation and validation
KW - software reliability engineering.
VL - 0
JA - Software Engineering Workshop, Annual IEEE/NASA Goddard
ER -
 
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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