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31st IEEE Software Engineering Workshop (SEW 2007)
A New Way to Predict Software Reliability with Parameter Evaluation: Shuttle Applications
Columbia, MD, USA
March 06-March 08
ISBN: 0-7695-2862-7
ASCII Text
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Norman F. Schneidewind, "A New Way to Predict Software Reliability with Parameter Evaluation: Shuttle Applications," Software Engineering Workshop, Annual IEEE/NASA Goddard, pp. 167-178, 31st IEEE Software Engineering Workshop (SEW 2007), 2007.
 
 
BibTex
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@article{ 10.1109/SEW.2007.85,
author = {Norman F. Schneidewind},
title = {A New Way to Predict Software Reliability with Parameter Evaluation: Shuttle Applications},
journal ={Software Engineering Workshop, Annual IEEE/NASA Goddard},
volume = {0},
year = {2007},
issn = {1550-6215},
pages = {167-178},
doi = {http://doi.ieeecomputersociety.org/10.1109/SEW.2007.85},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Software Engineering Workshop, Annual IEEE/NASA Goddard
TI - A New Way to Predict Software Reliability with Parameter Evaluation: Shuttle Applications
SN - 1550-6215
SP167
EP178
A1 - Norman F. Schneidewind,
PY - 2007
VL - 0
JA - Software Engineering Workshop, Annual IEEE/NASA Goddard
ER -
 
Software reliability measurement and prediction are used to evaluate model parameters in advance of applying a model. Measurement involves collecting and analyzing data about the observed reliability of software, from which the parameters are estimated, for example, the occurrence of failures during test. Prediction is using a model to forecast future software reliability, for example, time to next failure during operation. Once the parameters are estimated, using the methodology we will demonstrate, we can rank the software releases by their projected relative reliability in order to rationally allocate resources to prediction and testing activities.
Citation:
Norman F. Schneidewind, "A New Way to Predict Software Reliability with Parameter Evaluation: Shuttle Applications," sew, pp.167-178, 31st IEEE Software Engineering Workshop (SEW 2007), 2007
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