Paper Info
Title
A framework for integrated software quality prediction using Bayesian nets
Abstract
The aim of this study is to develop a framework for integrated software quality prediction. This integration is reflected by a range of quality attributes incorporated in the model as well as relationships between these attributes. The model is formulated as a Bayesian net, a technique that has already been used in various software engineering studies. The framework enables to incorporate expert knowledge about the domain as well as related empirical data and encode them in the Bayesian net model. Such model may be used in decision support for software analysts and managers.
Year
DOI
Venue
2011
10.1007/978-3-642-21934-4_26
ICCSA (5)
Keywords
Field
DocType
decision support,software analyst,bayesian net,integrated software quality prediction,various software engineering study,empirical data,expert knowledge,framework
ENCODE,Data mining,Mathematical optimization,Computer science,Decision support system,Software quality prediction,Software,Artificial intelligence,Integrated software,Machine learning,Bayesian probability
Conference
Volume
ISSN
Citations 
6786
0302-9743
2
PageRank 
References 
Authors
0.37
16
1
Name
Order
Citations
PageRank
Łukasz Radliński1895.34