Paper Info
Title
A Bayesian Network Approach to Assess and Predict Software Quality Using Activity-Based Quality Models (Conference Version).
Abstract
Assessing and predicting the complex concept of software quality is still challenging in practice as well as research. Activity-based quality models break down this complex con- cept into more concrete definitions, more precisely facts about the system, process and environment and their impact on ac- tivities performed on and with the system. However, these models lack an operationalisation that allows to use them in assessment and prediction of quality. Bayesian Networks (BN) have been shown to be a viable means for assessment and prediction incorporating variables with uncertainty. This paper describes how activity-based quality models can be used to derive BN models for quality assessment and pre- diction. The proposed approach is demonstrated in a proof of concept using publicly available data.
Year
DOI
Venue
2016
10.1145/1540438.1540447
CoRR
DocType
Volume
ISSN
Journal
abs/1611.10187
Proceedings of the 5th International Conference on Predictor Models in Software Engineering (PROMISE '09). ACM, 2009
Citations 
PageRank 
References 
0
0.34
0
Authors
1
Name
Order
Citations
PageRank
Stefan Wagner196.41