Predicting Software Test Effort in Iterative Development Using a Dynamic Bayesian Network
Blekinge Institute of Technology, School of Computing2010 (English)Conference paper (Refereed) Published
Projects following iterative software development methodologies must still be managed in a way as to maximize quality and minimize costs. However, there are indications that predicting test effort in iterative development is challenging and currently there seem to be no models for test effort prediction. This paper introduces and validates a dynamic Bayesian network for predicting test effort in iterative software devel- opment. The proposed model is validated by the use of data from two industrial projects. The accuracy of the results has been verified through different prediction accuracy measurements and statistical tests. The results from the validation confirm that the model has the ability to predict test effort in iterative projects accurately.
Place, publisher, year, edition, pages
San Jose, CA: IEEE , 2010.
agile, Bayesian, prediction
Software Engineering Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:bth-7685Local ID: oai:bth.se:forskinfoA497CC3DD22D5361C12578010070793FOAI: oai:DiVA.org:bth-7685DiVA: diva2:835329
21st IEEE International Symposium on Software Reliability Engineering