Predicting Software Test Effort in Iterative Development Using a Dynamic Bayesian Network

Document type: Conference Papers
Peer reviewed: Yes
Full text:
Author(s): Richard Torkar, Nasir Majeed Awan, Adnan Khadem Alvi, Wasif Afzal
Title: Predicting Software Test Effort in Iterative Development Using a Dynamic Bayesian Network
Conference name: 21st IEEE International Symposium on Software Reliability Engineering
Year: 2010
Publisher: IEEE
City: San Jose, CA
Organization: Blekinge Institute of Technology
Department: School of Computing (Sektionen för datavetenskap och kommunikation)
School of Computing S-371 79 Karlskrona
+46 455 38 50 00
http://www.bth.se/com
Authors e-mail: rto@bth.se
Language: English
Abstract: 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.
Subject: Software Engineering\General
Mathematics\Probability and Statistics
Keywords: agile, Bayesian, prediction
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