Verification of SPL Feature Model by using Bayesian Network

Shamim Ripon; Musfiqur Rahman; Javedul Ferdous  and Md  Delwar Hossain

doi:10.17485/ijst/2016/v9i31/93731

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Verification of SPL Feature Model by using Bayesian Network

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2016/v9i31/93731

Year: 2016, Volume: 9, Issue: 31, Pages: 1-11

Original Article

Verification of SPL Feature Model by using Bayesian Network

Shamim Ripon^1*, Musfiqur Rahman², Javedul Ferdous¹ and Md. Delwar Hossain¹

¹ Department of Computer Science and Engineering, [email protected]
² Department of Computer Science and Software Engineering, Concordia University, Montreal, Canada
*Author for correspondence
Shamim Ripon
Department of Computer Science and Engineering,
Email: [email protected]bd.edu

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Feature Tree represents all the features along with their relationship of a Software Product Line. Any defect in feature model can diminish the benefits of product line approach. Hence, the analysis of feature model plays a key role towards the success of any Software Product Line. This paper presents various analysis rules for cardinality-based feature model of both dead and false optional features. These rules are then verified by using Bayesian Network Based inference mechanism. Such verification not only confirms the analysis rules of the feature trees but also ensures the applicability of probabilistic information into the feature trees.
Keywords: Bayesian Network, Dead Feature, False Optional Feature, Feature Analysis, Software Product Line