Abstract
Proper management of requirements plays a significant role in the successful development of any software product family. Application of AI, Bayesian Network (BN) in particular, is gaining much interest in Software Engineering, mainly in predicting software defects and software reliability. Feature analysis and its associated decision making is a suitable target area where BN can make remarkable effect. In SPL, a feature tree portrays various types of features as well as captures the relationships among them. This paper applies BN in modeling and analyzing features in a feature tree. Various feature analysis rules are first modeled and then verified in BN. The verification confirms the definition of the rules and thus these rules can be used in various decision making stages in SPL.
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Rahman, M., Ripon, S. (2014). Using Bayesian Networks to Model and Analyze Software Product Line Feature Model. In: Murty, M.N., He, X., Chillarige, R.R., Weng, P. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2014. Lecture Notes in Computer Science(), vol 8875. Springer, Cham. https://doi.org/10.1007/978-3-319-13365-2_20
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DOI: https://doi.org/10.1007/978-3-319-13365-2_20
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