Abstract
The study of change impact is a fundamental activity in software engineering because it can be used to plan changes, set them up and to predict or detect their effects on the system and try to reduce them. Various methods have been presented in the literature for this sector of maintenance. The objective of this project is to improve the maintenance of Object Oriented (OO) systems and to intervene more specifically in the task of analyzing and predicting the change impact. Among several models of representation, Bayesian Networks (BNs) constitute a particular quantitative approach that can integrate uncertainty in reasoning and offering explanations close to reality. Furthermore, with the BNs, it is also possible to use expert judgments to anticipate the predictions, about the change impact in our case. In this paper, we propose a probabilistic approach to determine the change impact in OO systems. This prediction is given in a form of probability.
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Cherif, C., Abdi, M.K. (2013). Change Impact Study by Bayesian Networks. In: Amine, A., Otmane, A., Bellatreche, L. (eds) Modeling Approaches and Algorithms for Advanced Computer Applications. Studies in Computational Intelligence, vol 488. Springer, Cham. https://doi.org/10.1007/978-3-319-00560-7_46
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DOI: https://doi.org/10.1007/978-3-319-00560-7_46
Publisher Name: Springer, Cham
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