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A Bayesian Network Based Approach for Change Coupling Prediction


Zhou, Y; Wuersch, M; Giger, E; Gall, H C; Lue, J (2008). A Bayesian Network Based Approach for Change Coupling Prediction. In: Working Conference on Reverse Engineering, Antwerp, Belgium, 15 October 2008 - 18 October 2008, 27-36.

Abstract

Source code coupling and change history are two important data
sources for change coupling analysis. The popularity of public open
source projects in recent years makes both sources available. Based
on our previous research, in this paper, we inspect different
dimensions of software changes including change significance or source code
dependency levels, extract a set of features from the two
sources and propose a bayesian network-based approach for
change coupling prediction. By combining the features from the co-changed entities
and their dependency relation, the approach can model the underlying
uncertainty. The empirical case study on two medium-sized
open source projects demonstrates the feasibility and effectiveness
of our approach compared to previous work.

Abstract

Source code coupling and change history are two important data
sources for change coupling analysis. The popularity of public open
source projects in recent years makes both sources available. Based
on our previous research, in this paper, we inspect different
dimensions of software changes including change significance or source code
dependency levels, extract a set of features from the two
sources and propose a bayesian network-based approach for
change coupling prediction. By combining the features from the co-changed entities
and their dependency relation, the approach can model the underlying
uncertainty. The empirical case study on two medium-sized
open source projects demonstrates the feasibility and effectiveness
of our approach compared to previous work.

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17 citations in Web of Science®
31 citations in Scopus®
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192 downloads since deposited on 29 Jan 2009
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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:18 October 2008
Deposited On:29 Jan 2009 12:00
Last Modified:06 Dec 2017 16:24
Publisher DOI:https://doi.org/10.1109/WCRE.2008.39

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