Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/860
Title: Change impact analysis: A systematic mapping study
Authors: Kretsou, Maria
Arvanitou, Elvira-Maria
Ampatzoglou, Apostolos
Deligiannis, Ignatios
Gerogiannis, Vassilis C.
Type: Article
Subjects: FRASCATI::Natural sciences::Computer and information sciences
Keywords: Change impact analysis
Change proneness
Instability
Changeability
Amount of change
Issue Date: 2021
Source: Journal of Systems and Software
Volume: 174
First Page: 110892
Abstract: Change Impact Analysis (CIA) is the process of exploring the tentative effects of a change in other parts of a system. CIA is considered beneficial in practice, since it reduces cost of maintenance and the risk of software development failures. In this paper, we present a systematic mapping study that covers a plethora of CIA methods (by exploring 111 papers), putting special emphasis on how the CIA phenomenon can be quantified: to be efficiently managed. The results of our study suggest that: (a) the practical benefits of CIA cover any type of maintenance request (e.g., feature additions, bug fixing) and can help in reducing relevant cost; (b) CIA quantification relies on four parameters (instability, amount of change, change proneness, and changeability), whose assessment is supported by various metrics and predictors; and (c) in this vast research field, there are still some viewpoints that remain unexplored (e.g., the negative consequences of highly change prone artifacts), whereas others are over-researched (e.g., quantification of instability based on metrics). Based on our results, we provide: (a) useful information for practitioners—i.e., the expected benefits of CIA, and a list of CIA-related metrics, emphasizing on the provision of a detailed interpretation of their relation to CIA; and (b) interesting future research directions—i.e., over- and under-researched sub-fields of CIA.
URI: https://doi.org/10.1016/j.jss.2020.110892
https://ruomo.lib.uom.gr/handle/7000/860
ISSN: 0164-1212
Other Identifiers: 10.1016/j.jss.2020.110892
Appears in Collections:Department of Applied Informatics

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