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Change impact analysis: A systematic mapping study
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AI
DOI：10.1016/j.jss.2020.110892.png)
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Abstract
En 中文
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. (C) 2020 Elsevier Inc. All rights reserved.
Keywords:
Change impact analysis
Change proneness
Instability
Changeability
Amount of change
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4.1
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5.5K
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