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Πλήρης εγγραφή μεταδεδομένων
Πεδίο DC | Τιμή | Γλώσσα |
---|---|---|
dc.contributor.author | Kretsou, Maria | - |
dc.contributor.author | Arvanitou, Elvira-Maria | - |
dc.contributor.author | Ampatzoglou, Apostolos | - |
dc.contributor.author | Deligiannis, Ignatios | - |
dc.contributor.author | Gerogiannis, Vassilis C. | - |
dc.date.accessioned | 2020-12-29T06:30:02Z | - |
dc.date.available | 2020-12-29T06:30:02Z | - |
dc.date.issued | 2021 | - |
dc.identifier | 10.1016/j.jss.2020.110892 | en_US |
dc.identifier.issn | 0164-1212 | en_US |
dc.identifier.uri | https://doi.org/10.1016/j.jss.2020.110892 | en_US |
dc.identifier.uri | https://ruomo.lib.uom.gr/handle/7000/860 | - |
dc.description.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. | en_US |
dc.language.iso | en | en_US |
dc.source | Journal of Systems and Software | en_US |
dc.subject | FRASCATI::Natural sciences::Computer and information sciences | en_US |
dc.subject.other | Change impact analysis | en_US |
dc.subject.other | Change proneness | en_US |
dc.subject.other | Instability | en_US |
dc.subject.other | Changeability | en_US |
dc.subject.other | Amount of change | en_US |
dc.title | Change impact analysis: A systematic mapping study | en_US |
dc.type | Article | en_US |
dc.contributor.department | Τμήμα Εφαρμοσμένης Πληροφορικής | en_US |
local.identifier.volume | 174 | en_US |
local.identifier.firstpage | 110892 | en_US |
Εμφανίζεται στις Συλλογές: | Τμήμα Εφαρμοσμένης Πληροφορικής |
Αρχεία σε αυτό το Τεκμήριο:
Αρχείο | Περιγραφή | Μέγεθος | Μορφότυπος | |
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kretsou2020jss.R1.pdf | 1,23 MB | Adobe PDF | Προβολή/Ανοιγμα |
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