Reusing empirical knowledge during cloud computing adoption

Article


Fahmideh, Mahdi and Beydoun, Ghassan. 2018. "Reusing empirical knowledge during cloud computing adoption." Journal of Systems and Software. 138, pp. 124-157. https://doi.org/10.1016/j.jss.2017.12.011
Article Title

Reusing empirical knowledge during cloud computing adoption

ERA Journal ID18045
Article CategoryArticle
AuthorsFahmideh, Mahdi and Beydoun, Ghassan
Journal TitleJournal of Systems and Software
Journal Citation138, pp. 124-157
Number of Pages34
YearApr 2018
Place of PublicationUnited States
ISSN0164-1212
1873-1228
Digital Object Identifier (DOI)https://doi.org/10.1016/j.jss.2017.12.011
Web Address (URL)https://www.sciencedirect.com/science/article/pii/S0164121217303047
Abstract

Moving existing legacy systems to cloud platforms is an ever popular option. But, such endeavour may not be hazard-free and demands a proper understanding of requirements and risks involved prior to taking any action. The time is indeed ripe to undertake a realistic view of what migrating legacy systems to cloud may offer, an understanding of exceptional situations causing system quality goal failure in such a transition, and insights on countermeasures. The cloud migration body of knowledge, although is useful, is dispersed over the current literature. It is hard for busy practitioners to digest, synthesize, and harness this body of knowledge into practice when integrating legacy systems with cloud services. We address this issue by creating an innovative synergy between the approaches evidence-based software engineering and goal-oriented modelling. We develop an evidential repository of commonly occurred obstacles and platform agnostic resolution tactics related to cloud enablement of legacy systems. The repository is further utilized during systematic goal-obstacle elaboration of given cloud migration scenarios. The applicability of our proposed framework is also demonstrated.

KeywordsCloud computing adoption; Legacy systems; Evidence-based software engineering; Goal-oriented requirement engineering; Legacy system reengineering
ANZSRC Field of Research 2020460908. Information systems organisation and management
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Byline AffiliationsUniversity of Technology Sydney
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