Reusing empirical knowledge during cloud computing adoption

© 2017 Elsevier Inc. 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