Requirements Engineering Framework for Service and Cloud Computing (REF-SCC)

Author(s):  
Krishan Chand ◽  
Muthu Ramachandran

Cloud computing services mature both economically and technologically and play a more and more extensive role in the domain of software and information systems engineering. SaaS offers advantage for both service providers and consumers. SaaS is faced with the question of appropriate techniques applying at early phase of Requirements engineering of producing system. The paper highlights two traditional methods namely i* and VORD belonging respectively to Goal oriented Requirements Engineering and Viewpoints approaches. The approach proposed try to dealing with the requirements elicitation in the context of Software-as-a-service SaaS. So, the approach benefits from strengths of both VORD and i* models and propose a combination of them in a new approach namely VORDi*.


Author(s):  
Holger Schrödl ◽  
Stefan Wind

In industrial practice, cloud computing is becoming increasingly established as an option for formulating cost-efficient and needs-oriented information systems. Despite the increasing acceptance of cloud computing within the industry, many fundamental questions remain unanswered, or are answered only partially. Besides issues relating to the best architectures, legal issues, and pricing models, suppliers of cloud-based solutions are faced with the issue of appropriate requirements engineering. This means eliciting optimal understanding of the customer’s requirements and implementing this into appropriate requirements of the solution to be realised. This chapter examines selected, established requirements engineering methods in order to study the extent to which they can be applied to the specific requirements of cloud-based solutions. Furthermore, it develops a comparison framework containing the features of cloud computing. This comparison framework is applied to four established process models for requirements engineering. Recommendations for a requirements engineering process adapted to cloud computing are derived.


Author(s):  
Ana Sofia Zalazar ◽  
Luciana Ballejos ◽  
Sebastian Rodriguez

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