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The Technical Debt in Cloud Software Engineering: A Prediction-Based and Quantification Approach
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Author(s): Georgios Skourletopoulos (Scientia Consulting S.A., Greece), Rami Bahsoon (University of Birmingham, UK), Constandinos X. Mavromoustakis (University of Nicosia, Cyprus)and George Mastorakis (Technological Educational Institute of Crete, Greece)
Copyright: 2015
Pages: 19
Source title:
Resource Management of Mobile Cloud Computing Networks and Environments
Source Author(s)/Editor(s): George Mastorakis (Technological Educational Institute of Crete, Greece), Constandinos X. Mavromoustakis (University of Nicosia, Cyprus)and Evangelos Pallis (Technological Educational Institute of Crete, Greece)
DOI: 10.4018/978-1-4666-8225-2.ch002
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Abstract
Predicting and quantifying promptly the Technical Debt has turned into an issue of significant importance over recent years. In the cloud marketplace, where cloud services can be leased, the difficulty to identify the Technical Debt effectively can have a significant impact. In this chapter, the probability of introducing the Technical Debt due to budget and cloud service selection decisions is investigated. A cost estimation approach for implementing Software as a Service (SaaS) in the cloud is examined, indicating three scenarios for predicting the incurrence of Technical Debt in the future. The Constructive Cost Model (COCOMO) is used in order to estimate the cost of the implementation and define a range of secureness by adopting a tolerance value for prediction. Furthermore, a Technical Debt quantification approach is researched for leasing a cloud Software as a Service (SaaS) in order to provide insights about the most appropriate cloud service to be selected.
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