The technical debt in cloud software engineering: A prediction-based and quantification approach

Georgios Skourletopoulos, Mavromoustakis M. Constandinos, Rami Bahsoon, George Mastorakis

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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 SService (SaaS) in order to provide insights about the most appropriate cloud service to be selected.

Original languageEnglish
Title of host publicationResource Management of Mobile Cloud Computing Networks and Environments
PublisherIGI Global
Pages24-42
Number of pages19
ISBN (Electronic)9781466682276
ISBN (Print)9781466682269
DOIs
Publication statusPublished - 31 Mar 2015

Keywords

  • Cloud service capacity
  • Cloud software engineering
  • Constructive cost model (COCOMO)
  • Implementing software as a service (SaaS)
  • Leasing cloud software as a service (SaaS)
  • Quantification tool
  • Technical debt
  • Tolerance value

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