Title :
Predicting and quantifying the technical debt in cloud software engineering
Author :
Skourletopoulos, Georgios ; Bahsoon, Rami ; Mavromoustakis, Constandinos X. ; Mastorakis, George ; Pallis, Evangelos
Author_Institution :
Dept. of e-Banking Insights, Scientia Consulting S.A., Athens, Greece
Abstract :
Identifying and managing effectively the Technical Debt has become an issue of great importance over recent years. In cloud marketplaces, where the cloud services can be leased, the difficulty to promptly predict and manage the Technical Debt has a significant impact. In this paper, we examine the Technical Debt, which stems from budget constraints during the software development process as well as the capacity of a cloud service. In this context, the budget and the cloud service selection decisions may introduce Technical Debt. Towards reaching a conclusion, two approaches are taken into consideration. Initially, a cost estimation approach is researched, which is related to implementing Software as a Service (SaaS) in the cloud for three scenarios aiming to predict the incurrence of the Technical Debt in the future. The Constructive Cost Model (COCOMO) is exploited, in order to estimate the implementation cost and define a range of secureness. In addition, a Technical Debt quantification approach is adopted, which is associated with leasing a cloud Software as a Service (SaaS), towards indicating the most appropriate cloud service to be selected.
Keywords :
cloud computing; costing; software engineering; COCOMO; SaaS; cloud service selection decisions; cloud software as a service; cloud software engineering; constructive cost model; cost estimation approach; implementation cost estimation; incurrence prediction; software development process; technical debt management; technical debt prediction; technical debt quantification approach; Computer architecture; Conferences; Silver; Software as a service; Software engineering; Switches; cloud service level selection; cloud software engineering; implementing software as a service; leasing cloud software as a service; technical debt prediction; technical debt quantification;
Conference_Titel :
Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), 2014 IEEE 19th International Workshop on
Conference_Location :
Athens
DOI :
10.1109/CAMAD.2014.7033201