Predicting and quantifying the technical debt in cloud software engineering

Georgios Skourletopoulos; Constandinos X. Mavromoustakis; Rami Bahsoon; George Mastorakis; Evangelos Pallis

doi:10.1109/CAMAD.2014.7033201

Predicting and quantifying the technical debt in cloud software engineering

Georgios Skourletopoulos, Constandinos X. Mavromoustakis, Rami Bahsoon, George Mastorakis, Evangelos Pallis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

23 Citations (Scopus)

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.

Original language	English
Title of host publication	2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2014
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	36-40
Number of pages	5
ISBN (Print)	9781479957255
DOIs	https://doi.org/10.1109/CAMAD.2014.7033201
Publication status	Published - 5 Feb 2015
Event	2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2014 - Athens, Greece Duration: 1 Dec 2014 → 3 Dec 2014

Conference

Conference	2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2014
Country/Territory	Greece
City	Athens
Period	1/12/14 → 3/12/14

Keywords

cloud service level selection
cloud software engineering
implementing software as a service
leasing cloud software as a service
technical debt prediction
technical debt quantification

ASJC Scopus subject areas

Computer Networks and Communications
Computer Graphics and Computer-Aided Design

Access to Document

10.1109/CAMAD.2014.7033201

Cite this

Skourletopoulos, G., Mavromoustakis, C. X., Bahsoon, R., Mastorakis, G., & Pallis, E. (2015). Predicting and quantifying the technical debt in cloud software engineering. In 2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2014 (pp. 36-40). Article 7033201 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/CAMAD.2014.7033201

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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.",

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Skourletopoulos, G, Mavromoustakis, CX, Bahsoon, R, Mastorakis, G & Pallis, E 2015, Predicting and quantifying the technical debt in cloud software engineering. in 2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2014., 7033201, Institute of Electrical and Electronics Engineers (IEEE), pp. 36-40, 2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2014, Athens, Greece, 1/12/14. https://doi.org/10.1109/CAMAD.2014.7033201

Predicting and quantifying the technical debt in cloud software engineering. / Skourletopoulos, Georgios; Mavromoustakis, Constandinos X.; Bahsoon, Rami et al.
2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2014. Institute of Electrical and Electronics Engineers (IEEE), 2015. p. 36-40 7033201.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Skourletopoulos G, Mavromoustakis CX, Bahsoon R, Mastorakis G, Pallis E. Predicting and quantifying the technical debt in cloud software engineering. In 2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2014. Institute of Electrical and Electronics Engineers (IEEE). 2015. p. 36-40. 7033201 doi: 10.1109/CAMAD.2014.7033201

Predicting and quantifying the technical debt in cloud software engineering

Abstract

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Keywords

ASJC Scopus subject areas

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