预测和量化云软件工程中的技术债务

Georgios Skourletopoulos, C. Mavromoustakis, R. Bahsoon, G. Mastorakis, E. Pallis
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引用次数: 33

摘要

近年来,有效地识别和管理技术债务已经成为一个非常重要的问题。在云市场中,云服务可以被租用,因此难以及时预测和管理技术债务会产生重大影响。在本文中,我们研究了技术债务,它源于软件开发过程中的预算限制以及云服务的容量。在这种情况下,预算和云服务选择决策可能会引入技术债务。为了得出结论,考虑了两种方法。首先,研究了一种成本估算方法,该方法与在云中实现软件即服务(SaaS)有关,针对三种场景,旨在预测未来技术债务的发生。利用构建成本模型(COCOMO)来估算实施成本和定义安全范围。此外,采用了技术债务量化方法,该方法与租用云软件即服务(SaaS)相关联,以指示要选择的最合适的云服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting and quantifying the technical debt in cloud software engineering
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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