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Context-oriented programming for customizable SaaS applications

Authors: Truyen, Eddy; Cardozo, Nicolás; Walraven, Stefan; Vallejos, Jorge; Bainomugisha, Engineer; Günther, Sebastian; D’Hondt, Theo; +1 Authors

Context-oriented programming for customizable SaaS applications

Abstract

Software-as-a-Service (SaaS) applications are multi-tenant software applications that are delivered as highly configurable web services to individual customers, which are called tenants in this context. For reasons of complexity management and to lower maintenance cost, SaaS providers maintain and deploy a single version of the application code for all tenants. As a result, however, custom-made extensions for individual tenants cannot be efficiently integrated and managed. In this paper we show that by using a context-oriented programming model, cross-tier tenant-specific software variations can be easily integrated into the single-version application code base. Moreover, the selection of which variations to execute can be configured on a per tenant basis. Concretely, we provide a technical case study based on Google App Engine (GAE), a cloud platform for building multi-tenant web applications. We contribute by showing: (a) how ContextJ, a context-oriented programming (COP) language, can be used with GAE, (b) the increase in flexibility and customizability of tenant-specific software variations using ContextJ as compared to Google's dependency injection framework Guice, and (c) that the performance of using ContextJ is comparable to Guice. Based on these observations, we come to the conclusion that COP can be helpful for providing software variations in SaaS.

Keywords

Google App Engine, context-oriented programming, Multi-tenancy, Customization, Context-oriented programming,, Software-as-a-Service

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    popularity
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    Average
    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Average
Top 10%
Top 10%
Green