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Semantics-Based Composition for Aspect-Oriented Requirements Engineering

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Publication date04/2007
Host publicationAOSD '07 Proceedings of the 6th international conference on Aspect-oriented software development
PublisherACM
Pages36-48
Number of pages13
<mark>Original language</mark>English
EventSixth International Conference on Aspect-Oriented Software Development (AOSD 2007) - Vancouver, British Columbia, Canada
Duration: 12/03/200716/03/2007

Conference

ConferenceSixth International Conference on Aspect-Oriented Software Development (AOSD 2007)
CityVancouver, British Columbia, Canada
Period12/03/0716/03/07

Conference

ConferenceSixth International Conference on Aspect-Oriented Software Development (AOSD 2007)
CityVancouver, British Columbia, Canada
Period12/03/0716/03/07

Abstract

In this paper, we discuss the limitations of the current syntactic composition mechanisms in aspect-oriented requirements engineering (AORE). We highlight that such composition mechanisms not only increase coupling between aspects and base concerns but are also insufficient to capture the intentionality of the aspect composition. Furthermore, they force the requirements engineer to reason about semantic influences and trade-offs among aspects from a syntactic perspective. We present a requirements description language (RDL) that enriches the existing natural language requirements specification with semantic information derived from the semantics of the natural language itself. Composition specifications are written based on these semantics rather than requirements syntax hence providing improved means for expressing the intentionality of the composition, in turn facilitating semantics-based reasoning about aspect influences and trade-offs. We also discuss the practicality of the use of this RDL by outlining the automation support for requirements annotation (realized as an extension of the Wmatrix natural language processing tool suite) to expose the semantics which are in turn utilized to facilitate composition and analysis (supported by the MRAT tool).