2013 4th International Workshop on Product LinE Approaches in Software Engineering (PLEASE) 2013
DOI: 10.1109/please.2013.6608660
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Knowledge-assisted product requirements configurator

Abstract: Producing timely and customer oriented products is a key determinant for the success of any product-based business. Product requirement elicitation and configuration practices therefore play a major role in taking products to market efficiently. Knowledge of the existing generic product is crucially important while creating its variants. In this paper, we discuss an ontological representation of product primitives for a knowledge-assisted requirements configurator and illustrate its use for a financial product… Show more

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Cited by 2 publications
(5 citation statements)
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References 10 publications
(16 reference statements)
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“…In section 2.3, we take two examples from a project on developing a knowledge platform for product requirement configuration [13]. We further explain how the K-RAE framework facilitated us in accommodating the ever changing customer requirements with minimal change to architectural design.…”
Section: The Knowledge-assisted Frameworkmentioning
confidence: 99%
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“…In section 2.3, we take two examples from a project on developing a knowledge platform for product requirement configuration [13]. We further explain how the K-RAE framework facilitated us in accommodating the ever changing customer requirements with minimal change to architectural design.…”
Section: The Knowledge-assisted Frameworkmentioning
confidence: 99%
“…We take two illustrative examples from the development of an ontology-based method and tool to represent product knowledge and reuse it in configuration exercises [13]. The product configurator reported in [13] is in use by a financial product team in our company.…”
Section: Examplementioning
confidence: 99%
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“…In an earlier publication, we discussed our work on a product knowledge configurator to represent product knowledge so that it can be reused in RE exercises for large projects in the same domain [7]. The approach involves knowledge-assisted product requirements evolution from a knowledge base (KB).…”
Section: Introductionmentioning
confidence: 99%