2003
DOI: 10.1002/sys.10055
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Defining goals in a COTS‐aware requirements engineering approach

Abstract: The goals of developing systems better, faster, and cheaper continue to drive software engineering practitioners and researchers to investigate software engineering methodologies. In requirements engineering, the focus has traditionally been on modeling the software engineering process and products for systems that are being built from scratch. As the size and complexity of systems continues to grow the use of commercial off the shelf (COTS) components is being viewed as a solution. Effective use of COTS compo… Show more

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Cited by 19 publications
(9 citation statements)
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References 39 publications
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“…Accordingly, the solution can focus on the speed with which streamed images can be compared and be linked to behavioural data associated with matching images in the image-base. Note that this complements component-based requirements engineering (CARE) [10].…”
Section: A Requirement Engineeringmentioning
confidence: 97%
“…Accordingly, the solution can focus on the speed with which streamed images can be compared and be linked to behavioural data associated with matching images in the image-base. Note that this complements component-based requirements engineering (CARE) [10].…”
Section: A Requirement Engineeringmentioning
confidence: 97%
“…This approach is an extension of our on-going Component-Aware Technique (CAT) research, whose major emphasis lies in COTS-Aware Requirements Engineering (CARE) and COTS-Aware Software Architecting (CASA) [1][2] [3]. The CAT research maintains a knowledge-based repository for the OTS components, which are represented in terms of goal-/agent-/object-oriented models.…”
Section: Introductionmentioning
confidence: 99%
“…The metrics presented in this work are defined and gathered within the context of the requirements engineering approach called CARE (Chung et al 2004). CARE is a knowledge based, agent-oriented and goal-oriented requirements engineering approach.…”
Section: Introductionmentioning
confidence: 99%