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Analysis and Evaluation of Methods for Activities in the Expanded Requirements Generation Model (x-RGM)

In recent years, the requirements engineering community has proposed a number of models for the generation of a well-formulated, complete set of requirements. However, these models are often highly abstract or narrowly focused, providing only pieces of structure and parts of guidance to the requirements generation process. Furthermore, many of the models fail to identify methods that can be employed to achieve the activity objectives. As a consequence of these problems, the requirements engineer lacks the necessary guidance to effectively apply the requirements generation process, and thus, resulting in the production of an inadequate set of requirements.

To address these concerns, we propose the expanded Requirements Generation Model (x-RGM), which consists of activities at a more appropriate level of abstraction. This decomposition of the model ensures that the requirements engineer has a clear understanding of the activities involved in the requirements generation process. In addition, the objectives of all the activities defined by the x-RGM are identified and explicitly stated so that no assumptions are made about the goals of the activities involved in the generation of requirements. We also identify sets of methods that can be used during each activity to effectively achieve its objectives. The mapping of methods to activities guides the requirements engineer in selecting the appropriate techniques for a particular activity in the requirements engineering process. Furthermore, we prescribe small subsets of methods for each activity based on commonly used selection criteria such that the chosen criterion is optimized. This list of methods is created with the intention of simplifying the task of choosing methods for the activities defined by the x-RGM that best meet the selection criterion goal / Master of Science

Identiferoai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/34199
Date30 July 2004
CreatorsLobo, Lester Oscar
ContributorsComputer Science, Arthur, James D., Edwards, Stephen H., Nance, Richard E.
PublisherVirginia Tech
Source SetsVirginia Tech Theses and Dissertation
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf
RightsIn Copyright, http://rightsstatements.org/vocab/InC/1.0/
RelationLobo_Masters_Thesis_July_2004.pdf

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