Despite extensive work in the field of Requirements Engineering, ineffective require- ments remains a major antecedent to the failure of projects. Requirements Engineering (RE) refers to the body of methods associated with elucidating the needs of a client, when considering the development of a new system or product. In the literature, challenges in RE have been mainly attributed to insufficient client input, incomplete requirements, evolving requirements and lack of understanding of the domain. Accordingly, this has raised the need for methods of effectively eliciting, analysing and recording requirements. In the literature, promising methods have been proposed for using ethnography to improve methods for elicitation because of its strong qualitative and quantitative qualities in understanding human activities. There has also been success with the use of Model Driven Engineering techniques for analysing, recording and communicating requirements through the use of Conceptual Data Models (CDM), to provide a shared understanding of the domain of a system. However, there has been little work that has attempted to integrate these two areas either from an empirical or theoretical perspective. In this thesis, we investigate how ethnographic research methods contribute to a method for data analysis in RE. Specifically, we consider the proposition that a CDM based on explicit and implicit information derived from ethnographic elicitation, will lead to design solutions that more closely match the expectations of clients. As a result of our investigation, this thesis presents the following key contributions: (i) the introduction of an ethnographic approach to RE for elicitation and verification (ii) a rich CDM metamodel and modeling language necessary for defining and recording ethnographic analyses based on implicit and explicit information (iii) a method for mapping CDM’s to high level architectural abstractions called ecologies. To compliment this work, an evaluation case study is provided that demonstrates a real world application of this work.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:634170 |
| Date | January 2013 |
| Creators | Williams, Gbolahan |
| Publisher | King's College London (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://kclpure.kcl.ac.uk/portal/en/theses/architecting-tacit-information-in-conceptual-data-models-for-requirements-process-improvement(2d3369c6-4387-4b69-b625-c9d36705bfac).html |
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