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Unbounded rule-based expert system for selecting software development methodologies

MCom (Business Information Systems) / Deparment of Business Information Systems / The extent of success of a given project can be increased by using an appropriate Project Management Methodology (PMM) that takes into account the specific characteristics of the project (such as complexity, size, budget, nature of risk, etc.). PMMs have evolved over the years to become more diverse, complex, with evolving and dynamic ICT platforms. Such PMMs have traditionally been used as frameworks to guide the project management process for decision makers (such as Project Managers, Project Owners and Project Teams). The choice of selecting an appropriate project methodology is daunting; apart from other considerations related to project characteristics such as budget, scope, schedule, performance and resource constraints. One of the vital stages of a successful software development project is selecting a good software development methodology that best suits that project.
The aim of this research is to investigate the critical factors to be considered by project managers in the selection of the software development methodology for the project. These critical factors are then used as a foundation for an architecture for an “unbounded rule-based expert system. A survey was conducted amongst project managers to determine the critical factors necessary for the selection of a software development methodology. From the findings of the study, it was established the critical factors revolved around three constructs of Project Excellence Enablers, Excellent Project Management Practices, and Business Value Proposition factors. The findings from this study therefore provided a rationale and a basis for the evolution of an “Unbounded Rule-Based Expert Systems Architecture” as a basis for the selection of the right software development methodology / NRF

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:univen/oai:univendspace.univen.ac.za:11602/1305
Date16 May 2019
CreatorsMacheque, Vhutshilo
ContributorsKadyamatimba, A., Tutani, D., Ochara, N. M.
Source SetsSouth African National ETD Portal
LanguageEnglish
Detected LanguageEnglish
TypeDissertation
Format1 online resource (xii, 107 leaves: color illustrations)
RightsUniversity of Venda

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