Return to search

Decision support framework for the adoption of software development methodologies.

M. Tech. (Department of Information and Communication Technology, Faculty of Applied and Computer Sciences), Vaal University of Technology. / There are many software development methodologies that are used to control the process of developing a software system. However, no exact system has been found which could help software engineers in selecting the best software development methodology (SDM). The increasing complexity of software development today has led to complex management of software systems.
This complexity increases the challenges faced by professionals in selecting the most appropriate SDM to adopt in a project. This is important because the wrong choice of methodology is costly for the organization as it may impact on deliveries, maintenance costs, budget projects and reliability.
In this study we propose a decision support framework to assist professionals in the selection of appropriate software development methodologies that would fit each organisation and project setting.
The case based reasoning (CBR) methodology was implemented in this study. This methodology focuses on problem solving that centres on the reutilization of past experiences. The CBR methodology was implemented using the SQL programming language.
We tested the precision of the decision support framework by comparing the recommended methodology to the actual software methodology that was adopted for the project. The DS framework recorded an 80% precision result. In addition, the findings contribute to reducing the software crisis faced by today’s professionals. Therefore the framework can be adopted as a reliable tool for methodology selection in software development projects.

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:vut/oai:digiresearch.vut.ac.za:10352/487
Date January 2019
CreatorsSimelane, Lynette
ContributorsZuva, Tranos, Prof., Feukeu, Etienne Alain, Dr.
PublisherVaal University of Technology
Source SetsSouth African National ETD Portal
LanguageEnglish
Detected LanguageEnglish
TypeThesis

Page generated in 0.0022 seconds