Publication Details

Brown, R. B. K., Beydoun, G., Low, G., Tibben, W., García-Sánchez, F., Zamani, R. & Martinez-Bejar, R. (2016). Computationally efficient ontology selection in software requirement planning. Information Systems Frontiers: a journal of research and innovation, 18 (2), 349-358.


Understanding the needs of stakeholders and prioritizing requirements are the vital steps in the development of any software application. Enabling tools to support these steps have a critical role in the success of the corresponding software application. Based on such a critical role, this paper presents a computationally efficient ontology selection in software requirement planning. The key point guiding the underlying design is that, once gathered, requirements need to be processed by decomposition towards the generation of a specified systems design. A representational framework allows for the expression of high level abstract conceptions under a single schema, which may then be made explicit in terms of axiomatic relations and expressed in a suitable ontology. The initial experimental results indicate that our framework for filtered selection of a suitable ontology operates in a computationally efficient manner.



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