Design of Minimal Spanning Tree and Analytic Hierarchical Process (SAHP) Based Hybrid Technique for Software Requirements Prioritization

Prioritizing software requirements in a sustainable manner can significantly contribute to the success of a software project, adding substantial value throughout its development lifecycle. Analytic hierarchical process (AHP) is considered to yield more accurate prioritized results, but due to high pairwise comparisons, it is not considered to be scalable for prioritization of high number of requirements. To address scalability issue, a hybrid approach of minimal spanning trees (MSTs) and AHP, called as spanning tree and AHP (SAHP), is designed for prioritizing large set of functional requirements (FRs) with fewer comparisons, and thus scalability issue is solved. In this research, on-demand open object (ODOO) enterprise resource planning (ERP) system FRs are prioritized, and the results are compared with AHP. The results of the case study proved that SAHP is more scalable that can prioritize any type of requirement with only n–1 pairs of requirements. Total FRs considered for case from ODOO were 100, where 18 spanning trees were constructed from it. With only 90 pairwise comparisons, these FRs were prioritized with more consistency compared to AHP. Total pairwise comparisons with AHP reach 4950, which is 55 times more compared with SAHP. Consistency of results is measured from average consistency index (CI) value, which was below 0.1. The consistency ratio (CR) value below 0.1 shows results are consistent and acceptable.