An Empirical Evaluation of Requirements Prioritization Techniques
Abstract
In today’s time and budget intensive software development market, quick delivery is the basicmotive of teams. Software development teams strive to gain customer satisfaction by all
possible means. Requirements prioritization is the most challenging customer input dependent
task in the software development life cycle that decides the fate of a project. Selection of a
well-suited requirements prioritization technique may result in customer satisfaction and on
time delivery time. Literature reports on many requirements prioritization techniques in
practice. However, each has its own features that can outperform the rest for a certain case.
Therefore, this research is conducted to empirically evaluate the existing techniques in terms
of certain quality measures (i.e., accuracy, efficiency, and scalability). The selected techniques
are evaluated for the small, medium and large scale of requirements sets. For that, we selected
five existing techniques that are multi-criteria-decision-making techniques and have user
involvement (i.e., Analytical Hieratical Process (AHP), Analytical Network Process (ANP),
FuzzyAHP, FuzzyANP and Interactive Genetic Algorithm (IGA)). The experimental results
showed that among the five selected techniques, FuzzyAHP is the most efficient and accurate
technique for the large dataset of requirements.
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