An Empirical Evaluation of Requirements Prioritization Techniques

In today’s time and budget intensive software development market, quick delivery is the basic motive 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.