Requirements Prioritization Using Logarithmic Fuzzy Trapezoidal Approach (LFTA)

Requirement prioritization (RP) is considered as an important phase of SDLC in the process of requirements engineering. Requirement prioritization techniques are very useful for making good decisions to determine the relative priority weights of the requirements as per their importance. The existing techniques are very complex and time consuming in fuzzy environment. FAHP is a very appropriate approach for RP. The FAHP has found its significant applications in today’s scenario and majority of the applications in requirement prioritization are derived by using EA and FPA and nonlinear techniques for fuzzy AHP priority derivation. However, FPA-based nonlinear approach is effective one but exhibits several issues of uncertainty and complexity. The performance of such prioritization approaches does not provide the appropriate priority as per the customer expectations, create multiple and conflict priority vectors, may result in different conclusions which are not acceptable to fuzzy pairwise comparison matrix. This research paper helps to overcome the issue of existing approach, proposes an effective and appropriate priority technique for fuzzy AHP called logarithmic fuzzy trapezoidal approach (LFTA) to conclude the priorities vector of requirements engineering. The proposed technique is used to resolve the typical gaps and meets the customer expectations of judgment making in real-life applications This technique is tested on real-life project ‘selection rank 1 of college’ based on different criteria’s.