Evaluation of Critical Factors Affecting The Efficiency of Searching Techniques

Searching for data is one of the fundamental fields of computing. Often, the difference between a fast and slow one is the use of good algorithm for the data set. The efficiency of searching techniques used in a task will determine how fast such task can be completed. In this work, the efficiency of linear and binary searching techniques in terms of running time, memory usage and the numbers of comparison was evaluated. The search time, memory used and numbers of comparison were used as decision variables to evaluate their efficiencies. Experimental results for the decision variables were generated from a software tool written using Java programming language in which the arrays of number searched were varied for the four different searching techniques of linear and binary. The results were subjected to Factor analysis to test the level at which each factor affects the searching techniques. Eigenvalues were used to indicate how well each of the extracted factors fits the data from the experimental results. The result showed that numbers of comparison contributed; 84.459% and 72.876% for linear and binary searching techniques respectively. The time taken came second, contributing 15.538% and 27.041% while memory used was the least of all contributing 0.003% and 0 .082% for linear and binary search respectively. It can be concluded that numbers of comparison is the most critical factor affecting the searching techniques. Binary search is the most efficient of all the searching techniques considered. Keywords— Factor Analysis, Searching techniques, Decision Variables, Eigenvalue, Principal Components, Communality, Correlation