Enhanced rule accuracy algorithm for validating software metrics

Abstract

Software metrics has significant scope in the software quality and productivity measurement. In this work the competence of Rule Accuracy Algorithm is enhanced by the Fitness Proportionate selection algorithm that has been previously applied to genetic algorithm as potential recombination of selection, which overcomes the ant colony algorithms multiple path issue. The work analyzes the adequacy of Rule Accuracy Algorithm to validate whether the ant colony algorithm or Fitness Proportionate selection algorithm provide best results. Experimental result shows interesting conclusions on the improvements of the rule accuracy algorithm in Fitness Proportionate selection algorithm. It also opens up new areas of research on the efficiency and effectiveness of software metrics validation. © 2012 Springer-Verlag.