Application of Gene Expression Programming in Software Reliability Modeling
Baiqiao Huang · Jisuanji kexue yu tansuo · 2011
Gene expression programming (GEP),which is a new evolutionary algorithm based on genetic algorithm and genetic programming,has been acknowledged as a powerful machine learning technique and widely used in the field of data mining.Thus,this paper applies GEP into the non-parametric software reliability modeling due to its unique and pretty characters.This new GEP-based modeling approach considers some important characters of reli-ability modeling in several main components of GEP,i.e.function set,terminal criteria,fitness function,and then obtains the final model (named GEP-NPSRM) by training on the failure data.Finally,for several real failure data-sets,four case studies are proposed by respectively comparing GEP-NPSRM with several representative existing software reliability models in term of the fitting and prediction powers.The results show that the GEP-NPSRM pro-vides better fitting and prediction performances.