摘要
As the complexity of software systems is increasing;software maintenance is becoming a challenge for software practitioners.The prediction of classes that require high maintainability effort is of utmost necessity to develop cost-effective and high-quality software.In research of software engineering predictive modeling,various software maintainability prediction(SMP)models are evolved to forecast maintainability.To develop a maintainability prediction model,software practitioners may come across situations in which classes or modules requiring high maintainability effort are far less than those requiring low maintainability effort.This condition gives rise to a class imbalance problem(CIP).In this situation,the minority classes’prediction,i.e.,the classes demanding high maintainability effort,is a challenge.Therefore,in this direction,this study investigates three techniques for handling the CIP on ten open-source software to predict software maintainability.This empirical investigation supports the use of resampling with replacement technique(RR)for treating CIP and develop useful models for SMP.
