| Resumen |
Software engineering (SE) has been defined as the application of a systematic, disciplined, quantifiable approach to the development, operation, and maintenance of software. Enhancement is a type of software maintenance. SE involves software planning (SP), and SP includes prediction. In this study, we propose the application of two types of support vector regression (SVR) termed ϵ-SVR and ν-SVR to predict the duration of the software enhancement. A SVR is a type of support vector machine, which is a machine learning technique. Two data sets of software projects were used for training and testing the ϵ-SVR and ν-SVR. The prediction accuracy of the SVRs was compared to that of a statistical regression. Based on statistical tests, results showed that a ϵ-SVR with linear kernel was statistically better than that of a statistical regression model when software projects were enhanced on Mid Range platform and coded in programming languages of third generation. © 2017 IEEE. |
