Software reliability forecasting by support vector machines with simulated annealing algorithms

Authors:
Ping-Feng Pai;Wei-Chiang Hong
Affiliations:
Department of Information Management, National Chi Nan University, 1, University Rd. Puli, Nantou 545, Taiwan, ROC;School of Management, Da-Yeh University, 112 Shan-Jiau Road, Da-Tusen, Chang-hua 51505, Taiwan, ROC
Venue:
Journal of Systems and Software
Year:
2006

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Abstract

Support vector machines (SVMs) have been successfully employed to solve non-linear regression and time series problems. However, SVMs have rarely been applied to forecasting software reliability. This investigation elucidates the feasibility of the use of SVMs to forecast software reliability. Simulated annealing algorithms (SA) are used to select the parameters of an SVM model. Numerical examples taken from the existing literature are used to demonstrate the performance of software reliability forecasting. The experimental results reveal that the SVM model with simulated annealing algorithms (SVMSA) results in better predictions than the other methods. Hence, the proposed model is a valid and promising alternative for forecasting software reliability.