University Events

Description: Topic: Multi-phase Algorithm Design for Accurate and Efficient Model Fitting

Location: Claire T. Carney Library (LIB), Room 314

Zoom Conference Link: https://umassd.zoom.us/j/96312746810
Meeting ID: 963 1274 6810 Passcode: 161289

Abstract:
Recent research applies soft computing techniques to fit software reliability growth models. However, runtime performance and the distribution of the distance from an optimal solution over multiple runs must be explicitly considered to justify the practical utility of these approaches, promote comparison, and support reproducible research. This paper presents a meta-optimization framework to design multi-phase algorithms for this purpose. The approach combines initial parameter estimation techniques from statistical algorithms, the global search properties of soft computing, and the rapid convergence of numerical methods. Designs that exhibit the best balance between runtime performance and accuracy are identified. The approach is illustrated through nonhomogeneous Poisson process and covariate software reliability growth models, including a cross-validation step on data sets not used to identify designs. The results indicate the nonhomogeneous Poisson process model considered is too simple to benefit from soft computing because it incurs additional runtime with no increase in accuracy attained. However, a multi-phase design for the covariate software reliability growth model consisting of the bat algorithm followed by a numerical method achieves better performance and converges consistently, compared to a numerical method only. The implementation of a framework-designed algorithm into a software reliability tool is demonstrated. The proposed approach also supports higher-dimensional covariate software reliability growth model fitting suitable for implementation in further tools.

Co-Advisor(s):
Dr. Lance Fiondella, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth

Committee Members:
Dr. Hong Liu, Commonwealth Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth;
Dr. Ruolin Zhou, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth


NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.

*For further information, please contact Dr. Lance Fiondella via email at lfiondella@umassd.edu