ECE Master of Science Thesis Defense By: Jacob Aubertine
When: Thursday,
April 29, 2021
11:00 AM
-
1:00 PM
Where: > See description for location
Cost: Free
Description: Topic: An Extensible Tool incorporating Covariate Software Reliability Models
Zoom Teleconference: https://umassd.zoom.us/j/98313202852
Meeting ID: 983 1320 2852
Abstract:
Covariate software reliability models characterize defect discovery as a function of test activities and related software metrics. These models also enable more detailed test activity allocation problems suitable for process improvement. However, the mathematical and algorithmic knowledge required to apply these models deters widespread adoption by software practitioners. This thesis presents the Covariate Software Failure and Reliability Assessment Tool (C-SFRAT), a free and open source application to promote the adoption of covariate software reliability models. The C-SFRAT automatically applies methods from software reliability engineering to accurately characterize the defect discovery process in terms of the test activities performed. The tool enables calculations and visualizations, including plots of the defect discovery data, covariate models fit to this data, and inferences made possible by these models as well as assessment of model goodness-of-fit. A generalized optimization procedure, referred to as the test activity allocation problem, has been implemented to guide the distribution of limited resources among specific test activities in order to maximize defect discovery for corrective action and improved reliability. The tool is extensible, allowing for the contributions of new hazard functions, goodness-of-fit measures, and optimization problems. The steps to add a new hazard function are described. Application of the C-SFRAT to two data sets from the literature indicates that, in some cases, newly incorporated hazard functions perform best. The open source nature of this tool will enable collaboration among researchers and practitioners from industry and government within a single shared platform.
NOTE: All ECE Graduate Students are ENCOURAGED to join the zoom teleconference.
All interested parties are invited to join.
Advisor: Dr. Lance Fiondella
Committee Members: Dr. Liudong Xing, Department of Electrical & Computer Engineering; Dr. Gokhan Kul, Department of Computer and Information Science, UMass Dartmouth
*For further information, please contact Dr. Lance Fiondella via email at lfiondella@umassd.edu.
Zoom Teleconference: https://umassd.zoom.us/j/98313202852
Meeting ID: 983 1320 2852
Abstract:
Covariate software reliability models characterize defect discovery as a function of test activities and related software metrics. These models also enable more detailed test activity allocation problems suitable for process improvement. However, the mathematical and algorithmic knowledge required to apply these models deters widespread adoption by software practitioners. This thesis presents the Covariate Software Failure and Reliability Assessment Tool (C-SFRAT), a free and open source application to promote the adoption of covariate software reliability models. The C-SFRAT automatically applies methods from software reliability engineering to accurately characterize the defect discovery process in terms of the test activities performed. The tool enables calculations and visualizations, including plots of the defect discovery data, covariate models fit to this data, and inferences made possible by these models as well as assessment of model goodness-of-fit. A generalized optimization procedure, referred to as the test activity allocation problem, has been implemented to guide the distribution of limited resources among specific test activities in order to maximize defect discovery for corrective action and improved reliability. The tool is extensible, allowing for the contributions of new hazard functions, goodness-of-fit measures, and optimization problems. The steps to add a new hazard function are described. Application of the C-SFRAT to two data sets from the literature indicates that, in some cases, newly incorporated hazard functions perform best. The open source nature of this tool will enable collaboration among researchers and practitioners from industry and government within a single shared platform.
NOTE: All ECE Graduate Students are ENCOURAGED to join the zoom teleconference.
All interested parties are invited to join.
Advisor: Dr. Lance Fiondella
Committee Members: Dr. Liudong Xing, Department of Electrical & Computer Engineering; Dr. Gokhan Kul, Department of Computer and Information Science, UMass Dartmouth
*For further information, please contact Dr. Lance Fiondella via email at lfiondella@umassd.edu.
Contact: > See Description for contact information
Topical Areas: General Public, University Community, College of Engineering, Electrical and Computer Engineering