Thesis (M.S. in Space Systems Operations)--Naval Postgraduate School, September 2003. / Thesis advisor(s): Eric Christiansen, Rudy Panholzer, Dan Bursch. Includes bibliographical references (p. 75-76). Also available online.

Thesis (M.A.S.)--Memorial University of Newfoundland, 2002. / Bibliography: leaves 51-52.

Thesis (M.S. in Operations Research)--Naval Postgraduate School, December 2003. / Thesis advisor(s): Robert A. Koyak, Lyn R. Whitaker. Includes bibliographical references (p. 63). Also available online.

Thesis (Ph. D.)--University of Washington, 2002. / Vita. Includes bibliographical references (p. 133-141).

Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 82-91).

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references (leaves 205-231). Available also in a digital version from Dissertation Abstracts.

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: portfolio risk decomposition; principal components regression; principal components analysis; mortgage-backed securities. Includes bibliographical references (p. 88-89).

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: Fisher's exact test; cross tabulations; CMH test; regression model. Includes bibliographical references (p. 96-97).

The identification of asthma patients most at risk of experiencing an emergency department event is an important step toward lessening public health burdens in the United States. In this report, the CDC BRFSS Asthma Call Back Survey Data from 2006 to 2009 is explored for potential factors for a predictive model. A metric for classifying the control level of asthma patients is constructed and applied. The data is then used to construct a predictive model for ED events with the rpart algorithm. / text

Software testing is the most commonly used methodology for validating quality of software systems. Conceptually, testing is simple, but in practice, given the huge (practically infinite) space of inputs to test against, it requires solving a number of challenging problems, including evaluating and reusing tests efficiently and effectively as software evolves. While software testing research has seen much progress in recent years, many crucial bugs still evade state-of-the-art approaches and cause significant monetary losses and sometimes are responsible for loss of life. My thesis is that a unified, bi-dimensional, change-driven methodology can form the basis of novel techniques and tools that can make testing significantly more effective and efficient, and allow us to find more bugs at a reduced cost. We propose a novel unification of the following two dimensions of change: (1) real manual changes made by programmers, e.g., as commonly used to support more effective and efficient regression testing techniques; and (2) mechanically introduced changes to code or specifications, e.g., as originally conceived in mutation testing for evaluating quality of test suites. We believe such unification can lay the foundation of a scalable and highly effective methodology for testing and maintaining real software systems. The primary contribution of my thesis is two-fold. One, it introduces new techniques to address central problems in both regression testing (e.g., test prioritization) and mutation testing (e.g., selective mutation testing). Two, it introduces a new methodology that uses the foundations of regression testing to speed up mutation testing, and also uses the foundations of mutation testing to help with the fault localization problem raised in regression testing. The central ideas are embodied in a suite of prototype tools. Rigorous experimental evaluation is used to validate the efficacy of the proposed techniques using a variety of real-world Java programs. / text