Finding, understanding, and fixing bugs in software systems is challenging. Dynamic binary translation (DBT) systems provide a powerful facility for building program analysis and debugging tools. However, DBT abstractions are too low-level and provide limited contextual information to instrumentation tools, making it hard to implement such tools. In this theis, we introduce behavioral watchpoints, a new software-based watchpoint framework that simplifies the implementation of DBT-based program analysis and debugging tools. Behavioral watchpoints have two key features: 1) they provide contextual information at the instruction level which are directly available with watchpoints and 2) they enable specializing instruction-level instrumentation with individual data structures. We describe three applications that were easily developed using our watchpoint framework: detecting buffer overflows, detecting read-before-write and memory freeing bugs and detecting memory leaks. We implemented behavioral watchpoints using Granary, a DBT framework for instrumenting operating system kernels. We evaluated the overheads of watchpoints for analyzing and debugging operating system kernel modules and show that these overheads are reasonable.

This thesis examines the special case in which a newly developed dynamic measurement system must be characterized when an accepted standard qualification procedure does not yet exist. In order to characterize this type of system, both physical experimentation and computational simulation methods will be used to build trust in this measurement system. This process of establishing credibility will be presented in the form of a proposed methodology. This proposed methodology will utilize verification and validation methods that apply within the simulation community as the foundation for this multi-faceted approach. The methodology will establish the relationships between four key elements: physical experimentation, conceptual modeling, computational simulations, and data processing. The combination of these activities will provide a comprehensive characterization study of the system. In order to illustrate the methodology, a case study was performed on a dynamic force measurement system owned by Sandia National Laboratories. This system was designed to measure the force required to pull a specimen to failure in tension at a user-input velocity. The results of the case study found that there was a significant measurement error occurring as the pull event involved large break loads and high velocities. 100 pull events were recorded using an experimental test assembly. The highest load conditions discovered a force measurement error of over 100%. Using computational simulations, this measurement error was reduced to less than 10%. These simulations were designed to account for the inertial effects that skew the piezoelectric load cells. This thesis displays the raw data and the corrected data for five different pull settings. The simulations designed using the methodology significantly reduced the error in all five pull settings. In addition to the force analysis, the simulations provide insight into the complete system performance. This includes the analysis of the maximum system velocity as well as the analysis of several proposed design changes. The findings suggest that the dynamic measurement system has a maximum velocity of 28 fps, and that this maximum velocity is unaffected by the track length or the mass of the moving carriage.

In recent years there has been increased interest in the development of sensorless switched reluctance machine drives. The proper operation of a switched reluctance machine (SRM) requires knowledge of the position of the rotor of the machine. The inclusion of a physical position sensor compromises the inherent robustness of this type of machine. Thus, there has been a need to develop techniques to estimate the position of the rotor in SRM drives. Switched reluctance machines are able to operate over a large range in speed. A fully loaded SRM is typically designed to saturate the ferromagnetic material that comprises the stator and rotor of the machine whereas a lightly loaded machine does not. Therefore, the model of the machine should be able to handle both a large range in frequency and input excitation levels of the magnetic material in the machine. The development of a new dynamic circuit-based ferromagnetic model is described in this thesis. The investigation of the behaviour of 24 gauge M19 silicon steel led to the conclusion that, for this material, a circuit model that has static parameters is unable to accurately reproduce the behaviour of the actual material over a large range of input frequencies and excitation levels without resorting to retuning the parameters of the model. This thesis provides two new mechanisms that dynamically adjust the resistance values of the flux tubes of the model. Comparisons using a normalized vertical least-squares metric between the newly proposed dynamic model and a model that has static resistance values clearly show the improvement that is gained by using these mechanisms. A practical implementation of the new model is also given. Timing using a general purpose CPU shows that this implementation of the model will most likely be able to be used as part of a multi-phase lumped parameter model for a SRM in realtime.

Thesis (M.S.)--Oregon State University, 1993. / Typescript (photocopy). Includes bibliographical references (leaves 48-49). Also available on the World Wide Web.

Thesis (M.S.)--University of Missouri, School of Mines and Metallurgy, 1963. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed July 1, 2008) Includes bibliographical references (p. 32).

Thesis (Ph. D.)--University of Wisconsin--Madison, 1985. / Vita. Includes bibliographical references (leaves 232-247).

Thesis (doctoral)--Vrije Universiteit te Amsterdam, 1981. / Summary in Dutch. Includes bibliographical references (p. 159-166).

Thesis (Ph. D.)--Drexel University, 2006. / Includes abstract and vita. Includes bibliographical references (leaves 92-97).

Thesis (M.S.)--Washington State University, July 2007. / Includes bibliographical references (p. 81-83).

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