Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1995. / Vita. Abstract. Includes bibliographical references (leaves 124-127). Also available via the Internet.

Thesis (M.A.)--University of Hong Kong, 1986. / Also available in print.

Thesis (M.A.)--University of Missouri-Columbia, 2004. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (June 30, 2006) Vita. Includes bibliographical references.

Thesis (M.S.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains iv, 116 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 66).

Compilation encompasses many steps. Parsing turns the input program into a more manageable syntax tree. Verification ensures that the program makes some semblance of sense. Finally, code generation transforms the internal abstract program representation into an executable program. Compilers strive to produce the best possible programs. Optimizations are applied at nearly every level of compilation. Instruction Scheduling is one of the last compilation tasks. It is part of code generation. Instruction Scheduling replaces the internal graph representation of the program with an instruction sequence. The scheduler should produce some sequence that the hardware can execute quickly. Considering that Instruction Scheduling is an NP-Complete optimization problem, it is interesting that schedules are usually generated by a greedy, heuristic algorithm called List Scheduling. Given search-based algorithms' successes in other NP-Complete optimization domains, we ask whether search-based algorithms can be applied to Instruction Scheduling to generate superior schedules without unacceptably increasing compilation time. To answer this question, we formulate a problem description that captures practical scheduling constraints. We show that this problem is NP-Complete given modest requirements on the actual hardware. We adapt three different search algorithms to Instruction Scheduling in order to show that search is an effective Instruction Scheduling technique. The schedules generated by our algorithms are generally shorter than those generated by List Scheduling. Search-based scheduling does take more time, but the increases are acceptable for some compilation domains.

When the message sink of a speech communication system is a human, the ultimate criterion of system performance is the subjective quality of the output speech. Unfortunately, no tractable mathematical function has been found to adequately relate speech quality to the physical system parameters. For this reason, empirical methods must be utilized to assess the interplay between the subjective quality and the objective parameters of a speech communication system. In this thesis the effects of transmission errors on the speech quality of pulse code modulation (PCM) and differential pulse code modulation (DPCM) voice communication systems are investigated. The subjective figure of merit adopted in this study is the listener's preference of the output speech with respect to a suitably chosen reference. Under some assumptions and restrictions, the system models of the two types of modulation systems of interest are formulated and simulated in an IBM System 360/Model 67 time-shared computer. With the aid of a special-purpose input/output interface, the simulated systems are used to process a recorded speech sample representative of English speech. The quality of the processed speech is then subjectively evaluated according to the isopreference method. The results of the subjective evaluation are presented in the form of isopreference contours. These contours indicate that in both PCM and DPCM systems, the speech quality is dominantly influenced by quantization error when the channel is relatively error-free; whereas if the channel is relatively noisy, finer quantization offers no improvement in quality. Furthermore, encoding the quantizer's output by either natural or folded binary coding yields virtually identical speech quality. In a comparison with contours of constant system signal-to-distortion power ratio, the isopreference contours reveal that under some conditions, the system signal-to-distortion power ratio may be a reasonably adequate measure of human preference of speech. In terms of the minimum channel capacity required to achieve a desired speech quality, DPCM is found to perform better than PCM for three important channel models: the binary symmetric channel, the additive white Gaussian channel, and the Rayleigh fading channel with additive white Gaussian noise. In the latter two cases, the performance improvement of DPCM over PCM increases with increasing desired speech quality for the range of speech quality considered in this study. Finally, the implications of the subjective tests' results in two suboptimal operations are discussed. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

Bilingualism is one of the by-products of globalization and migration. As people from different ethnicities come into contact, their languages will influence each other. People learn a second or third language in different environments leading to their linguistic proficiency levels being different. In conversations involving bilinguals, code-switching may be prevalent. This practise of alternating between two or more languages during a speech act has been of great interest to researchers with various models and hypotheses being proposed to explain it. Although code-switching has been studied extensively in literature, indigenous languages such as Shona have received less attention. This study aims to determine whether the markedness model of code-switching can be applied to Shona oral discourse (speech). An analysis is done to ascertain the nature, occurrence and characteristics of code-switching in the speech of Shona-English bilinguals. Participants who attended formal education for at least ten years were selected for the study. In order to inform on the theoretical background and on previous studies that dealt with code-switching, a literature review was conducted. The study used semi-structured interviews, a cloze test and recordings as data collection methods. Data was analysed to determine the applicability of the markedness model to the compiled corpus. Data analysis was also aided by WordSmith, (corpus analysis software). Results of the analysis seem to suggest that the markedness model can be applied to Shona-English code-switching. In addition, an analysis of the corpus using WordSmith showed frequently used English words and collocations and concordances of the code-switched words. An examination of the collocations and concordances shows the contexts in which the code-switched words appear. / Dissertation (MA) University of Pretoria, 2016. / National Research Foundation (NRF) / Afrikaans / MA / Unrestricted

No description available.

No description available.

Existing software engineering tools have proved useful in automating some aspects of the code review process, from uncovering defects to refactoring code. However, given that software teams still spend large amounts of time performing code reviews despite the use of such tools, much more research remains to be carried out in this area. This dissertation present two major contributions to this field. First, we perform a text classification experiment over thirty thousand GitHub review comments to understand what code reviewers typically discuss in reviews. Next, in an attempt to offer an innovative, data-driven approach to automating code reviews, we leverage probabilistic models of source code and graph embedding techniques to perform human-like code inspections. Our experimental results indicate that the proposed algorithm is able to emulate human-like code inspection behaviour in code reviews with a macro f1-score of 62%, representing an impressive contribution towards the relatively unexplored research domain of automated code reviewing tools. / Thesis / Master of Applied Science (MASc)