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    The identification, categorization, and evaluation of model-based behavioral decay in design patterns
    (Montana State University - Bozeman, College of Engineering, 2019) Reimanis, Derek Kristaps; Chairperson, Graduate Committee: Clemente Izurieta; Clemente Izurieta was a co-author of the article, 'Evaluations of behavioral technical debt in design patterns: a multiple longitudinal case study' submitted to the journal 'IEEE transactions on software engineering' which is contained within this thesis.
    Software quality assurance (QA) techniques seek to provide software developers and managers with the methods and tools necessary to monitor their software product to encourage fast, on-time, and bug-free releases for their clients. Ideally, QA methods and tools provide significant value and highly-specialized results to product stakeholders, while being fully incorporated into an organization's process and with actionable and easy-to-interpret outcomes. However, modern QA techniques fall short on these goals because they only feature structural analysis techniques, which do not fully illuminate all intricacies of a software product. Additionally, many modern QA methods are not capable of capturing domain-specific concerns, which suggests their results are not fulfilling their potential. To assist in the remediation of these issues, we have performed a comprehensive study to explore an unexplored phenomenon in the field of QA, namely model-based behavioral analysis. In this sense, behavioral analysis refers to the mechanisms that occur in a software product as the product is executing its code, at system run-time. We approach this problem from a model-based perspective because models are not tied to program-specific behaviors, so findings are more generalizable. Our procedure follows an intuitive process, involving first the identification of model-based behavioral issues, then the classification and categorization of these behavioral issues into a taxonomy, and finally the evaluation of them in terms of their effect on software quality. Our results include a taxonomy that captures and provides classifications for known model-based behavioral issues. We identified relationships between behavioral issues and existing structural issues to illustrate that the inclusion of behavioral analysis provides a new perspective into the inner mechanisms of software systems. We extended an existing state-of-the-art operational software quality measurement technique to incorporate these newfound behavioral issues. Finally, we used this quality extension to evaluate the effects of behavioral issues on system quality, and found that software quality has a strong inverse relationship with behavioral issues.
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    Design and implementation of a real-time system to characterize functional connectivity between cortical areas
    (Montana State University - Bozeman, College of Engineering, 2017) Parsa Gharamaleki, Mohammadbagher; Chairperson, Graduate Committee: Brendan Mumey
    Despite a thorough mapping of the anatomical connectivity between brain regions and decades of neurophysiological studies of neuronal activity within the various areas, our understanding of the nature of the neural signals sent from one area to another remains rudimentary. Orthodromic and antidromic activation of neurons via electrical stimulation ('collision testing') has been used in the peripheral nervous system and in subcortical structures to identify signals propagating along specific neural pathways. However, low yield makes this method prohibitively slow for characterizing cortico-cortical connections. We employed recent advances in electrophysiological methods to improve the efficiency of the collision technique between cortical areas. There are three key challenges: 1) maintaining neuronal isolations following stimulation, 2) increasing the number of neurons being screened, and 3) ensuring low-latency triggering of stimulation after spontaneous action potentials. We have developed a software-hardware solution for online isolations and stimulation triggering, which operates in conjunction with two hardware options, Hardware Processing Platform (HPP) or a Software Processing Platform (SPP). The HPP is a 'system on a chip' solution enabling real-time processing in a re-programmable hardware platform, whereas the SPP is a small Intel Atom processor that allows soft real-time computing on a CPU. Employing these solutions for template matching both accelerates spike sorting and provides the low-latency triggering of stimulation required to produce collision trials. Recording with a linear tetrode array electrode allows simultaneous screening of multiple neurons, while the software package coordinates efficient collision testing of multiple user-selected units across channels. This real-time connectivity screening system enables researchers working with a variety of animal models and brain regions to identify the functional properties of specific projections between cortical areas in behaving animals.
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