Configuration Analysis for Large Scale Feature Models: Towards Speculative-Based Solutions

Los sistemas de alta variabilidad son sistemas de software en los que la gestión de la variabilidad es una actividad central. Algunos ejemplos actuales de sistemas de alta variabilidad son el sistema web de gesión de contenidos Drupal, el núcleo de Linux, y las distribuciones Debian de Linux. La configuración en sistemas de alta variabilidad es la selección de opciones de configuración según sus restricciones de configuración y los requerimientos de usuario. Los modelos de características son un estándar “de facto” para modelar las funcionalidades comunes y variables de sistemas de alta variabilidad. No obstante, el elevado número de componentes y configuraciones que un modelo de características puede contener hacen que el análisis manual de estos modelos sea una tarea muy costosa y propensa a errores. Así nace el análisis automatizado de modelos de características con mecanismos y herramientas asistidas por computadora para extraer información de estos modelos. Las soluciones tradicionales de análisis automatizado de modelos de características siguen un enfoque de computación secuencial para utilizar una unidad central de procesamiento y memoria. Estas soluciones son adecuadas para trabajar con sistemas de baja escala. Sin embargo, dichas soluciones demandan altos costos de computación para trabajar con sistemas de gran escala y alta variabilidad. Aunque existan recusos informáticos para mejorar el rendimiento de soluciones de computación, todas las soluciones con un enfoque de computación secuencial necesitan ser adaptadas para el uso eficiente de estos recursos y optimizar su rendimiento computacional. Ejemplos de estos recursos son la tecnología de múltiples núcleos para computación paralela y la tecnología de red para computación distribuida. Esta tesis explora la adaptación y escalabilidad de soluciones para el analisis automatizado de modelos de características de gran escala. En primer lugar, nosotros presentamos el uso de programación especulativa para la paralelización de soluciones. Además, nosotros apreciamos un problema de configuración desde otra perspectiva, para su solución mediante la adaptación y aplicación de una solución no tradicional. Más tarde, nosotros validamos la escalabilidad y mejoras de rendimiento computacional de estas soluciones para el análisis automatizado de modelos de características de gran escala. Concretamente, las principales contribuciones de esta tesis son: • Programación especulativa para la detección de un conflicto mínimo y 1 2 preferente. Los algoritmos de detección de conflictos mínimos determinan el conjunto mínimo de restricciones en conflicto que son responsables de comportamiento defectuoso en el modelo en análisis. Nosotros proponemos una solución para, mediante programación especulativa, ejecutar en paralelo y reducir el tiempo de ejecución de operaciones de alto costo computacional que determinan el flujo de acción en la detección de conflicto mínimo y preferente en modelos de características de gran escala. • Programación especulativa para un diagnóstico mínimo y preferente. Los algoritmos de diagnóstico mínimo determinan un conjunto mínimo de restricciones que, por una adecuada adaptación de su estado, permiten conseguir un modelo consistente o libre de conflictos. Este trabajo presenta una solución para el diagnóstico mínimo y preferente en modelos de características de gran escala mediante la ejecución especulativa y paralela de operaciones de alto costo computacional que determinan el flujo de acción, y entonces disminuir el tiempo de ejecución de la solución. • Completar de forma mínima y preferente una configuración de modelo por diagnóstico. Las soluciones para completar una configuración parcial determinan un conjunto no necesariamente mínimo ni preferente de opciones para obtener una completa configuración. Esta tesis soluciona el completar de forma mínima y preferente una configuración de modelo mediante técnicas previamente usadas en contexto de diagnóstico de modelos de características. Esta tesis evalua que todas nuestras soluciones preservan los valores de salida esperados, y también presentan mejoras de rendimiento en el análisis automatizado de modelos de características con modelos de gran escala en las operaciones descrita

Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments

Supporting multiple stakeholders in agile development

Agile software development practices require several stakeholders with different kinds of expertise to collaborate while specifying requirements, designing, and modelling software, and verifying whether developers have implemented requirements correctly. We studied 112 requirements engineering (RE) tools from academia and the features of 13 actively maintained behavior-driven development (BDD) tools, which support various stakeholders in specifying and verifying the application behavior. Overall, we found that there is a growing tool specialization targeted towards a specific type of stakeholders. Particularly with BDD tools, we found no adequate support for non-technical stakeholders-- they are required to use an integrated development environment (IDE)-- which is not adapted to suit their expertise. We argue that employing separate tools for requirements specification, modelling, implementation, and verification is counterproductive for agile development. Such an approach makes it difficult to manage associated artifacts and support rapid implementation and feedback loops. To avoid dispersion of requirements and other software-related artifacts among separate tools, establish traceability between requirements and the application source code, and streamline a collaborative software development workflow, we propose to adapt an IDE as an agile development platform. With our approach, we provide in-IDE graphical interfaces to support non-technical stakeholders in creating and maintaining requirements concurrently with the implementation. With such graphical interfaces, we also guide non-technical stakeholders through the object-oriented design process and support them in verifying the modelled behavior. This approach has two advantages: (i) compared with employing separate tools, creating, and maintaining requirements directly within a development platform eliminates the necessity to recover trace links, and (ii) various natively created artifacts can be composed into stakeholder-specific interactive live in-IDE documentation. These advantages have a direct impact on how various stakeholders collaborate with each other, and allow for rapid feedback, which is much desired in agile practices. We exemplify our approach using the Glamorous Toolkit IDE. Moreover, the discussed building blocks can be implemented in any IDE with a rich-enough graphical engine and reflective capabilities

Advances on Mechanics, Design Engineering and Manufacturing III

This open access book gathers contributions presented at the International Joint Conference on Mechanics, Design Engineering and Advanced Manufacturing (JCM 2020), held as a web conference on June 2–4, 2020. It reports on cutting-edge topics in product design and manufacturing, such as industrial methods for integrated product and process design; innovative design; and computer-aided design. Further topics covered include virtual simulation and reverse engineering; additive manufacturing; product manufacturing; engineering methods in medicine and education; representation techniques; and nautical, aeronautics and aerospace design and modeling. The book is organized into four main parts, reflecting the focus and primary themes of the conference. The contributions presented here not only provide researchers, engineers and experts in a range of industrial engineering subfields with extensive information to support their daily work; they are also intended to stimulate new research directions, advanced applications of the methods discussed and future interdisciplinary collaborations

NASA/ASEE Summer Faculty Fellowship Program

This document is a collection of technical reports on research conducted by the participants in the 1996 NASA/ASEE Summer Faculty Fellowship Program at the Kennedy Space Center (KSC). This was the twelfth year that a NASA/ASEE program has been conducted at KSC. The 1996 program was administered by the University of Central Florida in cooperation with KSC. The program was operated under the auspices of the American Society for Engineering Education (ASEE) with sponsorship and funding from the Office of Educational Affairs, NASA Headquarters, Washington, DC and KSC. The KSC Program was one of nine such Aeronautics and Space Research Program funded by NASA in 1996. The NASA/ASEE Program is intended to be a two-year program to allow in-depth research by the University faculty member. The editors of this document were responsible for selecting appropriately qualified faculty to address some of the many problems of current interest to NASA/KSC

Characterising mismatch negativity biomarker signatures in preclinical models relevant to schizophrenia

Mismatch negativity (MMN) has been hailed as a "break-through biomarker in predicting psychosis onset" (Naatanen 2015). This is because deficits have been found in clinical populations diagnosed with psychotic syndromes such as schizophrenia. MMN is an auditory evoked potential (AEP) difference waveform produced by subtracting standard from deviant stimuli AEPs elicited by an oddball paradigm; purportedly arising from any discriminable change in auditory stimulation.;Despite nearly four decades of basic research into MMN the underlying mechanisms are not fully understood. Although popular theories suggest that it reflects a sensory-memory trace disruption and/or differential adaptation of responses to standard and deviant/oddball stimuli, there remains considerable debate over the neural mechanism and its interpretation.;Nevertheless, associations made between N-methyl-d-aspartate (NMDA) receptors in schizophrenia and findings showing that NMDA receptor antagonists (e.g. ketamine) induce MMN deficits in healthy volunteers suggests abnormal MMNs share common traits and support its use as a biomarker from an electrophysiological perspective. However, this is still speculative and there is great impetus on developing reliable preclinical models of MMN in order to examine the underpinning neurophysiology and therefore its reliance on NMDA receptors as a test of pathology in schizophrenia.;A question this thesis aims to address is whether a mismatch response (MMR) exists in rodents which is analogous to the human MMN, and whether its modification by NMDA receptor antagonists or as a result of schizophrenia-related genetic modification sheds light on its utility as a biomarker in disease models of schizophrenia.;This thesis describes three experiments performed using mitogen activated protein kinase kinase 7 heterozygous (Map2k7+/−) mice and their wild-type littermates, incorporating NMDA receptor antagonism with ketamine (10 mg/kg i.p.). The MAP2K7 gene is associated with schizophrenia and codes for a post-synaptic intracellular signalling enzyme which is activated following glutamatergic excitation, for instance via NMDA receptors.;The MMR to stimuli duration, frequency and intensity changes in oddball paradigms are characterised in urethane-anaesthetised and conscious animals, followed by an examination of laminar auditory cortex activity in response to these physical changes. Data recorded throughout this series of experiments includes cortical electroencephalography (EEG), video footage, and intra-cortical spiking information. These data were then analysed using various time, frequency and time-frequency domain techniques; although mainly focussing on the event-related potential (ERP) approach.;Recordings demonstrated substantial differences in the AEP waveform evoked from urethane-anaesthetised and conscious animals, with the latter displaying considerably more dynamic responses, although onset and offset of auditory stimuli induced comparable waveform features in both states. Effects of varying physical properties of stimuli in oddball and control paradigms have been identified as key determinants of the AEP and correspondingly the MMR difference waveform amplitudes.;The finding that NMDA receptor disruption in conscious animals by ketamine acutely diminishes a specific AEP feature (≈20-50 ms post stimulus onset) which may impact the resulting MMR tentatively links this study in mice with findings from humans noted above. Ketamine was also found to enhance animal movement and increase EEG spectral power in the 50-70 Hz (gamma-band) frequency range, observed for approximately 10 minutes following drug administration.;Both anaesthetised and conscious cohorts of Map2k7+/− mice displayed a significantly enhanced onset response (≈0-20 ms) in the AEP. Interestingly, ketamine did not appear to have a differential effect on Map2k7+/− mice compared with the wild-type group, suggesting that NMDA receptor-mediated neurotransmission is unimpaired in this genetic model relevant to schizophrenia.;Overall, the findings suggest that the MMR in mice is fundamentally influenced by the physical properties of stimuli employed; ketamine causes an acute, specific alteration to the AEP in conscious mice in addition to other electrophysiological and behavioural changes; and Map2k7 gene disruption causes a specific and replicable change in AEP amplitude.;Overall this study indicates that mouse models are useful for exploring the effects of different pharmacological and genetic manipulations on the auditory evoked response; however, MMN data in clinical cohorts still needs to be interpreted with care. In order to address whether the rodent MMR is analogous to human MMN, it would be necessary to probe how influencing factors revealed in the rodent studies impact on the human response. Whilst the rodent MMR and human MMN show some degree of translation, their potential as schizophrenia biomarkers requires further characterisation and validation.Mismatch negativity (MMN) has been hailed as a "break-through biomarker in predicting psychosis onset" (Naatanen 2015). This is because deficits have been found in clinical populations diagnosed with psychotic syndromes such as schizophrenia. MMN is an auditory evoked potential (AEP) difference waveform produced by subtracting standard from deviant stimuli AEPs elicited by an oddball paradigm; purportedly arising from any discriminable change in auditory stimulation.;Despite nearly four decades of basic research into MMN the underlying mechanisms are not fully understood. Although popular theories suggest that it reflects a sensory-memory trace disruption and/or differential adaptation of responses to standard and deviant/oddball stimuli, there remains considerable debate over the neural mechanism and its interpretation.;Nevertheless, associations made between N-methyl-d-aspartate (NMDA) receptors in schizophrenia and findings showing that NMDA receptor antagonists (e.g. ketamine) induce MMN deficits in healthy volunteers suggests abnormal MMNs share common traits and support its use as a biomarker from an electrophysiological perspective. However, this is still speculative and there is great impetus on developing reliable preclinical models of MMN in order to examine the underpinning neurophysiology and therefore its reliance on NMDA receptors as a test of pathology in schizophrenia.;A question this thesis aims to address is whether a mismatch response (MMR) exists in rodents which is analogous to the human MMN, and whether its modification by NMDA receptor antagonists or as a result of schizophrenia-related genetic modification sheds light on its utility as a biomarker in disease models of schizophrenia.;This thesis describes three experiments performed using mitogen activated protein kinase kinase 7 heterozygous (Map2k7+/−) mice and their wild-type littermates, incorporating NMDA receptor antagonism with ketamine (10 mg/kg i.p.). The MAP2K7 gene is associated with schizophrenia and codes for a post-synaptic intracellular signalling enzyme which is activated following glutamatergic excitation, for instance via NMDA receptors.;The MMR to stimuli duration, frequency and intensity changes in oddball paradigms are characterised in urethane-anaesthetised and conscious animals, followed by an examination of laminar auditory cortex activity in response to these physical changes. Data recorded throughout this series of experiments includes cortical electroencephalography (EEG), video footage, and intra-cortical spiking information. These data were then analysed using various time, frequency and time-frequency domain techniques; although mainly focussing on the event-related potential (ERP) approach.;Recordings demonstrated substantial differences in the AEP waveform evoked from urethane-anaesthetised and conscious animals, with the latter displaying considerably more dynamic responses, although onset and offset of auditory stimuli induced comparable waveform features in both states. Effects of varying physical properties of stimuli in oddball and control paradigms have been identified as key determinants of the AEP and correspondingly the MMR difference waveform amplitudes.;The finding that NMDA receptor disruption in conscious animals by ketamine acutely diminishes a specific AEP feature (≈20-50 ms post stimulus onset) which may impact the resulting MMR tentatively links this study in mice with findings from humans noted above. Ketamine was also found to enhance animal movement and increase EEG spectral power in the 50-70 Hz (gamma-band) frequency range, observed for approximately 10 minutes following drug administration.;Both anaesthetised and conscious cohorts of Map2k7+/− mice displayed a significantly enhanced onset response (≈0-20 ms) in the AEP. Interestingly, ketamine did not appear to have a differential effect on Map2k7+/− mice compared with the wild-type group, suggesting that NMDA receptor-mediated neurotransmission is unimpaired in this genetic model relevant to schizophrenia.;Overall, the findings suggest that the MMR in mice is fundamentally influenced by the physical properties of stimuli employed; ketamine causes an acute, specific alteration to the AEP in conscious mice in addition to other electrophysiological and behavioural changes; and Map2k7 gene disruption causes a specific and replicable change in AEP amplitude.;Overall this study indicates that mouse models are useful for exploring the effects of different pharmacological and genetic manipulations on the auditory evoked response; however, MMN data in clinical cohorts still needs to be interpreted with care. In order to address whether the rodent MMR is analogous to human MMN, it would be necessary to probe how influencing factors revealed in the rodent studies impact on the human response. Whilst the rodent MMR and human MMN show some degree of translation, their potential as schizophrenia biomarkers requires further characterisation and validation