京都大学 / 新制・課程博士 / 博士(情報学) / 甲第24028号 / 情博第784号 / 新制||情||133(附属図書館) / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 鹿島 久嗣, 教授 山本 章博, 教授 吉川 正俊 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Indiana University-Purdue University Indianapolis (IUPUI) / The counting process is the fundamental of many real-world problems with event data. Poisson process, used as the background intensity of Hawkes process, is the most commonly used point process. The Hawkes process, a self-exciting point process fits to temporal event data, spatial-temporal event data, and event data with covariates. We study the Hawkes process that fits to heterogeneous drug overdose data via a novel semi-parametric approach. The counting process is also related to survival data based on the fact that they both study the occurrences of events over time. We fit a Cox model to temporal event data with a large corpus that is processed into high dimensional covariates. We study the significant features that influence the intensity of events.

Cloud computing is one important direction of current advanced technology trends, which is dominating the industry in many aspects. These days Cloud computing has become an intense battlefield of many big technology companies, whoever can win this war can have a very high potential to rule the next generation of technologies. From a technical point of view, Cloud computing is classified into three different categories, each can provide different crucial services to users: Infrastructure (Hardware) as a Service (IaaS), Software as a Service (SaaS), and Platform as a Service (PaaS). Normally, the standard measurements for cloud computing reliability level is based on two approaches: Service Level Agreements (SLAs) and Quality of Service (QoS). This thesis will focus on IaaS cloud systems’ Error Event Logs as an aspect of QoS in IaaS cloud reliability. To have a better view, basically, IaaS is a derivation of the traditional virtualization system where multiple virtual machines (VMs) with different Operating System (OS) platforms, are run solely on one physical machine (PM) that has enough computational power. The PM will play the role of the host machine in cloud computing, and the VMs will play the role as the guest machines in cloud computing. Due to the lack of fully access to the complete real cloud system, this thesis will investigate the technical reliability level of IaaS cloud through simulated virtualization system. By collecting and analyzing the event logs generated from the virtualization system, we can have a general overview of the system’s technical reliability level based on number of error events occur in the system. Then, these events will be used on neural network time series model to detect the system failure events’ pattern, as well as predict the next error event that is going to occur in the virtualization system.

SERVICE oriented architecture (SOA) is an architectural style to structure software systems, fostering loose coupling and dynamic integration among the applications. The use of SOA and Web services to develop complex and large business processes demands more formal and systematic testing. In addition, characteristics of this type of software limit the straightforward application of traditional testing techniques. Model-based testing (MBT) is a promising approach to deal with these problems. This dissertation investigates how two modeling techniques, namely Finite State Machine (FSM) and Event Sequence Graph (ESG), can be used to support MBT of service-oriented applications. Both techniques model different aspects and can be applied in a complementary way. Initially, we define an MBT process for service-oriented applications that employs FSMs. Based on previous experience, we propose a model-based approach to test composite services using ESGs. This approach is holistic, once test suites are generated to cover both desired situations (positive testing) and unexpected behaviors (negative testing). Three experimental studies evaluate the proposed approach: (i) a case study, (ii) a cost analysis, and (iii) a study in industry. Testing tools are also presented to support its practical use / A Arquitetura orientada a serviço (SOA) é um estilo arquitetural para estruturar sistemas de software de modo que exista um baixo grau de acoplamento entre as aplicações e essas possam ser facilmente integradas de forma dinâmica. A incorporação de SOA e serviços Web em sistemas que modelam processos de negócios grandes e complexos contribui para a necessidade de testes mais formais e sistemáticos. Além disso, características próprias dessa nova classe de software fazem com que técnicas de teste tradicionais não possam ser diretamente aplicadas. O teste baseado em modelo (TBM) apresenta-se como uma abordagem promissora que busca a resolução desses problemas. Esta tese investiga como duas técnicas de modelagem, Máquina de Estados Finitos (MEF) e Grafo de Sequência de Eventos (GSE), podem ser utilizadas para apoiar o TBM de aplicações orientadas a serviço. Essas técnicas modelam diferentes aspectos e podem ser aplicadas de forma complementar. Inicialmente, é definido um processo de TBM para aplicações orientadas a serviço que emprega MEFs. Com base na experiência adquirida, é proposta uma abordagem baseada em modelo para o teste de serviços compostos usando GSEs. Essa abordagem é holística uma vez que conjuntos de teste são gerados para cobrir tanto situações desejadas (teste positivo) quanto comportamentos inesperados (teste negativo). Três estudos experimentais avaliam a abordagem proposta: (i) um estudo de caso, (ii) uma análise de custo e (ii) um estudo na indústria. Ferramentas de teste também são apresentadas para apoiar o uso prático da abordagem proposta

SERVICE oriented architecture (SOA) is an architectural style to structure software systems, fostering loose coupling and dynamic integration among the applications. The use of SOA and Web services to develop complex and large business processes demands more formal and systematic testing. In addition, characteristics of this type of software limit the straightforward application of traditional testing techniques. Model-based testing (MBT) is a promising approach to deal with these problems. This dissertation investigates how two modeling techniques, namely Finite State Machine (FSM) and Event Sequence Graph (ESG), can be used to support MBT of service-oriented applications. Both techniques model different aspects and can be applied in a complementary way. Initially, we define an MBT process for service-oriented applications that employs FSMs. Based on previous experience, we propose a model-based approach to test composite services using ESGs. This approach is holistic, once test suites are generated to cover both desired situations (positive testing) and unexpected behaviors (negative testing). Three experimental studies evaluate the proposed approach: (i) a case study, (ii) a cost analysis, and (iii) a study in industry. Testing tools are also presented to support its practical use / A Arquitetura orientada a serviço (SOA) é um estilo arquitetural para estruturar sistemas de software de modo que exista um baixo grau de acoplamento entre as aplicações e essas possam ser facilmente integradas de forma dinâmica. A incorporação de SOA e serviços Web em sistemas que modelam processos de negócios grandes e complexos contribui para a necessidade de testes mais formais e sistemáticos. Além disso, características próprias dessa nova classe de software fazem com que técnicas de teste tradicionais não possam ser diretamente aplicadas. O teste baseado em modelo (TBM) apresenta-se como uma abordagem promissora que busca a resolução desses problemas. Esta tese investiga como duas técnicas de modelagem, Máquina de Estados Finitos (MEF) e Grafo de Sequência de Eventos (GSE), podem ser utilizadas para apoiar o TBM de aplicações orientadas a serviço. Essas técnicas modelam diferentes aspectos e podem ser aplicadas de forma complementar. Inicialmente, é definido um processo de TBM para aplicações orientadas a serviço que emprega MEFs. Com base na experiência adquirida, é proposta uma abordagem baseada em modelo para o teste de serviços compostos usando GSEs. Essa abordagem é holística uma vez que conjuntos de teste são gerados para cobrir tanto situações desejadas (teste positivo) quanto comportamentos inesperados (teste negativo). Três estudos experimentais avaliam a abordagem proposta: (i) um estudo de caso, (ii) uma análise de custo e (ii) um estudo na indústria. Ferramentas de teste também são apresentadas para apoiar o uso prático da abordagem proposta

<p>    </p> <p>The counting process is the fundamental of many real-world problems with event data. Poisson process, used as the background intensity of Hawkes process, is the most commonly used point process. The Hawkes process, a self-exciting point process fits to temporal event data, spatial-temporal event data, and event data with covariates. We study the Hawkes process that fits to heterogeneous drug overdose data via a novel semi-parametric approach. The counting process is also related to survival data based on the fact that they both study the occurrences of events over time. We fit a Cox model to temporal event data with a large corpus that is processed into high dimensional covariates. We study the significant features that influence the intensity of events. </p>