On the Efficient Design and Testing of Dependable Systems Software

Modern computing systems that enable increasingly smart and complex applications permeate our daily lives. We strive for a fully connected and automated world to simplify our lives and increase comfort by offloading tasks to smart devices and systems. We have become dependent on the complex and ever growing ecosystem of software that drives the innovations of our smart technologies. With this dependence on complex software systems arises the question whether these systems are dependable, i.e., whether we can actually trust them to perform their intended functions. As software is developed by human beings, it must be expected to contain faults, and we need strategies and techniques to minimize both their number and the severity of their impact that scale with the increase in software complexity. Common approaches to achieve dependable operation include fault acceptance and fault avoidance strategies. The former gracefully handle faults when they occur during operation, e.g., by isolating and restarting faulty components, whereas the latter try to remove faults before system deployment, e.g., by applying correctness testing and software fault injection (SFI) techniques. On this background, this thesis aims at improving the efficiency of fault isolation for operating system kernel components, which are especially critical for dependable operation, as well as at improving the efficiency of dynamic testing activities to cope with the increasing complexity of software. Using the widely used Linux kernel, we demonstrate that partial fault isolation techniques for kernel software components can be enhanced with dynamic runtime profiles to strike a balance between the expected overheads imposed by the isolation mechanism and the achieved degree of isolation according to user requirements. With the increase in software complexity, comprehensive correctness and robustness assessments using testing and SFI require a substantially increasing number of individual tests whose execution requires a considerable amount of time. We study, considering different levels of the software stack, if modern parallel hardware can be employed to mitigate this increase. In particular, we demonstrate that SFI tests can benefit from parallel execution if such tests are carefully designed and conducted. We furthermore introduce a novel SFI framework to efficiently conduct such experiments. Moreover, we investigate if existing test suites for correctness testing can already benefit from parallel execution and provide an approach that offers a migration path for test suites that have not originally been designed for parallel execution

Risk management in enterprise resource planning projects

In recent years Enterprise Resource Planning (ERP) systems have received much attention. ERP are extremely complex information systems, whose implementation is often a complex adventure for business enterprises. The organizational relevance and risk of ERP projects make it important for organizations to focus on ways to make ERP implementation successful. However, dealing with risk management in ERP project introduction is an ambitious task. Numerous risk factors have to be taken into account which include technological and managerial aspects, both psychological and sociological; moreover they can be deeply interconnected and have indirect e ects on the project. Therefore, the risk management process is highly difficult and uncertain. The general purpose of this study is to develop an innovative risk management methodology supporting the formulation of risk treatment strategies and actions during ERP introduction projects in order to nally improve the success rate. In this thesis, the research context, framework and methodology are presented; then main phases are introduced and results discussed

On the Support of Massive Machine-to-Machine Traffic in Heterogeneous Networks and Fifth-Generation Cellular Networks

The widespread availability of many emerging services enabled by the Internet of Things (IoT) paradigm passes through the capability to provide long-range connectivity to a massive number of things, overcoming the well-known issues of ad-hoc, short-range networks. This scenario entails a lot of challenges, ranging from the concerns about the radio access network efficiency to the threats about the security of IoT networks. In this thesis, we will focus on wireless communication standards for long-range IoT as well as on fundamental research outcomes about IoT networks. After investigating how Machine-Type Communication (MTC) is supported nowadays, we will provide innovative solutions that i) satisfy the requirements in terms of scalability and latency, ii) employ a combination of licensed and license-free frequency bands, and iii) assure energy-efficiency and security

Management: A continuing bibliography with indexes

This biliography lists 919 reports, articles, and other documents introduced into the NASA scientific and technical information system in 1981

Формирование профессиональных компетенций юриста

В статье рассматривается проблема формирования профессиональных компетенций юриста в рамках дисциплины «Профессиональные навыки юриста» в условиях игрового состязательного судебного процесса, различные формы организации учебной деятельности студентов, которые способствуют приобретению студентами новых знаний, закреплению коммуникативных умений и навыков публичных выступлений

Оценка точности восстановления координат при моделировании трехмерных объектов с использованием стереоизображений

Необходимость реконструкции трехмерных координат возникает в задачах распознавания, в которых требуется восстановить форму изображенного объекта. Один из способов решения задачи базируется на использовании модели системы технического зрения, описывающей формирование стереопары изображений. Параметры такой модели задаются матрицами преобразования однородных координат сцены. Для калибровки модели могут быть использованы тестовые стереоизображения, сделанные в разных ракурсах, для шести точек которых известны координаты соответствующих им точек сцены. Точность восстановления координат точек поверхности изображенного объекта (при условии удачного распознавания соответствующих им точек стереопары изображений) обуславливается, главным образом, точностью калибровки модели технического зрения. Оценка погрешностей позволяет построить тетраэдр, во внутренней области которого лежит точка поверхности трехмерного тела, соответствующая распознанной точке стереоизображения

Randomized Machine Learning: Statement, solution, applications

In this paper we propose a new machine learning concept called randomized machine learning, in which model parameters are assumed random and data are assumed to contain random errors. Distinction of this approach from “classical” machine learning is that optimal estimation deals with the probability density functions of random parameters and the “worst” probability density of random data errors. As the optimality criterion of estimation, randomized machine learning employs the generalized information entropy maximized on a set described by the system of empirical balances. We apply this approach to text classification and dynamic regression problems. The results illustrate capabilities of the approach