Data-driven extraction and analysis of repairable fault trees from time series data

Fault tree analysis is a probability-based technique for estimating the risk of an undesired top event, typically a system failure. Traditionally, building a fault tree requires involvement of knowledgeable experts from different fields, relevant for the system under study. Nowadays’ systems, however, integrate numerous Internet of Things (IoT) devices and are able to generate large amounts of data that can be utilized to extract fault trees that reflect the true fault-related behavior of the corresponding systems. This is especially relevant as systems typically change their behaviors during their lifetimes, rendering initial fault trees obsolete. For this reason, we are interested in extracting fault trees from data that is generated from systems during their lifetimes. We present DDFTAnb algorithm for learning fault trees of systems using time series data from observed faults, enhanced with Naïve Bayes classifiers for estimating the future fault-related behavior of the system for unobserved combinations of basic events, where the state of the top event is unknown. Our proposed algorithm extracts repairable fault trees from multinomial time series data, classifies the top event for the unseen combinations of basic events, and then uses proxel-based simulation to estimate the system’s reliability. We, furthermore, assess the sensitivity of our algorithm to different percentages of data availabilities. Results indicate DDFTAnb’s high performance for low levels of data availability, however, when there are sufficient or high amounts of data, there is no need for classifying the top event

Techniques for calculating software product metrics threshold values: A systematic mapping study

Several aspects of software product quality can be assessed and measured using product metrics. Without software metric threshold values, it is difficult to evaluate different aspects of quality. To this end, the interest in research studies that focus on identifying and deriving threshold values is growing, given the advantage of applying software metric threshold values to evaluate various software projects during their software development life cycle phases. The aim of this paper is to systematically investigate research on software metric threshold calculation techniques. In this study, electronic databases were systematically searched for relevant papers; 45 publications were selected based on inclusion/exclusion criteria, and research questions were answered. The results demonstrate the following important characteristics of studies: (a) both empirical and theoretical studies were conducted, a majority of which depends on empirical analysis; (b) the majority of papers apply statistical techniques to derive object-oriented metrics threshold values; (c) Chidamber and Kemerer (CK) metrics were studied in most of the papers, and are widely used to assess the quality of software systems; and (d) there is a considerable number of studies that have not validated metric threshold values in terms of quality attributes. From both the academic and practitioner points of view, the results of this review present a catalog and body of knowledge on metric threshold calculation techniques. The results set new research directions, such as conducting mixed studies on statistical and quality-related studies, studying an extensive number of metrics and studying interactions among metrics, studying more quality attributes, and considering multivariate threshold derivation. 2021 by the authors. Licensee MDPI, Basel, Switzerland.Funding: Authors thanks to the Molde University College-Specialized Univ. in Logistics, Norway for the support of Open access fund.Scopus2-s2.0-8512089773

Mathematics in Software Reliability and Quality Assurance

This monograph concerns the mathematical aspects of software reliability and quality assurance and consists of 11 technical papers in this emerging area. Included are the latest research results related to formal methods and design, automatic software testing, software verification and validation, coalgebra theory, automata theory, hybrid system and software reliability modeling and assessment

Generation of model-based safety arguments from automatically allocated safety integrity levels

To certify safety-critical systems, assurance arguments linking evidence of safety to appropriate requirements must be constructed. However, modern safety-critical systems feature increasing complexity and integration, which render manual approaches impractical to apply. This thesis addresses this problem by introducing a model-based method, with an exemplary application based on the aerospace domain.Previous work has partially addressed this problem for slightly different applications, including verification-based, COTS, product-line and process-based assurance. Each of the approaches is applicable to a specialised case and does not deliver a solution applicable to a generic system in a top-down process. This thesis argues that such a solution is feasible and can be achieved based on the automatic allocation of safety requirements onto a system’s architecture. This automatic allocation is a recent development which combines model-based safety analysis and optimisation techniques. The proposed approach emphasises the use of model-based safety analysis, such as HiP-HOPS, to maximise the benefits towards the system development lifecycle.The thesis investigates the background and earlier work regarding construction of safety arguments, safety requirements allocation and optimisation. A method for addressing the problem of optimal safety requirements allocation is first introduced, using the Tabu Search optimisation metaheuristic. The method delivers satisfactory results that are further exploited for construction of safety arguments. Using the produced requirements allocation, an instantiation algorithm is applied onto a generic safety argument pattern, which is compliant with standards, to automatically construct an argument establishing a claim that a system’s safety requirements have been met. This argument is hierarchically decomposed and shows how system and subsystem safety requirements are satisfied by architectures and analyses at low levels of decomposition. Evaluation on two abstract case studies demonstrates the feasibility and scalability of the method and indicates good performance of the algorithms proposed. Limitations and potential areas of further investigation are identified

Tехнічні засоби діагностування та контролю бортових систем інформаційного обміну на літаку

Робота публікується згідно наказу ректора від 27.05.2021 р. №311/од "Про розміщення кваліфікаційних робіт вищої освіти в репозиторії НАУ". Керівник дипломної роботи: доцент кафедри авіоніки, Слободян Олександр ПетровичТехнічний прогрес в авіаційній та будь-якій іншій галузі тісно пов'язаний з автоматизацією технологічних процесів. Сьогодні Автоматизація технологічних процесів використовується для підвищення характеристик надійності, довговічності, екологічності, ресурсозбереження і, найголовніше, економічності і простоти експлуатації. Завдяки швидкому розвитку комп'ютерних технологій і мікропроцесорів у нас є можливість використовувати більш досконалі і складні методи моніторингу та управління системами авіаційної промисловості і будь-якими іншими. Мікропроцесорні та електронні обчислювальні пристрої, з'єднані обчислювальними і керуючими мережами з використанням загальних баз даних, мають стандарти, що дозволяють модифікувати і інтегрувати нові пристрої, що, в свою чергу, дозволяє інтегрувати і вдосконалювати виробничі процеси і управляти ними. Проектування системи розподіленої інтегрованої модульної авіоніки (DIMA) з використанням розподіленої інтегрованої технології, змішаного планування критичних завдань, резервний планування в режимі реального часу і механізму зв'язку, який запускається за часом, значно підвищує надійність, безпеку і продуктивність інтегрованої електронної системи в режимі реального часу. DIMA являє собою тенденцію розвитку майбутніх систем авіоніки. У цій статті вивчаються і обговорюються архітектурні характеристики DIMA. Потім він детально вивчає та аналізує розвиток ключових технологій в системі DIMA. Нарешті, в ньому розглядається тенденція розвитку технології DIMA

Forschungsbericht Universität Mannheim 2006 / 2007

Sie erhalten darin zum einen zusammenfassende Darstellungen zu den Forschungsschwerpunkten und Forschungsprofilen der Universität und deren Entwicklung in der Forschung. Zum anderen gibt der Forschungsbericht einen Überblick über die Publikationen und Forschungsprojekte der Lehrstühle, Professuren und zentralen Forschungseinrichtungen. Diese werden ergänzt um Angaben zur Organisation von Forschungsveranstaltungen, der Mitwirkung in Forschungsausschüssen, einer Übersicht zu den für Forschungszwecke eingeworbenen Drittmitteln, zu den Promotionen und Habilitationen, zu Preisen und Ehrungen und zu Förderern der Universität Mannheim. Darin zeigt sich die Bandbreite und Vielseitigkeit der Forschungsaktivitäten und deren Erfolg auf nationaler und internationaler Ebene

Quantitative Modeling and Verification of Evolving Software

Mit der steigenden Nachfrage nach Innovationen spielt Software in verschiedenenWirtschaftsbereichen eine wichtige Rolle, wie z.B. in der Automobilindustrie, bei intelligenten Systemen als auch bei Kommunikationssystemen. Daher ist die Qualität für die Softwareentwicklung von großer Bedeutung. Allerdings ändern sich die probabilistische Modelle (die Qualitätsbewertungsmodelle) angesichts der dynamischen Natur moderner Softwaresysteme. Dies führt dazu, dass ihre Übergangswahrscheinlichkeiten im Laufe der Zeit schwanken, welches zu erheblichen Problemen führt. Dahingehend werden probabilistische Modelle im Hinblick auf ihre Laufzeit kontinuierlich aktualisiert. Eine fortdauernde Neubewertung komplexer Wahrscheinlichkeitsmodelle ist jedoch teuer. In letzter Zeit haben sich inkrementelle Ansätze als vielversprechend für die Verifikation von adaptiven Systemen erwiesen. Trotzdem wurden bei der Bewertung struktureller Änderungen im Modell noch keine wesentlichen Verbesserungen erzielt. Wahrscheinlichkeitssysteme werden als Automaten modelliert, wie bei Markov-Modellen. Solche Modelle können in Matrixform dargestellt werden, um die Gleichungen basierend auf Zuständen und Übergangswahrscheinlichkeiten zu lösen. Laufzeitmodelle wie Matrizen sind nicht signifikant, um die Auswirkungen von Modellveränderungen erkennen zu können. In dieser Arbeit wird ein Framework unter Verwendung stochastischer Bäume mit regulären Ausdrücken entwickelt, welches modular aufgebaut ist und eine aktionshaltige sowie probabilistische Logik im Kontext der Modellprüfung aufweist. Ein solches modulares Framework ermöglicht dem Menschen die Entwicklung der Änderungsoperationen für die inkrementelle Berechnung lokaler Änderungen, die im Modell auftreten können. Darüber hinaus werden probabilistische Änderungsmuster beschrieben, um eine effiziente inkrementelle Verifizierung, unter Verwendung von Bäumen mit regulären Ausdrücken, anwenden zu können. Durch die Bewertung der Ergebnisse wird der Vorgang abgeschlossen.Software plays an innovative role in many different domains, such as car industry, autonomous and smart systems, and communication. Hence, the quality of the software is of utmost importance and needs to be properly addressed during software evolution. Several approaches have been developed to evaluate systems’ quality attributes, such as reliability, safety, and performance of software. Due to the dynamic nature of modern software systems, probabilistic models representing the quality of the software and their transition probabilities change over time and fluctuate, leading to a significant problem that needs to be solved to obtain correct evaluation results of quantitative properties. Probabilistic models need to be continually updated at run-time to solve this issue. However, continuous re-evaluation of complex probabilistic models is expensive. Recently, incremental approaches have been found to be promising for the verification of evolving and self-adaptive systems. Nevertheless, substantial improvements have not yet been achieved for evaluating structural changes in the model. Probabilistic systems are usually represented in a matrix form to solve the equations based on states and transition probabilities. On the other side, evolutionary changes can create various effects on theese models and force them to re-verify the whole system. Run-time models, such as matrices or graph representations, lack the expressiveness to identify the change effect on the model. In this thesis, we develop a framework using stochastic regular expression trees, which are modular, with action-based probabilistic logic in the model checking context. Such a modular framework enables us to develop change operations for the incremental computation of local changes that can occur in the model. Furthermore, we describe probabilistic change patterns to apply efficient incremental quantitative verification using stochastic regular expression trees and evaluate our results