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Publication Type: search.filters.UBSTyp.PreprintStart date: 2010

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Now showing 1 - 10 of 26
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    ERA - Energy-based reliability analysis - Energiebasierte Zuverlässigkeitsanalyse
    (2014) Kemmler, Stefan; Koller, Oliver; Bertsche, Bernd
    Da die Wechselwirkungen zwischen mechatronischen Komponenten in Systemen eine entscheidende Rolle auf ihre Belastung einnehmen, ist die Betrachtung dieser Wechselwirkungen un- verzichtbar. Zur Identifikation solcher Wechselwirkungen ist eine ergänzende Methode zur den bisher klassischen Systemanalysen von Nöten. Dies wird bei der vorgestellten energiebasierten Zuverlässigkeitsanalyse (engl. Energy-based Reliability Analysis - ERA) berücksichtigt, indem die stationären Energie- beziehungsweise die dynamischen Leistungsflüsse mechatronischer Systemen in Form von Energieflussdiagrammen dargestellt werden. Mit der Modellierung des Energieflusses und damit das Ansetzen des ERA-Verfahrens kann der Nutzer Wirkzusammenhänge und Schwachstellen erkennen, eine exaktere Bestimmung der Zuverlässigkeit durch Berechnung der Belastung erreichen und folglich Komponenten zuverlässigkeitsbasiert auslegen.
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    Distributed cooperative deep transfer learning for industrial image recognition
    (2020) Maschler, Benjamin; Kamm, Simon; Nasser, Jazdi; Weyrich, Michael
    In this paper, a novel light-weight incremental class learning algorithm for live image recognition is presented. It features a dual memory architecture and is capable of learning formerly unknown classes as well as conducting its learning across multiple instances at multiple locations without storing any images. In addition to tests on the ImageNet dataset, a prototype based upon a Raspberry Pi and a webcam is used for further evaluation: The proposed algorithm successfully allows for the performant execution of image classification tasks while learning new classes at several sites simultaneously, thereby enabling its application to various industry use cases, e.g. predictive maintenance or self-optimization.
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    An industrial case study on the evaluation of a safety engineering approach for software-intensive systems in the automotive domain
    (2016) Abdulkhaleq, Asim; Vöst, Sebastian; Wagner, Stefan; Thomas, John
    Safety remains one of the essential and vital aspects in today's automotive systems. These systems, however, become ever more complex and dependent on software which is responsible for most of their critical functions. Therefore, the software components need to be analysed and verified appropriately in the context of software safety. The complexity of software systems makes defining software safety requirements with traditional safety analysis techniques difficult. A new technique called STPA (Systems-Theoretic Process Analysis) based on system and control theory has been developed by Leveson to cope with complex systems. Based on STPA, we have developed a comprehensive software safety engineering approach in which the software and safety engineers integrate the analysis of software risks with their verification to recognize the software-related hazards and reduce the risks to a low level. In this paper, we explore and evaluate the application of our approach to a real industrial system in the automotive domain. The case study was conducted analysing the software controller of the Active Cruise Control System (ACC) of the BMW Group.
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    A non-intrusive nonlinear model reduction method for structural dynamical problems based on machine learning
    (2020) Kneifl, Jonas; Grunert, Dennis; Fehr, Jörg
    The paper uses a nonlinear non-intrusive model reduction approach, to derive efficient and accurate surrogate models for structural dynamical problems. Therefore, a combination of proper orthogonal decomposition along with regression algorithms from the field of machine learning is utilized to capture the dynamics in a reduced representation. This allows highly performant approximations of the original system. In this context, we provide a comparison of several regression algorithms based on crash simulations of a structural dynamic frame.
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    Possibilistic calculus as a conservative counterpart to probabilistic calculus
    (2019) Hose, Dominik; Hanss, Michael
    In this contribution, we revisit Zadeh's Extension Principle in the context of imprecise probabilities and present two simple modifications to obtain meaningful results when using possibilistic calculus to propagate credal sets of probability distributions through models. It is demonstrated how these results facilitate the possibilistic solution of two benchmark problems in uncertainty quantification.
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    A microstructurally-based, multi-scale, continuum-mechanical model of skeletal muscle tissue
    (2019) Bleiler, Christian; Ponte Castañeda, Pedro; Röhrle, Oliver
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    An automatic safety-based test case generation approach based on systems-theoretic process analysis
    (2016) Abdulkhaleq, Asim; Wagner, Stefan
    Software safety remains one of the essential and vital aspects in today’s systems. Software is becoming responsible for most of the critical functions of systems. Therefore, the software components in the systems need to be tested extensively against their safety requirements to ensure a high level of system safety. However, performing testing exhaustively to test all software behaviours is impossible. Numerous testing approaches exist. However, they do not directly concern the information derived during the safety analysis. STPA (Systems-Theoretic Process Analysis) is a unique safety analysis approach based on system and control theory, and was developed to identify unsafe scenarios of a complex system including software. In this paper, we present a testing approach based on STPA to automatically generate test cases from the STPA safety analysis results to help software and safety engineers to recognize and reduce the associated software risks. We also provide an open-source safety-based testing tool called STPA TCGenerator to support the proposed approach. We illustrate the proposed approach with a prototype of a software of the Adaptive Cruise Control System (ACC) with a stop-and-go function with a Lego-Mindstorms EV3 robot.
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    Naming the pain in requirements engineering: a design for a global family of surveys and first results from Germany
    (2015) Méndez Fernández, Daniel; Wagner, Stefan
    Context: For many years, we have observed industry struggling in defining a high quality requirements engineering (RE) and researchers trying to understand industrial expectations and problems. Although we are investigating the discipline with a plethora of empirical studies, they still do not allow for empirical generalisations. Objective: To lay an empirical and externally valid foundation about the state of the practice in RE, we aim at a series of open and reproducible surveys that allow us to steer future research in a problem-driven manner. Method: We designed a globally distributed family of surveys in joint collaborations with different researchers and completed the first run in Germany. The instrument is based on a theory in the form of a set of hypotheses inferred from our experiences and available studies. We test each hypothesis in our theory and identify further candidates to extend the theory by correlation and Grounded Theory analysis. Results: In this article, we report on the design of the family of surveys, its underlying theory, and the full results obtained from Germany with participants from 58 companies. The results reveal, for example, a tendency to improve RE via internally defined qualitative methods rather than relying on normative approaches like CMMI. We also discovered various RE problems that are statistically significant in practice. For instance, we could corroborate communication flaws or moving targets as problems in practice. Our results are not yet fully representative but already give first insights into current practices and problems in RE, and they allow us to draw lessons learnt for future replications. Conclusion: Our results obtained from this first run in Germany make us confident that the survey design and instrument are well-suited to be replicated and, thereby, to create a generalisable empirical basis of RE in practice.
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    On data-based estimation of possibility distributions
    (2019) Hose, Dominik; Hanss, Michael
    In this paper, we show how a possibilistic description of uncertainty arises very naturally in statistical data analysis. In combination with recent results in inverse uncertainty propagation and the consistent aggregation of marginal possibility distributions, this estimation procedure enables a very general approach to possibilistic identification problems in the framework of imprecise probabilities, i.e. the non-parametric estimation of possibility distributions of uncertain variables from data with a clear interpretation.
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    Introduction of static quality analysis in small- and medium-sized software enterprises: experiences from technology transfer
    (2014) Gleirscher, Mario; Golubitskiy, Dmitriy; Irlbeck, Maximilian; Wagner, Stefan
    Today, small- and medium-sized enterprises (SMEs) in the software industry face major challenges. Their resource constraints require high efficiency in development. Furthermore, quality assurance (QA) measures need to be taken to mitigate the risk of additional, expensive effort for bug fixes or compensations. Automated static analysis (ASA) can reduce this risk because it promises low application effort. SMEs seem to take little advantage of this opportunity. Instead, they still mainly rely on the dynamic analysis approach of software testing. In this article, we report on our experiences from a technology transfer project. Our aim was to evaluate the results static analysis can provide for SMEs as well as the problems that occur when introducing and using static analysis in SMEs. We analysed five software projects from five collaborating SMEs using three different ASA techniques: code clone detection, bug pattern detection and architecture conformance analysis. Following the analysis, we applied a quality model to aggregate and evaluate the results. Our study shows that the effort required to introduce ASA techniques in SMEs is small (mostly below one person-hour each). Furthermore, we encountered only few technical problems. By means of the analyses, we could detect multiple defects in production code. The participating companies perceived the analysis results to be a helpful addition to their current QA and will include the analyses in their QA process. With the help of the Quamoco quality model, we could efficiently aggregate and rate static analysis results. However, we also encountered a partial mismatch with the opinions of the SMEs. We conclude that ASA and quality models can be a valuable and affordable addition to the QA process of SMEs.