Prof. Dr.-Ing. habil.

Trapp, Mario

Filters

5
4 1
Reset filters

Settings
Now showing 1 - 5 of 5
  • Publication
    Probabilistic analysis of safety-critical adaptive systems with temporal dependences
    ( 2008)
    Adler, Rasmus
    ;
    Domis, Dominik J.
    ;
    Förster, Marc
    ;
    Trapp, Mario
    Dynamic adaptation means that components are reconfigured at run time. Consequently, the degree to which a system fulfils its functional and safety requirements depends on the current system configuration at run time. The probability of a violation of functional requirements in combination with an importance factor for each requirement gives us a measure for reliability. In the same way, the degree of violation of safety requirements can be a measure for safety. These measures can easily be derived based on the probabilities of possible system configurations. For this purpose, we are introducing a new probabilistic analysis technique that determines configuration probabilities based on Fault trees, Binary Decision Diagrams (BDDs) and Markov chains. Through our recent work we have been able to determine configuration probabilities of systems but we neglected timing aspects [1]. Timing delays have impact on the adaptation behavior and are necessary to handle cyclic dependences. The contribution of the present article is to extend analysis towards models with timing delays. This technique builds upon the Methodologies and Architectures for Runtime Adaptive Systems (MARS) [2], a modeling concept we use for specifying the adaptation behavior of a system at design time. The results of this paper determine configuration probabilities, that are necessary to quantify the fulfillment of functional and safety requirements by adaptive systems.
  • Publication
    Development of safe and reliable embedded systems using dynamic adaptation
    ( 2007)
    Adler, Rasmus
    ;
    Schneider, Daniel
    ;
    Trapp, Mario
    A major application of dynamic adaptation is the development of safe and reliable embedded systems. In contrast to classical redundancy approaches dynamic adaptation can react much more flexible to different kinds of errors including changes in the environment. Moreover dynamic adaptation can usually be realized much more cost-efficient than classical redundancy or faulttolerance mechanisms. Using dynamic adaptation for developing dependable systems requires means to explicitly specify the adaptation behavior and to analyze the effects of dynamic adaptation on system reliability and particularly safety. However, these activities are very complex and error prone and hence pose the need for a sound and seamless engineering support. For this reason, this position paper points out some of the lessons we have learned over the last years of applying and advancing dynamic adaptation for the development of safe and reliable adaptive systems. We furthermore discuss and classify current achievements in research and practice and derive corresponding future research challenges.
  • Publication
    Determining configuration probabilities of safety-critical adaptive systems
    ( 2007)
    Adler, Rasmus
    ;
    Förster, Marc
    ;
    Trapp, Mario
    This article presents a novel technique to calculate the probability that an adaptive system assumes a configuration. An important application area of dynamic adaptation is the cost-efficient development of dependable embedded systems. Dynamic adaptation exploits implicitly available redundancy, reducing the need for hardware redundancy, to make systems more available, reliable, survivable and, ultimately, more safe. Knowledge of configuration probabilities of a system is an essential requirement for the optimization of safety efforts in development. In perspective, it is also a prerequisite for dependability assessment. Our approach is based on a modeling language for complex reconfiguration behavior. We transform the adaptation model into a probabilistic target model that combines a compositional fault tree with Markov chains. This hybrid model can be evaluated efficiently using a modified BDD-based algorithm. The approach is currently being implemented in an existing reliability modeling tool.
  • Publication
    Runtime adaptation in safety-critical automotive systems
    ( 2007)
    Trapp, Mario
    ;
    Adler, Rasmus
    ;
    Förster, Marc
    ;
    Junger, Janosch
    The cost-efficient development for dependable systems is one of the major future challenges of the automotive industry. Existing fault tolerance approaches are often not applicable and not sufficient. Therefore, innovative alternatives are required. A possible solution is given by dynamic adaptation. In the case of errors, dynamic adaptation can ensure that the best possible system functionality is achieved and that critical functions are kept alive (survivability). Exploiting implicitly available redundancy, dynamic adaptation provides a cost-efficient means to keep up functionalities as long as possible without requiring expensive explicit redundancy channels. Unconstrained dynamic adaptation can lead to emergent, unpredictable behavior, making it inapplicable for safetycritical systems. In this paper, we illustrate how adaptation behavior can be explicitly modeled, analyzed, and verified at design time. By this means, it is possible to use the advantages of dynamic adaptation for the realization of safe and reliable systems.
  • Publication
    Probabilistic analysis of safety-critical adaptive systems with temporal dependences
    ( 2007)
    Adler, Rasmus
    ;
    Domis, Dominik J.
    ;
    Förster, Marc
    ;
    Trapp, Mario
    Dynamic adaptation means that components are reconfigured at run time. Consequently, the degree to which a system fulfils its functional and safety requirements depends on the current system configuration at run time. The probability of a violation of functional requirements in combination with an importance factor for each requirement gives us a measure for reliability. In the same way, the degree of violation of safety requirements can be a measure for safety. These measures can easily be derived based on the probabilities of possible system configurations. For this purpose, we are introducing a new probabilistic analysis technique that determines configuration probabilities based on Fault trees, Binary Decision Diagrams (BDDs) and Markov chains. Through our recent work we have been able to determine configuration probabilities of systems but we neglected timing aspects [1]. Timing delays have impact on the adaptation behavior and are necessary to handle cyclic dependences. The contribution of the present article is to extend analysis towards models with timing delays. This technique builds upon the Methodologies and Architectures for Runtime Adaptive Systems (MARS) [2], a modeling concept we use for specifying the adaptation behavior of a system at design time. The results of this paper determine configuration probabilities, that are necessary to quantify the fulfillment of functional and safety requirements by adaptive systems.