Logo des Repositoriums

Auflistung nach Autor:in "Scheerer, Max"

1 - 3 von 3
  • Zeitschriftenartikel
    Evaluating Architectural Safeguards for Uncertain AI Black-Box Components
    (Softwaretechnik-Trends Band 44, Heft 2, 2024) Scheerer, Max
    There have been enormous achievements in the field of Artificial Intelligence (AI) which has attracted a lot of attention. Their unverifiable nature, however, makes them inherently unreliable. For example, there are various reports of incidents in which incorrect predictions of AI components led to serious system malfunctions (some even ended fatally). As a result, various architectural approaches (referred to as Architectural Safeguards) have been developed to deal with the unreliable and uncertain nature of AI. Software engineers are now facing the challenge to select the architectural safeguard that satisfies the non-functional requirements (e.g. reliability) best. However, it is crucial to resolve such design decisions as early as possible to avoid (i) changes after the system has been deployed (and thus potentially high costs) and to meet the rigorous quality requirements of safety-critical systems where AI is more commonly used. This dissertation presents a model-based approach that supports software engineers in the development of AI-enabled systems by enabling the evaluation of architectural safeguards. More specifically, an approach for reliability prediction of AI-enabled systems (based on established model-based techniques) is presented. Moreover, the approach is generalised to architectural safeguards with self-adaptive capabilities, i.e. self adaptive systems. The approach has been validated by considering four case studies. The results show that the approach not only makes it possible to analyse the impact of architectural safeguards on the overall reliability of an AI-enabled system, but also supports software engineers in their decision-making.
  • Textdokument
    Holistische Verifikation von Hybriden Quantenprogrammen durch Software Bounded Model Checking
    (INFORMATIK 2021, 2021) Klamroth,Jonas; Scheerer, Max; Denninger, Oliver
    Quantencomputer erschließen uns durch ihren überpolynomiellem Speedup neue Anwendungsfelder für schwer-berechenbare Probleme. Der Entwurf von Quantenalgorithmen ist bisher allerdings komplex und fehleranfällig. Daher ist zu erwarten, dass vorerst nur einzelne Subroutinen eines Programms auf Quantencomputern umgesetzt werden. Um die Korrektheit solcher Programme garantieren zu können, sind neue Ansätze erforderlich. In dieser Arbeit stellen wir einen Ansatz zum vollautomatischen Nachweis der Korrektheit von Programmen mit eingebetteten Quantenalgorithmen vor. Dazu bauen wir auf Bounded-Model-Checking-Verfahren auf, welche die Fehlerfreiheit hinsichtlich einer gegebenen Spezifikation beweisen können. Als Spezifikationssprache verwenden wir JML. Dabei werden die Quantenalgorithmen als Quantenschaltkreis beschrieben und in Java eingebettet. Wir zeigen die Umsetzbarkeit unseres Ansatzes an zwei etablierten Quantenalgorithmen.
  • Konferenzbeitrag
    SimuLizar NG: An extensible event-oriented simulation engine for self-adaptive software architectures
    (Softwaretechnik-Trends Band 39, Heft 3, 2019) Krach, Sebastian Dieter; Scheerer, Max
    Software simulation constitutes an essential mechanism for design time architecture analysis. Domain-specific software, e.g. of cyber-physical systems, requires domain-specific extensions to the architecture models and their execution semantics. Existing simulators are cumbersome to extend, do not support self-adaptivity or do not scale well. In this paper we present concepts of SimuLizar NG, a scalable simulation engine for the SimuLizar approach. Its principal goal is to facilitate domain-specific extension and adaptations to the model interpretation semantic while at the same time ensuring reactive simulation execution in demanding scalability scenarios.