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Dagstuhl Seminar 98441

Adaptation and Evolution in Embedded Information Systems

( Nov 02 – Nov 06, 1998 )

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Please use the following short url to reference this page: https://www.dagstuhl.de/98441

Organizers
  • B. Kleinjohann (Paderborn)
  • H. Franke (IBM Yorktown Heights)
  • J. Sztipanovits (Vanderbilt Univ.)



Motivation

Among the most significant technological developments of the last two decades has been the proliferation of embedded information systems (EISs). In EISs, functional, performance and reliability requirements mandate a tight integration of information processing and physical processes. EISs include a wide range of applications, such as computer-integrated manufacturing (CIM) systems, aerospace systems, computerized vehicles, appliances, consumer electronics equipment, and a wide variety of systems in health care, transportation, defense, communication, power generation and distribution. The rapid evolution of EISs has triggered paradigm shifts in industry and exerted a profound impact on engineering processes throughout the system life cycle, from design through manufacturing, operation and maintenance. This trend is clearly demonstrated by the dramatic increase of the role and size of software in products. For example, currently, over 60% of the development cost of aerospace systems is software, but even an electric shaver has over 16K bytes software.

The ultimate driver of this trend is the fact that incorporation of information processing as an integral part of physical systems increases the potential interactions among physical components and processes, generates complex dynamics, and establishes component interdependencies unknown in previous-generation systems. The tight integration of "physical" and "information" processes represents major challenges for the software technology. First of all, using Brooks terminology, the "conceptual construct" of the software which represents its "essential complexity" is inextricably combined with the conceptual construct of its "external environment", i.e. with the structure of physical processes. Consequently, the overall system behavior can only be understood if information, material and energy transfer processes are modeled and analyzed together. It means that software artifacts need to be modeled together "with their context", using a modeling language - or modeling paradigm - which is meaningful for the design, analysis and operation of the whole system. Another well-known challenge in the design and implementation of EIS software stems from the fact that it serves as a component in a larger, changing, heterogeneous system. As a result of this, the EIS software cannot be static, it must change, evolve together with its embedding environment. An additional challenge of EIS software technology is criticality. EIS software directly impacts the operation of physical processes and failure may cause unacceptable social or economic damage. Thus the software technology must offer methods and tools for the formal verification and validation of system level requirements, such as dependability, safety and reliability.

This seminar intends to bring together leading researchers from academia and industry in the areas of embedded information systems, adaptive software architectures and evolutionary design environments. The goal is to review state-of-the-art and map future research directions that help to answer challenges in EIS and to investigate the potential of applying recent advances in the aforementioned fields. The seminar will include the following topics:

  1. Definition and characterization of adaptive and evolutionary embedded systems:
    • needs
    • characteristics
    • case studies
  2. Critical technology components
    • self-adaptive software architectures
    • architecture-based evolution
    • incremental, embeddable generators
    • transient management
  3. Design environments
    • design abstractions, hybrid/heterogeneous modeling
    • verification, correctness by construction
    • incremental design
    • design optimization

Participants
  • B. Kleinjohann (Paderborn)
  • H. Franke (IBM Yorktown Heights)
  • J. Sztipanovits (Vanderbilt Univ.)