Worst-Case Execution Time Optimization of Story Patterns for Hard Real-Time Systems

In the future, technical systems are expected to operate more intelligent than today by taking their local context explored by means of sensors and network communication into account. To realize this vision, the systems must be able to represent and query as well as interact with a large number of possible situations not known a priori. Therefore, flexible means to store, query, and manipulate such context information are required. Known flexible and powerful representations are class diagrams or other graph-like notations. However, such dynamic data structures which are sources for unpredictable run-time timing behavior are traditionally not recommended for the development of hard real-time systems. In this paper, we describe our efforts to employ story patterns, which are used for the specification of query and update operations on dynamic data structures, in hard real-time systems.

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