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This paper presents a novel approach to timing analysis of complex real-time systems containing data-driven tasks with intricate execution dependencies. Using a system model inspired by industrial control systems, we show how the execution time of tasks can be represented as a mathematical expression instead of a single numeric value. Next, based on this more detailed modeling, we introduce a concrete process of formally obtaining the exact value of both Worst-Case Execution-Time (WCET) and Worst-Case Response-Time (WCRT) of tasks by using upper-part binary search and TIMES (a timed model checker). Finally, in order to show the potential of the proposed approach, we apply it to a model created from a real robotic control system for which the traditional way of obtaining a WCET estimate (through static WCET analysis) on tasks for usage in basic RTA is not appropriate. Our results indicate a significant reduction of pessimism when compared to basic RTA using WCET estimates on tasks given by a basic assumption.