This paper focuses on the analysis of execution traces for real-time systems. Kernel tracing can provide useful information, without\nhaving to instrument the applications studied. However, the generated traces are often very large.The challenge is to retrieve only\nrelevant data in order to find quickly complex or erratic real-time problems. We propose a new approach to help finding those\nproblems. First, we provide a way to define the execution model of real-time tasks with the optional suggestions of a pattern\ndiscovery algorithm. Then, we show the resulting real-time jobs in a Comparison View, to highlight those that are problematic.\nOnce some jobs that present irregularities are selected, different analyses are executed on the corresponding trace segments instead\nof the whole trace.This allows saving huge amount of time and execute more complex analyses.Our main contribution is to combine\nthe critical path analysis with the scheduling information to detect scheduling problems. The efficiency of the proposed method is\ndemonstrated with two test cases, where problems that were difficult to identify were found in a few minutes.
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