Trace Checking of Metric Temporal Logic with Aggregating Modalities Using MapReduce

  • Domenico Bianculli
  • Carlo Ghezzi
  • Srđan Krstić
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8702)


Modern complex software systems produce a large amount of execution data, often stored in logs. These logs can be analyzed using trace checking techniques to check whether the system complies with its requirements specifications. Often these specifications express quantitative properties of the system, which include timing constraints as well as higher-level constraints on the occurrences of significant events, expressed using aggregate operators.

In this paper we present an algorithm that exploits the MapReduce programming model to check specifications expressed in a metric temporal logic with aggregating modalities, over large execution traces. The algorithm exploits the structure of the formula to parallelize the evaluation, with a significant gain in time. We report on the assesment of the implementation—based on the Hadoop framework—of the proposed algorithm and comment on its scalability.


Temporal Logic Execution Trace MapReduce Framework Hadoop MapReduce Reduce Task 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Domenico Bianculli
    • 1
  • Carlo Ghezzi
    • 2
  • Srđan Krstić
    • 2
  1. 1.SnT CentreUniversity of LuxembourgLuxembourg
  2. 2.DEEP-SE group - DEIBPolitecnico di MilanoItaly

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