Complexity Based Test Cases for Log File Analyzers

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    1 Citation (Scopus)


    Log files are used in many big data applications. If the log is meant for a different purpose, the analysis and finding the best log analyzer can be very complex. Our solution is to create a generic test case framework to model and create representative log data. Related work model the behavior as state machines, but our model uses a composition of elementary acyclic graphs, thus addressing the log file size, variation, branching and confidence. We have created test cases originally based on real Intelligent Transportation Systems (ITS) data, and evaluated our LOGDIG analyzer against it. We can easily generate hundreds of test cases with our model, and modify the cases as needed.
    Original languageEnglish
    Title of host publicationIEEE 15th International Conference of Industrial Informatics (INDIN 2017)
    ISBN (Electronic)978-1-5386-0837-1
    ISBN (Print)978-1-5386-0838-8
    Publication statusPublished - Jul 2017
    Publication typeA4 Article in conference proceedings
    EventIEEE International Conference on Industrial Informatics -
    Duration: 1 Jan 1900 → …

    Publication series

    ISSN (Electronic)2378-363X


    ConferenceIEEE International Conference on Industrial Informatics
    Period1/01/00 → …

    Publication forum classification

    • Publication forum level 1


    Dive into the research topics of 'Complexity Based Test Cases for Log File Analyzers'. Together they form a unique fingerprint.

    Cite this