A novel industry grade dataset for fault prediction based on model-driven developed automotive embedded software

H. Altinger, S. Siegl, Y. Dajsuren, F. Wotawa

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

    11 Citations (Scopus)
    1 Downloads (Pure)

    Abstract

    In this paper, we present a novel industry dataset on static software and change metrics for Matlab/Simulink models and their corresponding auto-generated C source code. The data set comprises data of three automotive projects developed and tested accordingly to industry standards and restrictive software development guidelines. We present some background information of the projects, the development process and the issue tracking as well as the creation steps of the dataset and the used tools during development. A specific highlight of the dataset is a low measurement error on change metrics because of the used issue tracking and commit policies.
    Original languageEnglish
    Title of host publication12th Working Conference on Mining Software Repositories (MSR'15, Florence, Italy, May 16-17, 2015)
    Place of PublicationPiscataway
    PublisherIEEE Press
    Pages494-497
    ISBN (Print)978-0-7695-5594-2
    DOIs
    Publication statusPublished - 2015
    Event12th Working Conference on Mining Software Repositories (MSR 2015) - Palazzo dei Congressi, Florence, Italy
    Duration: 16 May 201517 May 2015
    Conference number: 12
    http://2015.msrconf.org/

    Conference

    Conference12th Working Conference on Mining Software Repositories (MSR 2015)
    Abbreviated titleMSR 2015
    Country/TerritoryItaly
    CityFlorence
    Period16/05/1517/05/15
    OtherConference co-located with the 37th International Conference on Software Engineering (ICSE 2015)
    Internet address

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