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

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

doi:10.1109/MSR.2015.72

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

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

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

23 Citaten (Scopus)

1 Downloads (Pure)

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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.

Originele taal-2	Engels
Titel	12th Working Conference on Mining Software Repositories (MSR'15, Florence, Italy, May 16-17, 2015)
Plaats van productie	Piscataway
Uitgeverij	IEEE Press
Pagina's	494-497
ISBN van geprinte versie	978-0-7695-5594-2
DOI's	https://doi.org/10.1109/MSR.2015.72
Status	Gepubliceerd - 2015
Evenement	12th Working Conference on Mining Software Repositories (MSR 2015) - Palazzo dei Congressi, Florence, Italië Duur: 16 mei 2015 → 17 mei 2015 Congresnummer: 12 http://2015.msrconf.org/

Congres

Congres	12th Working Conference on Mining Software Repositories (MSR 2015)
Verkorte titel	MSR 2015
Land/Regio	Italië
Stad	Florence
Periode	16/05/15 → 17/05/15
Ander	12th Working Conference on Mining Software Repositories
Internet adres	http://2015.msrconf.org/

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10.1109/MSR.2015.72

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@inproceedings{de70b7ee56dc4ee0a57b09089f017801,

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

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.",

author = "H. Altinger and S. Siegl and Y. Dajsuren and F. Wotawa",

year = "2015",

doi = "10.1109/MSR.2015.72",

language = "English",

isbn = "978-0-7695-5594-2",

pages = "494--497",

booktitle = "12th Working Conference on Mining Software Repositories (MSR'15, Florence, Italy, May 16-17, 2015)",

publisher = "IEEE Press",

note = "12th Working Conference on Mining Software Repositories (MSR 2015), MSR 2015 ; Conference date: 16-05-2015 Through 17-05-2015",

url = "http://2015.msrconf.org/",

}

Altinger, H, Siegl, S, Dajsuren, Y & Wotawa, F 2015, A novel industry grade dataset for fault prediction based on model-driven developed automotive embedded software. in 12th Working Conference on Mining Software Repositories (MSR'15, Florence, Italy, May 16-17, 2015). IEEE Press, Piscataway, blz. 494-497, 12th Working Conference on Mining Software Repositories (MSR 2015), Florence, Italië, 16/05/15. https://doi.org/10.1109/MSR.2015.72

A novel industry grade dataset for fault prediction based on model-driven developed automotive embedded software. / Altinger, H.; Siegl, S.; Dajsuren, Y. et al.
12th Working Conference on Mining Software Repositories (MSR'15, Florence, Italy, May 16-17, 2015). Piscataway: IEEE Press, 2015. blz. 494-497.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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N2 - 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.

AB - 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.

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DO - 10.1109/MSR.2015.72

M3 - Conference contribution

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BT - 12th Working Conference on Mining Software Repositories (MSR'15, Florence, Italy, May 16-17, 2015)

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

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