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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

23 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 language	English
Title of host publication	12th Working Conference on Mining Software Repositories (MSR'15, Florence, Italy, May 16-17, 2015)
Place of Publication	Piscataway
Publisher	IEEE Press
Pages	494-497
ISBN (Print)	978-0-7695-5594-2
DOIs	https://doi.org/10.1109/MSR.2015.72
Publication status	Published - 2015
Event	12th Working Conference on Mining Software Repositories (MSR 2015) - Palazzo dei Congressi, Florence, Italy Duration: 16 May 2015 → 17 May 2015 Conference number: 12 http://2015.msrconf.org/

Conference

Conference	12th Working Conference on Mining Software Repositories (MSR 2015)
Abbreviated title	MSR 2015
Country/Territory	Italy
City	Florence
Period	16/05/15 → 17/05/15
Other	Conference co-located with the 37th International Conference on Software Engineering (ICSE 2015)
Internet address	http://2015.msrconf.org/

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10.1109/MSR.2015.72

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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",

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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, pp. 494-497, 12th Working Conference on Mining Software Repositories (MSR 2015), Florence, Italy, 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. p. 494-497.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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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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T2 - 12th Working Conference on Mining Software Repositories (MSR 2015)

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ER -

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

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