Abstract
In recent times, the number of features within a modern-day premium automobile has significantly increased. The majority of them are realized by software, leading to more than 1,000,000 LOC ranging from keeping the vehicle on the track to displaying a movie for rear seat entertainment. The majority of software modules need to be executed on embedded systems, some of them fulfilling mission-critical task, where a failure might lead to a fatal accident. Software development within the automotive industry is different from other industries or open source, as there are more restrictions upon development guidelines and rather strict testing definitions to meet the quality and reliability requirements or even ensure traceability on defect liability. To meet these requirements, various tools and processes have been integrated into the development process, delivering document metadata which can be used for further insights, for example, Software Fault Prediction (SFP).
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References
Altinger H (2015) Dataset on automotive software repository. http://www.ist.tugraz.at/_attach/Publish/AltingerHarald/MSR_2015_dataset_automotive.zip
Altinger H, Wotawa F, Schurius M (2014) Testing methods used in the automotive industry: results from a survey. In: Proceedings of JAMAICA. ACM, New York, pp 1–6
Altinger H, Herbold S, Grabowski J, Wotawa F (2015) Novel insights on cross project fault prediction applied to automotive software. In: El-Fakih K, Barlas G, Yevtushenko N (eds) Testing software and systems, vol 9447. Springer, Berlin, pp 141–157. http://dx.doi.org/10.1007/978-3-319-25945-1_9
Altinger H, Dajsuren Y, Sieg S, Vinju JJ, Wotawa F (2016) On error-class distribution in automotive model-based software. In: 2016 IEEE 23rd international conference on software analysis, evolution, and reengineering, IEEE, Piscataway, pp 688–692. https://doi.org/10.1109/SANER.2016.81
Altinger H, Herbold S, Wotawa F, Schneemann F (2017) Performance tuning for automotive software fault prediction. In: 2017 IEEE 24th international conference on software analysis, evolution, and reengineering. IEEE, Piscataway. https://doi.org/10.1109/SANER.2017.7884667
Audi AG (2017) Audi A8 (Typ 4N) Selbststudienprogramm 662. Technical manual. AUDI AG
Bergmann R, Walesch R (2012) HiL strategie audi. In: 6. dSpace Anwender Konfernz 2012, dSpace. http://www.dspace.com/shared/data/pdf/ankon2013/tag1_pdf/2_audi_walesch_robert_bergmann_richard.pdf
Bock T, Maurer M, Farber G (2007) Validation of the vehicle in the loop (VIL); a milestone for the simulation of driver assistance systems. In: 2007 IEEE Intelligent vehicles symposium, pp 612–617
Bock T, Maurer M, Meel F, Müller T (2008) Vehicle in the loop. ATZ Automobiltech Z 110(1):10–16. http://dx.doi.org/10.1007/BF03221943
Bock F, Homm D, Siegl S, German R (2016) A taxonomy for tools, processes and languages in automotive software engineering abs/1601.03528. http://arxiv.org/abs/1601.03528
Broy M, Kruger I, Pretschner A, Salzmann C (2007) Engineering automotive software. Proc IEEE 95(2):356–373. https://doi.org/10.1109/JPROC.2006.888386
Capers J (2009) A short history of the cost per defect metric. www.semat.org
Charette RN (2009) This car runs on code. IEEE Spectr 46(3):3
Duba GP, Bock T (2008) ATZextra Worldw 13:56. https://doi.org/10.1365/s40111-008-0055-0
Dupuis M, von Neumann-Cosel K, Weiss C (2010) Virtual test drive vereinheitlichung der simulationsumgebung für SiL-, HiL-, DiL-und ViL-tests bei der entwicklung von fahrerassistenz-und aktiven sicherheitssystemen
Herbold S, Grabowski J, Waack S (2011) Calculation and optimization of thresholds for sets of software metrics. Empir Softw Eng 16(6):812–841. https://doi.org/10.1007/s10664-011-9162-z
ISO TC 22 SC 3 (2011) ISO 26262:2011:Road vehicles – Functional safety. International. www.iso.org
Jin-Hua L, Qiong L, Jing L (2008) The w-model for testing software product lines. In: International Symposium on Computer Science and Computational Technology, 2008. ISCSCT’08, vol 1, pp 690–693
Kiffe G, Bock T (2013) Standardisierte entwicklungsumgebung fuer die softwareeigenentwicklung bei audi. In: 7. cSapce User Conference, dSpace, https://www.dspace.com/de/gmb/home/company/events/dspace_events/archive_2013/ankon2013.cfm
Mathworks T (2014) Mathworks automotive advisory board checks (MAAB). http://de.mathworks.com/help/slvnv/ref/mathworks-automotive-advisory-board-checks.html
Miegler M, Nentwig M (2015) Testing of piloted driving on virtual streets. ATZ Worldw 117(9):16–21. http://dx.doi.org/10.1007/s38311-015-0044-7
Miegler M, Schieber R, Kern A, Ganslmeier T, Nentwig M (2009) Hardware-in-the-loop test of advanced driver assistance systems. ATZ Elektron Worldw 4(5):4–9
Motor Industry Software Reliability Association (2004) MISRA-C:2004 - Guidelines for the use of the C language in critical systems, 2nd edn. MISRA
Müller DIFSO, Brand IM, Wachendorf S, Schröder DIFH, Szot DIFT, Schwab DIS, Kremer B (2009) Integration vernetzter fahrerassistenz-funktionen mit HiL für den VW passat CC 14(4):60–65
Nagappan N, Ball T, Zeller A (2006) Mining metrics to predict component failures. In: Proceedings of the 28th international conference on software engineering, pp 452–461
Nentwig M, Stamminger M (2011) Hardware-in-the-loop testing of computer vision based driver assistance systems. In: 2011 IEEE Intelligent vehicles symposium (IV), pp 339–344. https://doi.org/10.1109/IVS.2011.5940567
NHTSA USDoT {and} USAgov (1997) Office of defects investigation (ODI) recalls database. www-odi.nhtsa.dot.gov
Reactis (2015) Achieving ISO 26262 compliance with reactis. http://www.reactive-systems.com/papers/iso-26262.pdf
Sayyad Shirabad J, Menzies T (2005) The PROMISE Repository of Software Engineering Databases. http://promise.site.uottawa.ca/SERepository, published: School of Information Technology and Engineering, University of Ottawa, Canada
Shea T (2010) Why does it cost so much for automakers to develop new models? http://www.autoblog.com/2010/07/27/why-does-it-cost-so-much-for-automakers-to-develop-new-models/
VW Aktiengesellschaft (2014) Geschaeftsbericht 2014. http://geschaeftsbericht2014.volkswagenag.com/konzernlagebericht/nachhaltige-wertsteigerung/forschung-und-entwicklung/f-e-kennzahlen.html
WARDS Auto (2013) U.S. car and truck sales, 1931–2013. www.wardsauto.com
Zimmermann T, Premraj R, Zeller A (2007) Predicting defects for eclipse. In: International Workshop on Predictor models in software engineering, 2007. PROMISE’07: ICSE Workshops 2007. IEEE, Piscataway, p 9
Zimmermann T, Nagappan N, Gall H, Giger E, Murphy B (2009) Cross-project defect prediction: a large scale experiment on data vs. domain vs. process. In: Proceedings of the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on the foundations of software engineering, pp 91–100
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Altinger, H. (2019). State-of-the-Art Tools and Methods Used in the Automotive Industry. In: Dajsuren, Y., van den Brand, M. (eds) Automotive Systems and Software Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-12157-0_4
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