On error-class distribution in automotive model-based software

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[1] Altinger, Harald
[2] Dajsuren, Yanja
[3] Siegl, Sebastian
[4] Vinju, Jurgen J.
[5] Wotawa, Franz
来源：
Altinger, Harald (harald.altinger@audi.de) | 1600年 / Institute of Electrical and Electronics Engineers Inc.卷 / 01期
关键词：
Software fault prediction promises to be a powerful tool in supporting test engineers upon their decision where to define testing hotspots. However; there are limitations on a cross project prediction and a lack of reports upon application to industrial software; as well as the power of metrics to represent bugs. In this paper; we present a novel analysis based upon faults discovered in model-based automotive software projects and their relationship to metrics used to perform fault prediction. Using our previously released dataset on software metrics; we report bug classes discovered during heavy testing of those automotive software. As the software has been developed following strict coding and development guidelines; we present the results based on a comparison between the discovered error classes and those which might derive a reduced potential error set. Using the three projects from our dataset we determine if any of these bug classes are project specific. © 2016 IEEE;
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