Novel insights on cross project fault prediction applied to automotive software

Harald Altinger*, Steffen Herbold, Jens Grabowski, Franz Wotawa

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Defect prediction is a powerful tool that greatly helps focusing quality assurance efforts during development. In the case of the availability of fault data from a particular context, there are different ways of using such fault predictions in practice. Companies like Google, Bell Labs and Cisco make use of fault prediction, whereas its use within auto- motive industry has not yet gained a lot of attraction, although, modern cars require a huge amount of software to operate. In this paper, we want to contribute the adoption of fault prediction techniques for automotive software projects. Hereby we rely on a publicly available data set comprising fault data from three automotive software projects. When learning a fault prediction model from the data of one particular project, we achieve a remarkably high and nearly perfect prediction performance for the same project. However, when applying a cross-project prediction we obtain rather poor results. These results are rather surprising, because of the fact that the underlying projects are as similar as two distinct projects can possibly be within a certain application context. Therefore we investigate the reasons behind this observation through correlation and factor analyses techniques. We further report the obtained findings and discuss the consequences for future applications of Cross-Project Fault Prediction (CPFP) in the domain of automotive software.

Original languageEnglish
Title of host publicationTesting Software and Systems - 27th IFIP WG 6.1 International Conference, ICTSS 2015, Proceedings
EditorsNina Yevtushenko, Khaled El-Fakih, Gerassimos Barlas
PublisherSpringer-Verlag Italia
Pages141-157
Number of pages17
ISBN (Print)9783319259444
DOIs
Publication statusPublished - 1 Jan 2015
Externally publishedYes
Event27th IFIP WG 6.1 International Conference on Testing Software and Systems, ICTSS 2015 - Sharjah and Dubai, United Arab Emirates
Duration: 23 Nov 201525 Nov 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9447
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference27th IFIP WG 6.1 International Conference on Testing Software and Systems, ICTSS 2015
CountryUnited Arab Emirates
CitySharjah and Dubai
Period23/11/1525/11/15

Keywords

  • Automotive
  • Cross project fault prediction
  • Principal component analysis
  • Project fault prediction

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Novel insights on cross project fault prediction applied to automotive software'. Together they form a unique fingerprint.

Cite this