Defect Prediction over Software Life Cycle in Automotive Domain - State of the Art and Road Map for Future
Rakesh Rana, Miroslaw Staron, Jörgen Hansson, Martin Nilsson
2014
Abstract
Software today provides an important and vital role in providing the functionality and user experience in automotive domain. With ever increasing size and complexity of software together with high demands on quality and dependability, managing software development process effectively is an important challenge. Methods of software defect predictions provide useful information for optimal resource allocation and release planning; they also help track and model software and system reliability. In this paper we present an overview of defect prediction methods and their applicability in different software lifecycle phases in the automotive domain. Based on the overview and current trends we identify that close monitoring of in service performance of software based systems will provide useful feedback to software development teams and allow them to develop more robust and user friendly systems.
References
- Boehm, Barry W. 1988. “A Spiral Model of Software Development and Enhancement.” Computer 21 (5): 61-72.
- Broy, Manfred. 2006. “Challenges in Automotive Software Engineering.” In Proceedings of the 28th International Conference on Software Engineering, 33-42.
- Ceylan, Evren, F. Onur Kutlubay, and Ayse Basar Bener. 2006. “Software Defect Identification Using Machine Learning Techniques.” In 32nd EUROMICRO Conference on Software Engineering and Advanced Applications, SEAA'06., 240-47. IEEE.
- Charette, Robert N. 2009. “This Car Runs on Code.” IEEE Spectrum 46 (3): 3.
- Dieterle, Werner. 2005. “Mechatronic Systems: Automotive Applications and Modern Design Methodologies.” Annual Reviews in Control 29 (2): 273-77.
- Fenton, N.E., and M. Neil. 1999. “A Critique of Software Defect Prediction Models.” IEEE Transactions on Software Engineering 25 (5): 675-89. doi:10.1109/32.815326.
- Fenton, Norman, Martin Neil, William Marsh, Peter Hearty, Lukasz Radlinski, and Paul Krause. 2008. “On the Effectiveness of Early Life Cycle Defect Prediction with Bayesian Nets.” Empirical Software Engineering 13 (5): 499- 537. doi:10.1007/s10664-008-9072-x.
- Gondra, Iker. 2008. “Applying Machine Learning to Software Fault-Proneness Prediction.” Journal of Systems and Software 81 (2): 186-95.
- ISO. 2011. “International Standard-ISO 26262-Road Vehicles-Functional Safety”. International Organization for Standardization.
- Khoshgoftaar, Taghi M., and Edward B. Allen. 1999. “Logistic Regression Modeling of Software Quality.” International Journal of Reliability, Quality and Safety Engineering 6 (04): 303-17.
- Menzies, Tim, Jeremy Greenwald, and Art Frank. 2007. “Data Mining Static Code Attributes to Learn Defect Predictors.” IEEE Transactions on Software Engineering 33 (1): 2-13.
- Rana, Rakesh, Miroslaw Staron, Christian Berger, Jörgen Hansson, Martin Nilsson, and Fredrik Törner. 2013. “Evaluating Long-Term Predictive Power of Standard Reliability Growth Models on Automotive Systems.” In Pasadena, CA, USA.
- Rana, Rakesh, Miroslaw Staron, Niklas Mellegård, Christian Berger, Jörgen Hansson, Martin Nilsson, and Fredrik Törner. 2013. “Evaluation of Standard Reliability Growth Models in the Context of Automotive Software Systems.” In Product-Focused Software Process Improvement, 324-29. Springer.
- Staron, Miroslaw, and Wilhelm Meding. 2008. “Predicting Weekly Defect Inflow in Large Software Projects Based on Project Planning and Test Status.” Information and Software Technology 50 (7): 782-96.
Paper Citation
in Harvard Style
Rana R., Staron M., Hansson J. and Nilsson M. (2014). Defect Prediction over Software Life Cycle in Automotive Domain - State of the Art and Road Map for Future . In Proceedings of the 9th International Conference on Software Engineering and Applications - Volume 1: ICSOFT-EA, (ICSOFT 2014) ISBN 978-989-758-036-9, pages 377-382. DOI: 10.5220/0005099203770382
in Bibtex Style
@conference{icsoft-ea14,
author={Rakesh Rana and Miroslaw Staron and Jörgen Hansson and Martin Nilsson},
title={Defect Prediction over Software Life Cycle in Automotive Domain - State of the Art and Road Map for Future},
booktitle={Proceedings of the 9th International Conference on Software Engineering and Applications - Volume 1: ICSOFT-EA, (ICSOFT 2014)},
year={2014},
pages={377-382},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005099203770382},
isbn={978-989-758-036-9},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 9th International Conference on Software Engineering and Applications - Volume 1: ICSOFT-EA, (ICSOFT 2014)
TI - Defect Prediction over Software Life Cycle in Automotive Domain - State of the Art and Road Map for Future
SN - 978-989-758-036-9
AU - Rana R.
AU - Staron M.
AU - Hansson J.
AU - Nilsson M.
PY - 2014
SP - 377
EP - 382
DO - 10.5220/0005099203770382