Abstract
Software safety standards recommend techniques to use throughout the software development lifecycle. These recommendations are a result of consensus building amongst software safety experts. Thus the reasoning underpinning compliance to these standards tends to be quite subjective. In addition, there are factors such as the size of the project, the effect of a review process on earlier phases of the development lifecycle, the complexity of the design and the quality of the staff, that arguably influence the assessment process but are not formally addressed by software safety standards. In this paper we present an expert system based on Bayesian Belief networks that take into account these and other factors when assessing the integrity at which the software was developed. This system has been reviewed by engineers working with software safety standard IEC61508. In this paper we illustrate some arguments that can be supported using the proposed system.
This paper and the work it describes were partly funded by the Health and Safety Executive. The opinions or conclusions expressed are those of the authors alone and do not necessarily represent the views of the Health and Safety Executive.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Korb, B.K., Nicholson, A.E.: Bayesian Artificial Intelligence. Chapman & Hall/CRC, Boca Raton (2003)
IEC61508 functional safety of electrical/ electronic/ programmable electronic safety-related systems parts 1-7. Published by the International Electrotechnical Commission (IEC), Geneva, Switzerland (1998-2000)
Jensen, F.: An Introduction to Bayesian networks. UCL Press limited (1996) ISBN: 1857283325
Hugin A/S: http://www.hugin.com
Morgan, M.G., Henrion, M.: Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis. Cambridge University Press, Cambridge (1990)
Morris, A.P.: Combining Experts Judgments: A Bayesian Approach. Management Science Journal 23(7) (1977)
Spiegelhalter, D.J., Dawid, A.P., Lauritzen, S.L., Cowell, R.G.: Bayesian Analysis in Expert Systems. Journal of Statistical Science 8(3), 219–283 (1993)
Cowell, R.G., Dawid, A.P., Speigelhalter, D.J.: Sequential Model Criticism in Probabilistic Expert Systems. IEEE Transactions on Pattern Analysis and Machine Intelligence 15(3) (1993)
Cockram, T.: Gaining confidence in software Inspection using a Bayesian Belief Model. Software Quality Journal 9(1), 31–42 (2001)
Cockram, T.: The use of Bayesian Networks to determine software inspection process efficiency. Ph.D Thesis. England, Open university (2002)
Hall, P., May, J., Nichol, D., Csachur, K., Kinch, B.: Integrity Prediction during Software Development. In: Safety of Computer Control Systems (SAFECOMP 1992), Computer Systems in Safety-Critical Applications, Proceedings of the IFAC Symposium, Zurich, Switzerland, October 28-30 (1992)
Fenton, N.E., Neil, M., Marsh, W., Krause, P., Mishra, R.: Predicting Software Defects in Varying Development Lifecycles using Bayesian Nets. ESEC (submitted, 2005)
Fenton, N.E., Krause, P., Neil, M.: Probabilistic Modelling for Software Quality Control. In: Benferhat, S., Besnard, P. (eds.) ECSQARU 2001. LNCS, vol. 2143, p. 444. Springer, Heidelberg (2001)
Fenton, N.E., Neil, M.: Making Decisions: Using Bayesian Nets and MCDA. Knowledge-Based Systems 14, 307–325 (2001)
Gran, B.A.: Assessment of programmable systems using Bayesian Belief nets. Safety Science 40, 797–812 (2002)
Gran, B.A.: Use of Bayesian Belief Networks when combining disparate sources of information in the safety assessment of software-based systems. International Journal of Systems Science 33(6), 529–542 (2002)
Lauritzen, S.: Graphical Models. Oxford Science Publications, Oxford (1996) ISBN 0198522193
Lauritzen, S.L., Spiegelhalter, D.J.: Local Computations with Probabilities on Graphical Structures and their Application to Expert Systems. Royal Statistical Society Journal 50(2), 157–224 (1988)
Pearl, J.: Probabilistic reasoning in intelligent systems. Morgan Kaufmann, San Mateo (1988)
Smith, D., Simpson, K.: Functional Safety – A straightforward guide to applying IEC61508 and related standards, 2nd edn. Elsevier, Amsterdam (2004)
Bishop, P.G., Bloomfield, R.E.: A conservative theory for long term reliability growth prediction. In: Proceedings of the Seventh International Symposium on Software Reliability Engineering, pp. 308–317 (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Brito, M., May, J. (2006). Gaining Confidence in the Software Development Process Using Expert Systems. In: Górski, J. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2006. Lecture Notes in Computer Science, vol 4166. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11875567_9
Download citation
DOI: https://doi.org/10.1007/11875567_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45762-6
Online ISBN: 978-3-540-45763-3
eBook Packages: Computer ScienceComputer Science (R0)