Abstract
Faults introduced in design or during implementation might be prevented by design validation and by evaluation during implementation. There are numerous methods available for validating and evaluating software. Expert judgment is a much used approach to identify problematic areas in design or target challenges related to implementation. ISTec and IFE cooperate on a project on automated complexity measurements of software of digital instrumentation and control (I&C) systems. Metrics measured from the function blocks and logic diagrams specifying I&C-systems are used as input to a Bayesian Belief Net describing correlation between inputs and a complexity metric. By applying expert judgment in the algorithms for the automatic complexity evaluation, expert judgment is applied to entire software systems. The results from this approach can be used to identify parts of software which from a complexity viewpoint is eligible for closer inspection. In this paper we describe the approach in detail as well as plans for testing the approach.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Fenton, N., Littlewood, B., Neil, M., Strigini, L., Sutcliffe, A., Wright, D.: Assessing Dependability of Safety Critical Systems using Diverse Evidence. In: IEEE Proceedings Software Engineering, vol. 145(1), pp. 35–39 (1998)
Dahll, G.: Safety Assessment of Software Based Systems. In: SAFECOMP - The International Conference on Computer Safety, Reliability and Security, pp. 14–24. Springer, Heidelberg (1997)
Boehm, B.W.: Software engineering economics. IEEE Transitional on Software Engineering 10(1), 7–19 (1984)
Jensen, F.: An Introduction to Bayesian Network. UCL Press, University College London (1996)
Gran, B.A., Dahll, G., Eisinger, S., Lund, E.J., Norstrm, J.G., Strocka, P., Ystanes, B.J.: Estimating Dependability of Programmable Systems Using BBNs. In: Koornneef, F., van der Meulen, M.J.P. (eds.) SAFECOMP 2000. LNCS, vol. 1943, pp. 309–320. Springer, Heidelberg (2000)
Gran, B.A.: The use of Bayesian Belief Networks for combining disparate sources of information in the safety assessment of software based systems. Thesis 2002:35, NTNU, Trondheim, Norway (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)
Gran, B.A., Helminen, A.: A Bayesian Belief Network for Reliability Assessment. In: Voges, U. (ed.) SAFECOMP 2001. LNCS, vol. 2187, pp. 35–45. Springer, Heidelberg (2001)
Bishop, P.G., Esp, D.G., Barnes, M., Humphreys, P., Dahll, G.: PODSA project on diverse software. IEEE Trans. Softw. Eng. 12(9), 929–940 (1986)
Märtz, J., Lindner, A., Miedl, H.: Complexity Measurement of Software in Digital I&C-Systems. In: Sixth American Nuclear Society Int. Topic Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies. NPIC&HMIT 2009, Knoxville Tennessee (2009)m American Nuclear Society, LaGrange Park (2009)
Lyu, M.R.: Handbook of Software Reliability Engineering, pp. 699–705. IEEE Computer Society Press, McGraw-Hill (1996)
Lyu, M.R.: Handbook of Software Reliability Engineering, pp. 41–43. IEEE Computer Society Press, McGraw-Hill (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Simensen, J.E., Gerst, C., Gran, B.A., Märtz, J., Miedl, H. (2009). Establishing the Correlation between Complexity and a Reliability Metric for Software Digital I&C-Systems. In: Buth, B., Rabe, G., Seyfarth, T. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2009. Lecture Notes in Computer Science, vol 5775. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04468-7_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-04468-7_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04467-0
Online ISBN: 978-3-642-04468-7
eBook Packages: Computer ScienceComputer Science (R0)