Abstract
This paper proposes a method in which to formally specify the design and reliability criteria of an advisory system for use within mission-critical contexts. This is motivated by increasing demands from industry to employ automated decision-support tools capable of operating as highly reliable applications under strict conditions. The proposed method applies the user requirements and design concept of the advisory system to define an abstract architecture. A Markov reliability model and real-time scheduling model are used to effectively capture the operational constraints of the system and are incorporated to the abstract architectural design to define an architectural model. These constraints describe component relationships, data flow and dependencies and execution deadlines of each component. This model is then expressed and proven using SPARK. It was found that the approach useful in simplifying the design process for reliable advisory systems, as well as effectively providing a good basis of a formal specification.
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References
Beemer, B.A., Gregg, D.G.: Advisory systems to support decision making. In: Handbook on Decision Support Systems 1: Basic Themes, 2007, chapt. 24, pp. 361–377. Springer (2007)
Fensel, D., Groenboom, R.: A software architecture for knowledge-based systems. Knowl. Eng. Rev. 14(2), 153–173 (1999)
Dunkel, J., Bruns, R.: Software architecture of advisory systems using agent and semantic web technologies. In: Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2005), pp. 418–421 (2005)
ElAlfi, A.E.E., ElAlami, M.E.: Intelligent advisory system for supporting university managers in law. Int. J. Comput. Sci. Inf. Secur. (IJCSIS) 3(1), 123–128 (2009)
Chu, S.C.W., Ng, H.S., Lam, K.P.: Intelligent trading advisor. In: Proceedings of the 2000 IEEE International Conference on Management of Innovation Technology, pp. 53–58 (2000)
Kassim, J.M., Abdullah, R.: Advisory system architecture in agricultural environment to support decision making process. In: 2nd International Conference on Digital Information and Communication Technology and its Applications, pp. 453–456 (2012)
Mburu, C., Lee, H., Mbogho, A.: E-Health advisory system for HIV/AIDS patients in South Africa. In: 7th International Conference on Appropriate Healthcare Technologies for Developing Countries, IET, pp. 1–4 (2012)
Engrand, P., Mitchell, T., Fowler, T., Melichar, T.: The development of a dvisory systems for shuttle slight computer systems at the kennedy space center. In: IEEE International Conference on Systems, Man and Cybernetics Conference Proceedings 1991, vol. 3, pp. 1685–1690 (1991)
Sadek, A.W.: Artificial Intelligence Applications in Trans portation. Artificial Intelligence in Transportation: Information for Application, Transportation Research Circular, No. E -C113, Transportation Research Board of the National Academies, pp. 1–6 (2007)
Spring, G.: Knowledge-based systems in transportation. Artificial Intelligence in Transportation: Information for Application, Transportation Research Circular, No. E-C113, Transportation Research Board of the National Academies, 2007, pp. 7–16 (2007)
Martin, L.J.: Predictive reasoning and machine learning for the enhancement of reliability in railway systems. In: Lecomte, T., Pinger, R., Romanovsky, A. (eds.) RSSRail 2016. LNCS, vol. 9707, pp. 178–188. Springer, Heidelberg (2016). doi:10.1007/978-3-319-33951-1_13
Ayel, M., Laurent, J.P.: Validation, verification and test of knowledge-based systems. IEEE Trans. Knowl. Data Eng. 11(1), 292–312 (1999)
Serrano, J.A.: Formal specifications of software design methods. In: IW-FM 1999 Proceedings of the 3rd Irish Conference on Formal Methods, British Computer Society, Swindon, UK, pp. 208–224 (1999)
Meseguer, P., Preece, A.D.: Verification and validation of knowledge-based systems with formal specifications. Knowl. Eng. Rev. 4(1) (1995)
Antoniou, G., van Harmelen, F., Plant, R., Vanthienen, J.: Verification and validation of knowledge-based systems. AI Mag. 19(3), 123–126 (1998)
Tsai, W.T., Vishnuvajjala, R., Zhang, D.: Verification and validation of knowledge-based systems. IEEE Trans. Knowl. Data Eng. 11(1), 202–212 (1999)
Kitchin, J.F.: Practical markov modelling for reliability analysis. In: Proceedings of the Annual Reliability and Maintainability Symposium, pp. 290–296 (1988)
Wang, W.L., Pan, D., Chen, M.H.: Architecture-based software reliability modeling. J. Syst. Softw. 79(1), 132–146 (2006)
de Magalhães, A.J.P., Costa, C.J.A.: Real-Time Scheduling Models. Technical report, Controlo 2000, 4th Portuguese Conference on Automatic Control (2000)
Dross, C., Efstathopoulos, P., Lesens, D., Mentré, D., Moy, Y.: Rail, space, security: three case studies for SPARK 2014. In: Proceedings of the ERTS (2014)
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Martin, L.J.W., Romanovsky, A. (2016). A Formal Approach to Designing Reliable Advisory Systems. In: Crnkovic, I., Troubitsyna, E. (eds) Software Engineering for Resilient Systems. SERENE 2016. Lecture Notes in Computer Science(), vol 9823. Springer, Cham. https://doi.org/10.1007/978-3-319-45892-2_3
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DOI: https://doi.org/10.1007/978-3-319-45892-2_3
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