Abstract
Increasingly, high-assurance applications rely on dynamically adaptive systems (DASs) to respond to environmental changes, while satisfying functional requirements and non-functional preferences. Examples include critical infrastructure protection and transportation systems. A DAS comprises a collection of (non-adaptive) target systems (represented as UML models) and a set of adaptations that realize transitions among target systems. Two sources of uncertainty inherent to DASs are: (1) predicting the future execution environment, and (2) using functional and non-functional trade-offs to respond to the changing environment. To address this uncertainty, we are inspired by living organisms that are astonishingly adept at adapting to changing environmental conditions using evolution. In this paper, we describe a digital evolution-based approach to generating models that represent possible target systems suitable for different environmental conditions, enabling the developer to identify the functional and non-functional trade-offs between the models, and then assisting the developer in selecting target systems for the DAS.
This work has been supported in part by NSF grants EIA-0000433, CNS-0551622, CCF-0541131, IIP-0700329, CCF-0750787, Department of the Navy, Office of Naval Research under Grant No. N00014-01-1-0744, Siemens Corporate Research,and a Quality Fund Program grant from Michigan State University.
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References
Schmidt, D.C.: Model-Driven Engineering. IEEE Computer 39(2) (2006)
McKinley, P., Cheng, B.H., Ofria, C., Knoester, D., Beckmann, B., Goldsby, H.: Harnessing digital evolution. IEEE Computer 41(1), 54–63 (2008)
Goldsby, H.J., Cheng, B.H.C.: An automated approach to detecting unwanted latent behavior in models of high assurance systems. Technical report, Michigan State University (May 2008) (submitted for publication)
Garlan, D., Cheng, S.W., Huang, A.C., Schmerl, B., Steenkiste, P.: Rainbow: Architecture-based self-adaptation with reusable infrastructure. Computer 37(10), 46–54 (2004)
Gorlick, M.M., Razouk, R.R.: Using weaves for software construction and analysis. In: ICSE 1991: Proceedings of the 13th International Conference on Software Engineering, pp. 23–34. IEEE Computer Society Press, Los Alamitos (1991)
Magee, J., Dulay, N., Eisenbach, S., Kramer, J.: Specifying Distributed Software Architectures. In: Schafer, W., Botella, P. (eds.) ESEC 1995. LNCS, vol. 989, pp. 137–153. Springer, Heidelberg (1995)
Noppen, J., van den Broek, P., Aksit, M.: Software development with imperfect information. Soft Computing 12, 3–28 (2008)
Yen, J., Lee, J.: Fuzzy logic as a basis for specifying imprecise requirements. In: Second IEEE International Conference on Fuzzy Systems (1993)
Whittle, J., Jayaraman, P.K.: Generating hierarchical state machines from use case charts. In: 14th IEEE International Requirements Engineering Conference (RE 2006), Washington, DC, USA, pp. 16–25 (2006)
Harel, D., Kugler, H., Pnueli, A.: Synthesis revisited: Generating statechart models from scenario-based requirements. In: Formal Methods in Software and Systems Modeling (2005)
Uchitel, S., Brunet, G., Chechik, M.: Behaviour model synthesis from properties and scenarios. In: ICSE 2007: Proceedings of the 29th International Conference on Software Engineering, pp. 34–43 (2007)
Jobstmann, B., Bloem, R.: Optimizations for LTL synthesis. In: FMCAD 2006: Proceedings of the Formal Methods in Computer Aided Design (2006)
Ofria, C., Wilke, C.O.: Avida: A software platform for research in computational evolutionary biology. Journal of Artificial Life 10, 191–229, International Society of Artificial Life (ISAL) (2004)
Hughes, D., Greenwood, P., Coulson, G., Blair, G., Pappenberger, F., Smith, P., Beven, K.: An intelligent and adaptable flood monitoring and warning system. In: Proceedings of the 5th UK E-Science All Hands Meeting (AHM) (2006)
Zhang, J., Cheng, B.H.C.: Model-based development of dynamically adaptive software. In: ICSE 2006: Proceeding of the 28th International Conference on Software Engineering, pp. 371–380 (2006) (Best Paper Award)
Goldsby, H.J., Cheng, B.H.C., McKinley, P.K., Knoester, D.B., Ofria, C.A.: Digital evolution of behavioral models for autonomic systems. In: Proceedings of the 5th International Conference on Autonomic Computing (ICAC 2008), Chicago, Illinois (June 2008) (Best Paper Award)
Konrad, S., Cheng, B.H.C.: Facilitating the construction of specification pattern-based properties. In: Proceedings of the IEEE International Requirements Engineering Conference (RE 2005), Paris, France (August 2005)
Cheng, S.W., Garlan, D., Schmerl, B.: Architecture-based self-adaptation in the presence of multiple objectives. In: ICSE 2006 Workshop on Software Engineering for Adaptive and Self-Managing Systems, Shanghai, China (May 2006)
Dwyer, M.B., Avrunin, G.S., Corbett, J.C.: Patterns in property specifications for finite-state verification. In: Proceedings of the 21st International Conference on Software Engineering, pp. 411–420 (1999)
McUmber, W.E., Cheng, B.H.C.: A general framework for formalizing UML with formal languages. In: Proceedings of the IEEE International Conference on Software Engineering (ICSE 2001), Toronto, Canada (May 2001)
Holzmann, G.: The Spin Model Checker, Primer and Reference Manual. Addison-Wesley, Reading (2004)
Zhang, J., Yang, Z., Cheng, B.H., McKinley, P.K.: Adding safeness to dynamic adaptation techniques. In: Proceedings of ICSE 2004 Workshop on Architecting Dependable Systems, Edinburgh, Scotland, UK (May 2004)
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Goldsby, H.J., Cheng, B.H.C. (2008). Automatically Generating Behavioral Models of Adaptive Systems to Address Uncertainty. In: Czarnecki, K., Ober, I., Bruel, JM., Uhl, A., Völter, M. (eds) Model Driven Engineering Languages and Systems. MODELS 2008. Lecture Notes in Computer Science, vol 5301. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87875-9_40
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