Abstract
Cyber-Physical Systems (CPS) are software and hardware systems that interact with the physical environment. Many CPSs have useful lifetimes measured in decades. This leads to unique concerns regarding security and longevity of software designed for CPSs which are exacerbated by the need for CPSs to adapt to ecosystem changes if they are to remain functional over extended periods. In particular, the software in long-lifetime CPSs must adapt to unanticipated trends in environmental conditions, aging effects on mechanical systems, and component upgrades and modifications. This paper presents the Toolkit for Evolving Ecosystem Envelopes (TEEE) system created to help address these challenges in CPSs. TEEE is able to detect environmental changes which have caused errors within the CPS without directly sensing the environmental change. TEEE uses dynamic profiling to detect the errors within the CPS, determine the root cause of the error, alert the user, and suggest a possible adaption.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
In one of the authors person experience, we once came across some donated defibrillators none of which had batteries. While the defibrillators are designed to still function without a battery (slightly slower charge build up), they were clearly never intended to be used this way as one of steps in the daily self test required the presence of a battery despite the battery itself not being present in the test. Luckily, we were able to find an alternate method of ensuring proper functionality.
References
Adjepon-Yamoah, D.E.: cloud-ATAM: method for analysing resilient attributes of cloud-based architectures. In: Crnkovic, I., Troubitsyna, E. (eds.) SERENE 2016. LNCS, vol. 9823, pp. 105–114. Springer, Cham (2016). doi:10.1007/978-3-319-45892-2_8
Arafeen, M.J., Do, H.: Test case prioritization using requirements-based clustering. In: 2013 IEEE Sixth International Conference on Software Testing, Verification and Validation (ICST), pp. 312–321. IEEE (2013)
Chen, Y., Probert, R.L., Sims, D.P.: Specification-based regression test selection with risk analysis. In: Proceedings of the 2002 Conference of the Centre for Advanced Studies on Collaborative Research, p. 1. IBM Press (2002)
Chlipala, A.: Certified Programming with Dependent Types: A Pragmatic Introduction to the Coq Proof Assistant. MIT Press, Cambridge (2013)
Cohen, D.M., Dalal, S.R., Fredman, M.L., Patton, G.C.: The AETG system: an approach to testing based on combinatorial design. IEEE Trans. Softw. Eng. 23(7), 437–444 (1997)
Dreossi, T., Donzé, A., Seshia, S.A.: Compositional falsification of cyber-physical systems with machine learning components. In: Barrett, C., Davies, M., Kahsai, T. (eds.) NFM 2017. LNCS, vol. 10227, pp. 357–372. Springer, Cham (2017). doi:10.1007/978-3-319-57288-8_26
Feiler, P., Lewis, B., Vestal, S.: The SAE avionics architecture description language (AADL) standard: a basis for model-based architecture-driven embedded systems. In: Real-Time Applications Symposium Workshop on Model-Driven Embedded Systems (2003)
Feiler, P.H., Gluch, D.P., Hudak, J.J.: The architecture analysis & design language (AADL): an introduction. Technical report, DTIC Document (2006)
Grindal, M., Lindström, B., Offutt, J., Andler, S.F.: An evaluation of combination strategies for test case selection. Empir. Softw. Eng. 11(4), 583–611 (2006)
Hughes, J., Sparks, C., Stoughton, A., Parikh, R., Reuther, A., Jagannathan, S.: Building resource adaptive software systems (brass): objectives and system evaluation. ACM SIGSOFT Softw. Eng. Notes 41(1), 1–2 (2016)
Software Engineering Institute. Open source AADL tool environment (osate). http://la.sei.cmu.edu/aadlinfosite/OpenSourceAADLToolEnvironment.html
Kephart, J.O., Chess, D.M.: The vision of autonomic computing. Computer 36(1), 41–50 (2003)
Larson, B., Hatcliff, J., Fowler, K., Delange, J.: Illustrating the AADL error modeling annex (v. 2) using a simple safety-critical medical device. ACM SIGAda Ada Lett. 33(3), 65–84 (2013)
Le Goues, C., Nguyen, T., Forrest, S., Weimer, W.: Genprog: a generic method for automatic software repair. IEEE Trans. Softw. Eng. 38(1), 54–72 (2012)
Lott, C., Jain, A., Dalal, S.: Modeling requirements for combinatorial software testing. ACM SIGSOFT Softw. Eng. Notes 30, 1–7 (2005). ACM
Mogyorodi, G.: What is requirements-based testing? Technical report, Crosstalk (2003)
Myers, G.J., Sandler, C., Badgett, T.: The Art of Software Testing. Wiley, New York (2011)
Neches, R.: Engineered resilient systems (ers) s&t priority description and roadmap (2011)
Perkins, J.H., Kim, S., Larsen, S., Amarasinghe, S., Bachrach, J., Carbin, M., Pacheco, C., Sherwood, F., Sidiroglou, S., Sullivan, G., et al.: Automatically patching errors in deployed software. In: Proceedings of the ACM SIGOPS 22nd Symposium on Operating Systems Principles, pp. 87–102. ACM (2009)
Qi, Y., Mao, X., Lei, Y.: Efficient automated program repair through fault-recorded testing prioritization. In: 2013 29th IEEE International Conference on Software Maintenance (ICSM), pp. 180–189. IEEE (2013)
Ranganathan, K., Rangarajan, M., Alexander, P., Regan, T.: Automated test vector generation from rosetta requirements. In: VHDL International Users Forum Fall Workshop, Proceedings, pp. 51–58. IEEE (2000)
Rodríguez, R.J., Merseguer, J., Bernardi, S.: Modelling and analysing resilience as a security issue within UML. In: Proceedings of the 2nd International Workshop on Software Engineering for Resilient Systems, pp. 42–51. ACM (2010)
Rugina, A.-E., Kanoun, K., Kaâniche, M.: A system dependability modeling framework using AADL and GSPNs. In: Lemos, R., Gacek, C., Romanovsky, A. (eds.) WADS 2006. LNCS, vol. 4615, pp. 14–38. Springer, Heidelberg (2007). doi:10.1007/978-3-540-74035-3_2
Stoicescu, M., Fabre, J.-C., Roy, M.: Architecting resilient computing systems: overall approach and open issues. In: Troubitsyna, E.A. (ed.) SERENE 2011. LNCS, vol. 6968, pp. 48–62. Springer, Heidelberg (2011). doi:10.1007/978-3-642-24124-6_5
Acknowledgments
This material is based upon work supported by the United States Air Force and DARPA under Contract No. FA8750-16-C-0273. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the United States Air Force or DARPA.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Borck, H. et al. (2017). 100 Years of Software - Adapting Cyber-Physical Systems to the Changing World. In: Romanovsky, A., Troubitsyna, E. (eds) Software Engineering for Resilient Systems. SERENE 2017. Lecture Notes in Computer Science(), vol 10479. Springer, Cham. https://doi.org/10.1007/978-3-319-65948-0_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-65948-0_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-65947-3
Online ISBN: 978-3-319-65948-0
eBook Packages: Computer ScienceComputer Science (R0)