Abstract
Solutions to specific challenges within software engineering activities can greatly benefit from human creativity. For example, evidence of trust derived from creative virtual evaluation scenarios can support the trust assurance of fast-paced runtime adaptation of intelligent behavior. Following this vision, in this paper, we introduce a methodological and architectural concept that interplays creative and social aspects of gaming into software engineering activities, more precisely into a virtual evaluation of system behavior. A particular trait of the introduced concept is that it reinforces cooperation between technological and social intelligence.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Carla Simulator. https://carla.org/. Accessed 04 Dec 2020
FMI. https://fmi-standard.org/. Accessed 06 Dec 2020
Foretellix. https://www.foretellix.com/open-language/. Accessed 12 Dec 2020
Foretellix M-SDL. https://www.foretellix.com/category/m-sdl/. Accessed 12 Dec 2020
LGSVL simulator. https://www.lgsvlsimulator.com/. Accessed 12 Dec 2020
Simulink. https://www.mathworks.com/products/simulink.html. Accessed 02 Dec 2020
Anderson, M.: Prescription-strength gaming: ADHD treatment now comes in the form of a first-person racing game-[News]. IEEE Spectr. 57(8), 9–10 (2020)
Bolte, J., Bar, A., Lipinski, D., Fingscheidt, T.: Towards corner case detection for autonomous driving. In: 2019 IEEE Intelligent Vehicles Symposium (IV), pp. 438–445 (2019). https://doi.org/10.1109/IVS.2019.8813817
Cioroaica, E., et al.: Towards creation of automated prediction systems for trust and dependability evaluation. In: 2020 International Conference on Software, Telecommunications and Computer Networks (SoftCOM), pp. 1–6. IEEE (2020)
Cioroaica, E., Kuhn, T., Bauer, T.: Prototyping automotive smart ecosystems. In: 2018 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W). IEEE (2018)
Cioroaica, E., Kuhn, T., Buhnova, B.: (Do not) trust in ecosystems. In: Proceedings of the 41st International Conference on Software Engineering: New Ideas and Emerging Results, pp. 9–12. IEEE Press (2019)
Huang, M.H., Rust, R., Maksimovic, V.: The feeling economy: managing in the next generation of artificial intelligence (AI). Calif. Manag. Rev. 61(4), 43–65 (2019)
Jia, Y., Harman, M.: An analysis and survey of the development of mutation testing. IEEE Trans. Softw. Eng. 37(5), 649–678 (2011). https://doi.org/10.1109/TSE.2010.62. Sept
Kuhn, T., Forster, T., Braun, T., Gotzhein, R.: FERAL-framework for simulator coupling on requirements and architecture level. In: 2013 Eleventh IEEE/ACM International Conference on Formal Methods and Models for Codesign (MEMOCODE), pp. 11–22. IEEE (2013)
Riccio, V., Jahangirova, G., Stocco, A., Humbatova, N., Weiss, M., Tonella, P.: Testing machine learning based systems: a systematic mapping. Empir. Softw. Eng. 25(6), 5193–5254 (2020). https://doi.org/10.1007/s10664-020-09881-0
Sullivan, D.P., et al.: Deep learning is combined with massive-scale citizen science to improve large-scale image classification. Nat. Biotechnol. 36(9), 820–828 (2018)
Tian, Y., Pei, K., Jana, S., Ray, B.: DeepTest: automated testing of deep-neural-network-driven autonomous cars. In: Proceedings of the 40th International Conference on Software Engineering, pp. 303–314 (2018)
Xin, K., Zhang, S., Wu, X., Cai, W.: Reciprocal crowdsourcing: building cooperative game worlds on blockchain. In: 2020 IEEE International Conference on Consumer Electronics (ICCE), pp. 1–6. IEEE (2020)
Yang, C., Ye, H.J., Feng, Y.: Using gamification elements for competitive crowdsourcing: exploring the underlying mechanism. Behav. Inf. Technol. 40(9), 837–854 (2021)
Acknowledgment
This work is co-funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 952702 (BIECO) and by ERDF “CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence” (No. CZ.02.1.01/0.0/0.0/16_019/0000822).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Cioroaica, E., Buhnova, B., Marchetti, E., Schneider, D., Kuhn, T. (2021). Bridging Trust in Runtime Open Evaluation Scenarios. In: Bellatreche, L., Chernishev, G., Corral, A., Ouchani, S., Vain, J. (eds) Advances in Model and Data Engineering in the Digitalization Era. MEDI 2021. Communications in Computer and Information Science, vol 1481. Springer, Cham. https://doi.org/10.1007/978-3-030-87657-9_9
Download citation
DOI: https://doi.org/10.1007/978-3-030-87657-9_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-87656-2
Online ISBN: 978-3-030-87657-9
eBook Packages: Computer ScienceComputer Science (R0)