Liang, J. H. (2018). Machine Learning for SAT Solvers. Waterloo, ON, Canada. Retrieved from http://hdl.handle.net/10012/14207 (Original work published 2018)
Publications
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Juodisius, P. ., Sarkar, A. ., Mukkamala, R. R., Antkiewicz, M. ., Czarnecki, K. ., & Wąsowski, A. . (2018). Clafer: Lightweight Modeling of Structure and Behaviour. The Art, Science, and Engineering of Programming Journal, 3. https://doi.org/10.22152/programming-journal.org/2019/3/2 (Original work published 2018)
Zhang, Z. ., Ernst, G. ., Sedwards, S. ., Arcani, P. ., & Hasuo, I. . (2018). Two-Layered Falsification of Hybrid Systems Guided by Monte Carlo Tree Search. IEEE TCAD. Torino, Italy: IEEE. Retrieved from https://ieeexplore.ieee.org/document/8418450
Colwell, I. . (2018). Runtime Restriction of the Operational Design Domain: A Safety Concept for Automated Vehicles. Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/13398 (Original work published 2018)
Zayan, D. ., Sarkar, A. ., Antkiewicz, M. ., Maciel, R. S. P., & Czarnecki, K. . (2018). Example-driven modeling: on effects of using examples on structural model comprehension, what makes them useful, and how to create them. https://doi.org/10.1007/s10270-017-0652-3 (Original work published 2018)
Zulkoski, E. . (2018). Understanding and Enhancing CDCL-based SAT Solvers. Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/13525 (Original work published 2018)
Budde, C. ., D’Argenio, P. ., Hartmanns, A. ., & Sedwards, S. . (2018). A Statistical Model Checker for Nondeterminism and Rare Events. Retrieved from https://link.springer.com/chapter/10.1007/978-3-319-89963-3_20
Given-Wilson, T. ., Legay, A. ., Sedwards, S. ., & Zendra, O. . (2018). Group abstraction for assisted navigation of social activities in intelligent environments. Springer Journal of Reliable Intelligent Environments, 4, 107\textendash120. Retrieved from https://link.springer.com/article/10.1007/s40860-018-0058-1
Angus, M. ., ElBalkini, M. ., Khan, S. ., Harakeh, A. ., Andrienko, O. ., Reading, C. ., Czarnecki, K. ., & Waslander, S. . (2018). Unlimited Road-scene Synthetic Annotation (URSA) Dataset. Unlimited Road-Scene Synthetic Annotation (URSA) Dataset. Presented at the. Maui, Hawaii, USA: IEEE. Retrieved from https://arxiv.org/abs/1807.06056 (Original work published 2018)
Colwell, I. ., Phan, B. T., Saleem, S. ., Salay, R. ., & Czarnecki, K. . (2018). An Automated Vehicle Safety Concept Based on Runtime Restriction of the Operational Design Domain. An Automated Vehicle Safety Concept Based on Runtime Restriction of the Operational Design Domain. Presented at the.