| A lean approach to building valid model-based safety arguments T Viger, L Murphy, A Di Sandro, R Shahin, M Chechik 2021 ACM/IEEE 24th International Conference on Model Driven Engineering …, 2021 | 7 | 2021 |
| The ForeMoSt approach to building valid model-based safety arguments T Viger, L Murphy, A Di Sandro, C Menghi, R Shahin, M Chechik Software and Systems Modeling 22 (5), 1473-1494, 2023 | 5 | 2023 |
| Validating safety arguments with lean L Murphy, T Viger, AD Sandro, R Shahin, M Chechik Software Engineering and Formal Methods: 19th International Conference, SEFM …, 2021 | 4 | 2021 |
| Supporting Assurance Case Development Using Generative AI T Viger, L Murphy, S Diemert, C Menghi, A Di, M Chechik SAFECOMP 2023, Position Paper, 2023 | 3 | 2023 |
| A Survey on Deep Learning for Theorem Proving Z Li, J Sun, L Murphy, Q Su, Z Li, X Zhang, K Yang, X Si arXiv preprint arXiv:2404.09939, 2024 | | 2024 |
| MMINT-A: A framework for model-based safety assurance A Di Sandro, L Murphy, T Viger, M Chechik Science of Computer Programming 231, 103004, 2024 | | 2024 |
| Reusing Your Favourite Analysis Framework to Handle Workflows of Product Line Models L Murphy, A Di Sandro, R Shahin, M Chechik Proceedings of the 27th ACM International Systems and Software Product Line …, 2023 | | 2023 |
Marsha ChechikProfessor of Computer Science, University of TorontoDirección de correo verificada de cs.toronto.edu
