| Code completion with statistical language models V Raychev, M Vechev, E Yahav Proceedings of the 35th ACM SIGPLAN Conference on Programming Language …, 2014 | 459 | 2014 |
| Ai2: Safety and robustness certification of neural networks with abstract interpretation T Gehr, M Mirman, D Drachsler-Cohen, P Tsankov, S Chaudhuri, ... 2018 IEEE Symposium on Security and Privacy (SP), 3-18, 2018 | 365 | 2018 |
| Predicting program properties from" big code" V Raychev, M Vechev, A Krause ACM Symposium on Principles of Programming Languages 50 (1), 111-124, 2015 | 315 | 2015 |
| Securify: Practical security analysis of smart contracts P Tsankov, A Dan, D Drachsler-Cohen, A Gervais, F Buenzli, M Vechev Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications …, 2018 | 305 | 2018 |
| Differentiable abstract interpretation for provably robust neural networks M Mirman, T Gehr, M Vechev International Conference on Machine Learning, 3578-3586, 2018 | 224 | 2018 |
| An abstract domain for certifying neural networks G Singh, T Gehr, M Püschel, M Vechev ACM Symposium on Principles of Programming Languages 3 (POPL), 1-30, 2019 | 161 | 2019 |
| Fast and Effective Robustness Certification. G Singh, T Gehr, M Mirman, M Püschel, MT Vechev NeurIPS 1 (4), 6, 2018 | 159 | 2018 |
| Abstraction-guided synthesis of synchronization M Vechev, E Yahav, G Yorsh ACM Symposium on Principles of Programming Languages 45 (1), 327-338, 2010 | 153 | 2010 |
| Laws of order: expensive synchronization in concurrent algorithms cannot be eliminated H Attiya, R Guerraoui, D Hendler, P Kuznetsov, MM Michael, M Vechev ACM Symposium on Principles of Programming Languages 46 (1), 487-498, 2011 | 143 | 2011 |
| QVM: An efficient runtime for detecting defects in deployed systems M Arnold, M Vechev, E Yahav Proceedings of the 2008 ACM SIGPLAN International Conference on Object …, 2008 | 139 | 2008 |
| Automatic inference of memory fences M Kuperstein, M Vechev, E Yahav Formal Methods in Computer-Aided Design (FMCAD), 2010, 111-119, 2010 | 136 | 2010 |
| Effective race detection for event-driven programs V Raychev, M Vechev, M Sridharan Proceedings of the 2013 ACM SIGPLAN international conference on Object …, 2013 | 130 | 2013 |
| PHOG: probabilistic model for code P Bielik, V Raychev, M Vechev International Conference on Machine Learning, 2933-2942, 2016 | 127 | 2016 |
| Idempotent work stealing MM Michael, MT Vechev, VA Saraswat ACM SIGPLAN Notices 44 (4), 45-54, 2009 | 124 | 2009 |
| Chameleon: adaptive selection of collections O Shacham, M Vechev, E Yahav ACM Programming Languages Design and Implementation 44 (6), 408-418, 2009 | 119 | 2009 |
| Learning programs from noisy data V Raychev, P Bielik, M Vechev, A Krause ACM Symposium on Principles of Programming Languages 51 (1), 761-774, 2016 | 117 | 2016 |
| Deriving fine-grained concurrent linearizable objects MT Vechev, E Yahav ACM Programming Languages Design and Implementation, 2008 | 116* | 2008 |
| Race detection for web applications B Petrov, M Vechev, M Sridharan, J Dolby ACM Programming Languages Design and Implementation 47 (6), 251-262, 2012 | 110 | 2012 |
| Scalable and precise dynamic datarace detection for structured parallelism R Raman, J Zhao, V Sarkar, M Vechev, E Yahav ACM Programming Languages Design and Implementation 47 (6), 531-542, 2012 | 107 | 2012 |
| Practical concurrent binary search trees via logical ordering D Drachsler, M Vechev, E Yahav Proceedings of the 19th ACM SIGPLAN symposium on Principles and practice of …, 2014 | 97 | 2014 |
Eran YahavTechnion, IsraelVerified email at cs.technion.ac.il
