Securify: Practical security analysis of smart contracts P Tsankov, A Dan, D Drachsler-Cohen, A Gervais, F Buenzli, M Vechev ACM CCS 2018, 2018 | 1009 | 2018 |
Ai2: Safety and robustness certification of neural networks with abstract interpretation T Gehr, M Mirman, D Drachsler-Cohen, P Tsankov, S Chaudhuri, ... IEEE Symposium on Security and Privacy (SP) 2018, 2018 | 1000 | 2018 |
Code completion with statistical language models V Raychev, M Vechev, E Yahav ACM PLDI 2014, 2014 | 789 | 2014 |
An abstract domain for certifying neural networks G Singh, T Gehr, M Püschel, M Vechev ACM POPL 2019, 2019 | 751 | 2019 |
Differentiable abstract interpretation for provably robust neural networks M Mirman, T Gehr, M Vechev ICML 2018, 2018 | 569 | 2018 |
Fast and Effective Robustness Certification G Singh, T Gehr, M Mirman, M Püschel, MT Vechev NeurIPS 2018, 2018 | 557 | 2018 |
Predicting program properties from" big code" V Raychev, M Vechev, A Krause ACM POPL 2015, 2015 | 502 | 2015 |
Probabilistic model for code with decision trees V Raychev, P Bielik, M Vechev Proceedings of the 2016 ACM international conference on Object oriented …, 2016 | 280 | 2016 |
Verx: Safety verification of smart contracts A Permenev, D Dimitrov, P Tsankov, D Drachsler-Cohen, M Vechev 2020 IEEE symposium on security and privacy (SP), 1661-1677, 2020 | 276 | 2020 |
PHOG: probabilistic model for code P Bielik, V Raychev, M Vechev ICML 2016, 0 | 255* | |
Boosting Robustness Certification of Neural Networks G Singh, T Gehr, M Püschel, MT Vechev ICLR 2019, 2019 | 234* | 2019 |
Learning to fuzz from symbolic execution with application to smart contracts J He, M Balunović, N Ambroladze, P Tsankov, M Vechev Proceedings of the 2019 ACM SIGSAC conference on computer and communications …, 2019 | 227 | 2019 |
Beyond the single neuron convex barrier for neural network certification G Singh, R Ganvir, M Püschel, M Vechev Advances in Neural Information Processing Systems 32, 2019 | 202 | 2019 |
Learning programs from noisy data V Raychev, P Bielik, M Vechev, A Krause ACM POPL 2016, 2016 | 190 | 2016 |
Abstraction-guided synthesis of synchronization M Vechev, E Yahav, G Yorsh ACM POPL 2010, 2010 | 181 | 2010 |
DL2: training and querying neural networks with logic M Fischer, M Balunovic, D Drachsler-Cohen, T Gehr, C Zhang, M Vechev International Conference on Machine Learning, 1931-1941, 2019 | 173 | 2019 |
PSI: Exact Symbolic Inference for Probabilistic Programs T Gehr, S Misailovic, M Vechev Computer Aided Verification: 28th International Conference, CAV 2016 …, 2016 | 171 | 2016 |
Adversarial training and provable defenses: Bridging the gap M Balunovic, M Vechev ICLR 2020, 0 | 171* | |
Laws of order: expensive synchronization in concurrent algorithms cannot be eliminated H Attiya, R Guerraoui, D Hendler, P Kuznetsov, MM Michael, M Vechev ACM POPL 2011, 2011 | 168 | 2011 |
Effective race detection for event-driven programs V Raychev, M Vechev, M Sridharan ACM OOPSLA 2013, 2013 | 166 | 2013 |