Статии с изисквания за обществен достъп - Mayur NaikНаучете повече
Налице някъде: 42
Hoppity: Learning graph transformations to detect and fix bugs in programs
E Dinella, H Dai, Z Li, M Naik, L Song, K Wang
Proceedings of the International Conference on Learning Representations …, 2020
Изисквания: US National Science Foundation, US Department of Defense
Learning loop invariants for program verification
X Si, H Dai, M Raghothaman, M Naik, L Song
Advances in Neural Information Processing Systems, 7751-7762, 2018
Изисквания: US National Science Foundation, US Department of Defense
Effective program debloating via reinforcement learning
K Heo, W Lee, P Pashakhanloo, M Naik
Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications …, 2018
Изисквания: US National Science Foundation, US Department of Defense
Accelerating search-based program synthesis using learned probabilistic models
W Lee, K Heo, R Alur, M Naik
Proceedings of the 39th ACM SIGPLAN Conference on Programming Language …, 2018
Изисквания: US National Science Foundation, US Department of Defense
On abstraction refinement for program analyses in Datalog
X Zhang, R Mangal, R Grigore, M Naik, H Yang
ACM SIGPLAN Notices 49 (6), 239-248, 2014
Изисквания: UK Engineering and Physical Sciences Research Council
APISan: Sanitizing API usages through semantic cross-checking
I Yun, C Min, X Si, Y Jang, T Kim, M Naik
USENIX Security Symposium, 363-378, 2016
Изисквания: US National Science Foundation
Scallop: From probabilistic deductive databases to scalable differentiable reasoning
J Huang, Z Li, B Chen, K Samel, M Naik, L Song, X Si
Advances in Neural Information Processing Systems 34, 25134-25145, 2021
Изисквания: US National Science Foundation, US Department of Defense
Syntax-guided synthesis of Datalog programs
X Si, W Lee, R Zhang, A Albarghouthi, P Koutris, M Naik
Proceedings of the ACM Joint European Software Engineering Conference and …, 2018
Изисквания: US National Science Foundation, US Department of Defense
Provenance-guided synthesis of Datalog programs
M Raghothaman, J Mendelson, D Zhao, B Scholz, M Naik
Technical report, 2019
Изисквания: US National Science Foundation, US Department of Defense, Australian …
User-guided program reasoning using Bayesian inference
M Raghothaman, S Kulkarni, K Heo, M Naik
Proceedings of the 39th ACM SIGPLAN Conference on Programming Language …, 2018
Изисквания: US National Science Foundation, US Department of Defense
Code2inv: A deep learning framework for program verification
X Si, A Naik, H Dai, M Naik, L Song
Computer Aided Verification: 32nd International Conference, CAV 2020, Los …, 2020
Изисквания: US National Science Foundation, US Department of Defense
Constraint-based synthesis of Datalog programs
A Albarghouthi, P Koutris, M Naik, C Smith
International Conference on Principles and Practice of Constraint …, 2017
Изисквания: US National Science Foundation
Hybrid top-down and bottom-up interprocedural analysis
X Zhang, R Mangal, M Naik, H Yang
ACM SIGPLAN Notices 49 (6), 249-258, 2014
Изисквания: UK Engineering and Physical Sciences Research Council
Learning a meta-solver for syntax-guided program synthesis
X Si, Y Yang, H Dai, M Naik, L Song
Изисквания: US National Science Foundation
Finding optimum abstractions in parametric dataflow analysis
X Zhang, M Naik, H Yang
ACM SIGPLAN Notices 48 (6), 365-376, 2013
Изисквания: UK Engineering and Physical Sciences Research Council
Learning neurosymbolic generative models via program synthesis
H Young, O Bastani, M Naik
arXiv preprint arXiv:1901.08565, 2019
Изисквания: US National Science Foundation
Effective interactive resolution of static analysis alarms
X Zhang, R Grigore, X Si, M Naik
Proceedings of the ACM on Programming Languages 1 (OOPSLA), 57, 2017
Изисквания: US National Science Foundation, US Department of Defense
Scallop: A language for neurosymbolic programming
Z Li, J Huang, M Naik
Proceedings of the ACM on Programming Languages 7 (PLDI), 1463-1487, 2023
Изисквания: US National Science Foundation, US Department of Defense
Arbitrar: User-guided API misuse detection
Z Li, A Machiry, B Chen, M Naik, K Wang, L Song
2021 IEEE Symposium on Security and Privacy (SP), 1400-1415, 2021
Изисквания: US National Science Foundation, US Department of Defense
Accelerating program analyses by cross-program training
S Kulkarni, R Mangal, X Zhang, M Naik
ACM SIGPLAN Notices 51 (10), 359-377, 2016
Изисквания: US National Science Foundation
Информацията за публикацията и осигуреното финансиране се определя автоматично от компютърна програма