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ORCIDMayur Naik
Person information
- affiliation: University of Pennsylvania, Philadelphia, USA
- affiliation (former): Georgia Institute of Technology, Atlanta GA, USA
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Books and Theses
- 2008
[b1]Mayur Naik:
Effective static race detection for Java. Stanford University, USA, 2008
Journal Articles
- 2023
- [j13]Aalok Thakkar
, Nathaniel Sands, George Petrou, Rajeev Alur, Mayur Naik, Mukund Raghothaman:
Mobius: Synthesizing Relational Queries with Recursive and Invented Predicates. Proc. ACM Program. Lang. 7(OOPSLA2): 1394-1417 (2023) - [j12]Ziyang Li, Jiani Huang, Mayur Naik:
Scallop: A Language for Neurosymbolic Programming. Proc. ACM Program. Lang. 7(PLDI): 1463-1487 (2023) - [j11]Aaditya Naik, Aalok Thakkar, Adam Stein, Rajeev Alur, Mayur Naik:
Relational Query Synthesis ⋈ Decision Tree Learning. Proc. VLDB Endow. 17(2): 250-263 (2023) - [j10]Haoxian Chen, Chenyuan Wu, Andrew Zhao, Mukund Raghothaman, Mayur Naik, Boon Thau Loo:
Synthesizing Formal Network Specifications From Input-Output Examples. IEEE/ACM Trans. Netw. 31(3): 994-1009 (2023) - [j9]Elizabeth Dinella, Todd Mytkowicz, Alexey Svyatkovskiy, Christian Bird, Mayur Naik, Shuvendu K. Lahiri:
DeepMerge: Learning to Merge Programs. IEEE Trans. Software Eng. 49(4): 1599-1614 (2023) - 2020
- [j8]Mukund Raghothaman, Jonathan Mendelson, David Zhao, Mayur Naik, Bernhard Scholz:
Provenance-guided synthesis of Datalog programs. Proc. ACM Program. Lang. 4(POPL): 62:1-62:27 (2020) - 2017
- [j7]Xin Zhang, Radu Grigore, Xujie Si, Mayur Naik:
Effective interactive resolution of static analysis alarms. Proc. ACM Program. Lang. 1(OOPSLA): 57:1-57:30 (2017) - 2015
- [j6]Yongin Kwon, Sangmin Lee, Hayoon Yi, Donghyun Kwon, Seungjun Yang, Byung-Gon Chun, Ling Huang, Petros Maniatis, Mayur Naik, Yunheung Paek:
Mantis: Efficient Predictions of Execution Time, Energy Usage, Memory Usage and Network Usage on Smart Mobile Devices. IEEE Trans. Mob. Comput. 14(10): 2059-2072 (2015) - 2011
- [j5]David Gay, Joel Galenson, Mayur Naik, Kathy Yelick:
Yada: Straightforward parallel programming. Parallel Comput. 37(9): 592-609 (2011) - 2008
- [j4]Mayur Naik, Jens Palsberg:
A type system equivalent to a model checker. ACM Trans. Program. Lang. Syst. 30(5): 29:1-29:24 (2008) - 2004
- [j3]Mayur Naik, Jens Palsberg:
Compiling with code-size constraints. ACM Trans. Embed. Comput. Syst. 3(1): 163-181 (2004) - 2000
- [j2]Mayur Naik, Rajeev Kumar:
Efficient Message Dispatch in Object-Oriented Systems. ACM SIGPLAN Notices 35(3): 49-58 (2000) - 1999
- [j1]Mayur Naik, Rajeev Kumar:
Object-Oriented Symbol Management in Syntax-Directed Compiler Systems. ACM SIGPLAN Notices 34(6): 58-67 (1999)
Conference and Workshop Papers
- 2024
- [c66]Ziyang Li, Jiani Huang, Jason Liu, Felix Zhu, Eric Zhao, William Dodds, Neelay Velingker, Rajeev Alur, Mayur Naik:
Relational Programming with Foundational Models. AAAI 2024: 10635-10644 - 2023
- [c65]Yinjun Wu, Adam Stein, Jacob Gardner, Mayur Naik:
Learning to Select Pivotal Samples for Meta Re-weighting. AAAI 2023: 6128-6136 - [c64]Hanlin Zhang, Jiani Huang, Ziyang Li, Mayur Naik, Eric P. Xing:
Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming. ACL (Findings) 2023: 3062-3077 - [c63]Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong:
Do Machine Learning Models Learn Statistical Rules Inferred from Data? ICML 2023: 25677-25693 - 2022
- [c62]Pardis Pashakhanloo, Aravind Machiry, Hyon-Young Choi, Anthony Canino, Kihong Heo, Insup Lee, Mayur Naik:
PacJam: Securing Dependencies Continuously via Package-Oriented Debloating. AsiaCCS 2022: 903-916 - [c61]Pardis Pashakhanloo, Aaditya Naik, Yuepeng Wang, Hanjun Dai, Petros Maniatis, Mayur Naik:
CodeTrek: Flexible Modeling of Code using an Extensible Relational Representation. ICLR 2022 - 2021
- [c60]Jonathan Mendelson, Aaditya Naik, Mukund Raghothaman, Mayur Naik:
GENSYNTH: Synthesizing Datalog Programs without Language Bias. AAAI 2021: 6444-6453 - [c59]Jiani Huang, Ziyang Li, Binghong Chen, Karan Samel, Mayur Naik, Le Song, Xujie Si:
Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning. NeurIPS 2021: 25134-25145 - [c58]Aalok Thakkar, Aaditya Naik, Nathaniel Sands, Rajeev Alur, Mayur Naik, Mukund Raghothaman:
Example-guided synthesis of relational queries. PLDI 2021: 1110-1125 - [c57]Ziyang Li, Aravind Machiry, Binghong Chen, Mayur Naik, Ke Wang, Le Song:
ARBITRAR: User-Guided API Misuse Detection. SP 2021: 1400-1415 - [c56]Aaditya Naik, Jonathan Mendelson, Nathaniel Sands, Yuepeng Wang, Mayur Naik, Mukund Raghothaman:
Sporq: An Interactive Environment for Exploring Code using Query-by-Example. UIST 2021: 84-99 - 2020
- [c55]Xujie Si, Aaditya Naik, Hanjun Dai, Mayur Naik, Le Song:
Code2Inv: A Deep Learning Framework for Program Verification. CAV (2) 2020: 151-164 - [c54]Elizabeth Dinella, Hanjun Dai, Ziyang Li, Mayur Naik, Le Song, Ke Wang:
Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs. ICLR 2020 - [c53]Jiani Huang, Calvin Smith, Osbert Bastani, Rishabh Singh, Aws Albarghouthi, Mayur Naik:
Generating Programmatic Referring Expressions via Program Synthesis. ICML 2020: 4495-4506 - 2019
- [c52]Xujie Si, Yuan Yang, Hanjun Dai, Mayur Naik, Le Song:
Learning a Meta-Solver for Syntax-Guided Program Synthesis. ICLR (Poster) 2019 - [c51]Halley Young, Osbert Bastani, Mayur Naik:
Learning Neurosymbolic Generative Models via Program synthesis. DeepRLStructPred@ICLR 2019 - [c50]Halley Young, Osbert Bastani, Mayur Naik:
Learning Neurosymbolic Generative Models via Program Synthesis. ICML 2019: 7144-7153 - [c49]Xujie Si, Mukund Raghothaman, Kihong Heo, Mayur Naik:
Synthesizing Datalog Programs using Numerical Relaxation. IJCAI 2019: 6117-6124 - [c48]Kihong Heo, Mukund Raghothaman, Xujie Si, Mayur Naik:
Continuously reasoning about programs using differential Bayesian inference. PLDI 2019: 561-575 - [c47]Mayur Naik:
Rethinking Static Analysis by Combining Discrete and Continuous Reasoning. SAS 2019: 3-16 - 2018
- [c46]Kihong Heo, Woosuk Lee, Pardis Pashakhanloo, Mayur Naik:
Effective Program Debloating via Reinforcement Learning. CCS 2018: 380-394 - [c45]Yan Shoshitaishvili, Mayur Naik:
FEAST'18 - 2018 Workshop on Forming an Ecosystem around Software Transformation. CCS 2018: 2185-2186 - [c44]Xujie Si, Hanjun Dai, Mukund Raghothaman, Mayur Naik, Le Song:
Learning Loop Invariants for Program Verification. NeurIPS 2018: 7762-7773 - [c43]Woosuk Lee, Kihong Heo, Rajeev Alur, Mayur Naik:
Accelerating search-based program synthesis using learned probabilistic models. PLDI 2018: 436-449 - [c42]Mukund Raghothaman, Sulekha Kulkarni, Kihong Heo, Mayur Naik:
User-guided program reasoning using Bayesian inference. PLDI 2018: 722-735 - [c41]Xujie Si, Woosuk Lee, Richard Zhang, Aws Albarghouthi, Paraschos Koutris, Mayur Naik:
Syntax-guided synthesis of Datalog programs. ESEC/SIGSOFT FSE 2018: 515-527 - 2017
- [c40]Xujie Si, Xin Zhang, Radu Grigore, Mayur Naik:
Maximum Satisfiability in Software Analysis: Applications and Techniques. CAV (1) 2017: 68-94 - [c39]Aws Albarghouthi, Paraschos Koutris, Mayur Naik, Calvin Smith:
Constraint-Based Synthesis of Datalog Programs. CP 2017: 689-706 - [c38]Xin Zhang, Xujie Si, Mayur Naik:
Combining the logical and the probabilistic in program analysis. MAPL@PLDI 2017: 27-34 - 2016
- [c37]Ravi Mangal, Xin Zhang, Aditya Kamath, Aditya V. Nori, Mayur Naik:
Scaling Relational Inference Using Proofs and Refutations. AAAI 2016: 3278-3286 - [c36]Xujie Si, Xin Zhang, Vasco M. Manquinho, Mikolás Janota, Alexey Ignatiev, Mayur Naik:
On Incremental Core-Guided MaxSAT Solving. CP 2016: 473-482 - [c35]Sulekha Kulkarni, Ravi Mangal, Xin Zhang, Mayur Naik:
Accelerating program analyses by cross-program training. OOPSLA 2016: 359-377 - [c34]Xin Zhang, Ravi Mangal, Aditya V. Nori, Mayur Naik:
Query-guided maximum satisfiability. POPL 2016: 109-122 - [c33]Insu Yun, Changwoo Min, Xujie Si, Yeongjin Jang, Taesoo Kim, Mayur Naik:
APISan: Sanitizing API Usages through Semantic Cross-Checking. USENIX Security Symposium 2016: 363-378 - 2015
- [c32]Ghila Castelnuovo, Mayur Naik, Noam Rinetzky, Mooly Sagiv, Hongseok Yang:
Modularity in Lattices: A Case Study on the Correspondence Between Top-Down and Bottom-Up Analysis. SAS 2015: 252-274 - [c31]Ravi Mangal, Xin Zhang, Aditya V. Nori, Mayur Naik:
Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances. SAT 2015: 299-306 - [c30]Ravi Mangal, Xin Zhang, Aditya V. Nori, Mayur Naik:
A user-guided approach to program analysis. ESEC/SIGSOFT FSE 2015: 462-473 - [c29]Jongse Park, Hadi Esmaeilzadeh, Xin Zhang, Mayur Naik, William Harris:
FlexJava: language support for safe and modular approximate programming. ESEC/SIGSOFT FSE 2015: 745-757 - 2014
- [c28]Ravi Mangal, Mayur Naik, Hongseok Yang:
A Correspondence between Two Approaches to Interprocedural Analysis in the Presence of Join. ESOP 2014: 513-533 - [c27]Cong Shi, Karim Habak, Pranesh Pandurangan, Mostafa H. Ammar, Mayur Naik, Ellen W. Zegura:
COSMOS: computation offloading as a service for mobile devices. MobiHoc 2014: 287-296 - [c26]Mayur Naik:
Large-scale configurable static analysis. SOAP@PLDI 2014: 7:1 - [c25]Xin Zhang, Ravi Mangal, Radu Grigore, Mayur Naik, Hongseok Yang:
On abstraction refinement for program analyses in Datalog. PLDI 2014: 239-248 - [c24]Xin Zhang, Ravi Mangal, Mayur Naik, Hongseok Yang:
Hybrid top-down and bottom-up interprocedural analysis. PLDI 2014: 249-258 - 2013
- [c23]Xin Zhang, Mayur Naik, Hongseok Yang:
Finding optimum abstractions in parametric dataflow analysis. PLDI 2013: 365-376 - [c22]Aravind Machiry, Rohan Tahiliani, Mayur Naik:
Dynodroid: an input generation system for Android apps. ESEC/SIGSOFT FSE 2013: 224-234 - [c21]Yongin Kwon, Sangmin Lee, Hayoon Yi, Donghyun Kwon, Seungjun Yang, Byung-Gon Chun, Ling Huang, Petros Maniatis, Mayur Naik, Yunheung Paek:
Mantis: Automatic Performance Prediction for Smartphone Applications. USENIX Annual Technical Conference 2013: 297-308 - 2012
- [c20]Mayur Naik, Hongseok Yang, Ghila Castelnuovo, Mooly Sagiv:
Abstractions from tests. POPL 2012: 373-386 - [c19]Cong Shi, Mostafa H. Ammar, Ellen W. Zegura, Mayur Naik:
Computing in cirrus clouds: the challenge of intermittent connectivity. MCC@SIGCOMM 2012: 23-28 - [c18]Saswat Anand, Mayur Naik, Mary Jean Harrold, Hongseok Yang:
Automated concolic testing of smartphone apps. SIGSOFT FSE 2012: 59 - 2011
- [c17]Byung-Gon Chun, Sunghwan Ihm, Petros Maniatis, Mayur Naik, Ashwin Patti:
CloneCloud: elastic execution between mobile device and cloud. EuroSys 2011: 301-314 - [c16]Percy Liang, Mayur Naik:
Scaling abstraction refinement via pruning. PLDI 2011: 590-601 - [c15]Percy Liang, Omer Tripp, Mayur Naik:
Learning minimal abstractions. POPL 2011: 31-42 - 2010
- [c14]Ling Huang, Jinzhu Jia, Bin Yu, Byung-Gon Chun, Petros Maniatis, Mayur Naik:
Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression. NIPS 2010: 883-891 - [c13]Percy Liang, Omer Tripp, Mayur Naik, Mooly Sagiv:
A dynamic evaluation of the precision of static heap abstractions. OOPSLA 2010: 411-427 - [c12]Pallavi Joshi, Mayur Naik, Koushik Sen, David Gay:
An effective dynamic analysis for detecting generalized deadlocks. SIGSOFT FSE 2010: 327-336 - 2009
- [c11]Pallavi Joshi, Mayur Naik, Chang-Seo Park, Koushik Sen:
CalFuzzer: An Extensible Active Testing Framework for Concurrent Programs. CAV 2009: 675-681 - [c10]Mayur Naik, Chang-Seo Park, Koushik Sen, David Gay:
Effective static deadlock detection. ICSE 2009: 386-396 - [c9]Zachary R. Anderson, David Gay, Mayur Naik:
Lightweight annotations for controlling sharing in concurrent data structures. PLDI 2009: 98-109 - [c8]Pallavi Joshi, Chang-Seo Park, Koushik Sen, Mayur Naik:
A randomized dynamic program analysis technique for detecting real deadlocks. PLDI 2009: 110-120 - 2007
- [c7]Mayur Naik, Alex Aiken:
Conditional must not aliasing for static race detection. POPL 2007: 327-338 - 2006
- [c6]Alice X. Zheng, Michael I. Jordan, Ben Liblit, Mayur Naik, Alex Aiken:
Statistical debugging: simultaneous identification of multiple bugs. ICML 2006: 1105-1112 - [c5]Mayur Naik, Alex Aiken, John Whaley:
Effective static race detection for Java. PLDI 2006: 308-319 - 2005
- [c4]Mayur Naik, Jens Palsberg:
A Type System Equivalent to a Model Checker. ESOP 2005: 374-388 - [c3]Ben Liblit, Mayur Naik, Alice X. Zheng, Alexander Aiken, Michael I. Jordan:
Scalable statistical bug isolation. PLDI 2005: 15-26 - 2003
- [c2]Thomas Ball, Mayur Naik, Sriram K. Rajamani:
From symptom to cause: localizing errors in counterexample traces. POPL 2003: 97-105 - 2002
- [c1]Mayur Naik, Jens Palsberg:
Compiling with code-size constraints. LCTES-SCOPES 2002: 120-129
Editorship
- 2020
- [e3]Koushik Sen, Mayur Naik:
Proceedings of the 4th ACM SIGPLAN International Workshop on Machine Learning and Programming Languages, MAPL@PLDI 2020, London, UK, June 15, 2020. ACM 2020, ISBN 978-1-4503-7996-0 [contents] - 2019
- [e2]Jennifer B. Sartor, Mayur Naik, Christopher J. Rossbach:
Proceedings of the 15th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments, VEE 2019, Providence, RI, USA, April 14, 2019. ACM 2019, ISBN 978-1-4503-6020-3 [contents] - 2015
- [e1]Anders Møller, Mayur Naik:
Proceedings of the 4th ACM SIGPLAN International Workshop on State Of the Art in Program Analysis, SOAP@PLDI 2015, Portland, OR, USA, June 15 - 17, 2015. ACM 2015, ISBN 978-1-4503-3585-0 [contents]
Informal and Other Publications
- 2023
- [i15]Yinjun Wu, Adam Stein, Jacob Gardner, Mayur Naik:
Learning to Select Pivotal Samples for Meta Re-weighting. CoRR abs/2302.04418 (2023) - [i14]Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong:
Do Machine Learning Models Learn Common Sense? CoRR abs/2303.01433 (2023) - [i13]Ziyang Li, Jiani Huang, Mayur Naik:
Scallop: A Language for Neurosymbolic Programming. CoRR abs/2304.04812 (2023) - [i12]Jiani Huang, Ziyang Li, David Jacobs, Mayur Naik, Ser-Nam Lim:
LASER: Neuro-Symbolic Learning of Semantic Video Representations. CoRR abs/2304.07647 (2023) - [i11]Hanlin Zhang, Jiani Huang, Ziyang Li, Mayur Naik, Eric P. Xing:
Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming. CoRR abs/2305.03742 (2023) - [i10]Adam Stein, Yinjun Wu, Eric Wong, Mayur Naik:
Rectifying Group Irregularities in Explanations for Distribution Shift. CoRR abs/2305.16308 (2023) - [i9]Aaditya Naik, Adam Stein, Yinjun Wu, Eric Wong, Mayur Naik:
MDB: Interactively Querying Datasets and Models. CoRR abs/2308.06686 (2023) - [i8]Elizabeth Dinella, Shuvendu K. Lahiri, Mayur Naik:
Program Structure Aware Precondition Generation. CoRR abs/2310.02154 (2023) - [i7]Avishree Khare, Saikat Dutta, Ziyang Li, Alaia Solko-Breslin, Rajeev Alur, Mayur Naik:
Understanding the Effectiveness of Large Language Models in Detecting Security Vulnerabilities. CoRR abs/2311.16169 (2023) - 2021
- [i6]Elizabeth Dinella, Todd Mytkowicz, Alexey Svyatkovskiy, Christian Bird, Mayur Naik, Shuvendu K. Lahiri:
DeepMerge: Learning to Merge Programs. CoRR abs/2105.07569 (2021) - 2019
- [i5]Halley Young, Osbert Bastani, Mayur Naik:
Learning Neurosymbolic Generative Models via Program Synthesis. CoRR abs/1901.08565 (2019) - [i4]Brian Heath, Neelay Velingker, Osbert Bastani, Mayur Naik:
PolyDroid: Learning-Driven Specialization of Mobile Applications. CoRR abs/1902.09589 (2019) - [i3]Xujie Si, Mukund Raghothaman, Kihong Heo, Mayur Naik:
Synthesizing Datalog Programs Using Numerical Relaxation. CoRR abs/1906.00163 (2019) - 2010
- [i2]Byung-Gon Chun, Sunghwan Ihm, Petros Maniatis, Mayur Naik:
CloneCloud: Boosting Mobile Device Applications Through Cloud Clone Execution. CoRR abs/1009.3088 (2010) - [i1]Byung-Gon Chun, Ling Huang, Sangmin Lee, Petros Maniatis, Mayur Naik:
Mantis: Predicting System Performance through Program Analysis and Modeling. CoRR abs/1010.0019 (2010)
Coauthor Index
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