Mayur Naik

Monographs

  1. Neurosymbolic Programming in Scallop: Principles and Practice. Ziyang Li, Jiani Huang, Jason Liu, Mayur Naik. Foundations and Trends in Programming Languages. NOW Publishers, 2024.

Preprints

  1. Dolphin: A Programmable Framework for Scalable Neurosymbolic Learning. Aaditya Naik, Jason Liu, Claire Wang, Saikat Dutta, Mayur Naik, Eric Wong. October 2024.
  2. LLM-Assisted Static Analysis for Detecting Security Vulnerabilities. Ziyang Li, Saikat Dutta, Mayur Naik. May 2024.
  3. LASER: A Neuro-Symbolic Framework for Learning Spatial-Temporal Scene Graphs with Weak Supervision. Jiani Huang, Ziyang Li, Mayur Naik, Ser Nam Lim. May 2024.

Peer-Reviewed Papers

  1. Understanding the Effectiveness of Large Language Models in Detecting Security Vulnerabilities. Avishree Khare*, Saikat Dutta*, Ziyang Li, Alaia Solko-Breslin, Rajeev Alur, Mayur Naik. ICST 2025.
  2. Data-Efficient Learning with Neural Programs. Alaia Solko-Breslin, Seewon Choi, Ziyang Li, Neelay Velingker, Rajeev Alur, Mayur Naik, Eric Wong. NeurIPS 2024.
  3. Crowd-sourced machine learning prediction of Long COVID using data from the National COVID Cohort Collaborative. Timothy Bergquist et al.. eBioMedicine 2024. NIH L3C Honorable Mention Award.
  4. TYGR: Type Inference on Stripped Binaries using Graph Neural Networks. Ziyang Li*, Chang Zhu*, Anton Xue, Ati Priya Bajaj, William Gibbs, Yibo Liu, Rajeev Alur, Tiffany Bao, Hanjun Dai, Adam Doupé, Mayur Naik, Yan Shoshitaishvili, Ruoyu Wang, Aravind Machiry. USENIX Security 2024.
  5. Towards Compositionality in Concept Learning. Adam Stein, Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong. ICML 2024.
  6. DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation. Yinjun Wu*, Mayank Keoliya*, Kan Chen, Neelay Velingker, Ziyang Li, Emily Getzen, Qi Long, Mayur Naik, Ravi Parikh, Eric Wong. ICML 2024. Spotlight Paper.
  7. TorchQL: A Programming Framework for Integrity Constraints in Machine Learning. Aaditya Naik, Adam Stein, Yinjun Wu, Mayur Naik, Eric Wong. OOPSLA 2024.
  8. Relational Programming with Foundation Models. Ziyang Li, Jiani Huang, Jason Liu, Felix Zhu, Eric Zhao, William Dodds, Neelay Velingker, Rajeev Alur, Mayur Naik. AAAI 2024.
  9. Relational Query Synthesis ⋈ Decision Tree Learning. Aaditya Naik, Aalok Thakkar, Adam Stein, Rajeev Alur, Mayur Naik. VLDB 2024.
  10. Mobius: Synthesizing Relational Queries with Recursive and Invented Predicates. Aalok Thakkar, Nathaniel Sands, George Petrou, Rajeev Alur, Mayur Naik, Mukund Raghothaman. OOPSLA 2023.
  11. Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming. Hanlin Zhang*, Jiani Huang*, Ziyang Li, Mayur Naik, Eric Xing. Findings of ACL 2023.
  12. Do Machine Learning Models Learn Statistical Rules Inferred from Data?. Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong. ICML 2023.
  13. Scallop: A Language for Neurosymbolic Programming. Ziyang Li*, Jiani Huang*, Mayur Naik. PLDI 2023. [long version] [code] [artifact].
  14. Learning to Select Pivotal Samples for Meta Re-weighting. Yinjun Wu, Adam Stein, Jacob Gardner, Mayur Naik. AAAI 2023. Oral Presentation.
  15. Synthesizing Formal Network Specifications from Input-Output Examples. Haoxian Chen, Chenyuan Wu, Andrew Zhao, Mukund Raghothaman, Mayur Naik, Boon Thau Loo. IEEE/ACM ToN 2022.
  16. DeepMerge: Learning to Merge Programs. Elizabeth Dinella, Todd Mytkowicz, Alexey Svyatkovskiy, Christian Bird, Mayur Naik, Shuvendu Lahiri. IEEE TSE 2022 and FSE 2022 (Journal-First Track).
  17. CodeTrek: Flexible Modeling of Code using an Extensible Relational Representation. Pardis Pashakhanloo, Aaditya Naik, Yuepeng Wang, Hanjun Dai, Petros Maniatis, Mayur Naik. ICLR 2022.
  18. PacJam: Securing Dependencies Continuously via Package-Oriented Debloating. Pardis Pashakhanloo, Aravind Machiry, Hyonyoung Choi, Anthony Canino, Kihong Heo, Insup Lee, Mayur Naik. Asia CCS 2022.
  19. Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning. Jiani Huang*, Ziyang Li*, Binghong Chen, Karan Samel, Mayur Naik, Le Song, Xujie Si. NeurIPS 2021.
  20. Sporq: An Interactive Environment for Exploring Code Using Query-by-Example. Aaditya Naik, Jonathan Mendelson, Nate Sands, Yuepeng Wang, Mayur Naik, Mukund Raghothaman. UIST 2021.
  21. Example-Guided Synthesis of Relational Queries. Aalok Thakkar, Aaditya Naik, Nate Sands, Rajeev Alur, Mayur Naik, Mukund Raghothaman. PLDI 2021.
  22. Arbitrar: User-Guided API Misuse Detection. Ziyang Li, Aravind Machiry, Binghong Chen, Ke Wang, Mayur Naik, Le Song. S&P 2021.
  23. GenSynth: Synthesizing Datalog Programs without Language Bias. Jonathan Mendelson, Aaditya Naik, Mukund Raghothaman, Mayur Naik. AAAI 2021.
  24. Generating Programmatic Referring Expressions via Program Synthesis. Jiani Huang, Calvin Smith, Osbert Bastani, Rishabh Singh, Aws Albarghouthi, Mayur Naik. ICML 2020.
  25. Code2Inv: A Deep Learning Framework for Program Verification. Xujie Si*, Aaditya Naik*, Hanjun Dai, Mayur Naik, Le Song. CAV 2020.
  26. Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs. Elizabeth Dinella*, Hanjun Dai*, Ziyang Li, Mayur Naik, Le Song, Ke Wang. ICLR 2020. Spotlight Paper.
  27. Provenance-Guided Synthesis of Datalog Programs. Mukund Raghothaman, Jonathan Mendelson, David Zhao, Mayur Naik, Bernhard Scholz. POPL 2020.
  28. Synthesizing Datalog Programs using Numerical Relaxation. Xujie Si*, Mukund Raghothaman*, Kihong Heo, Mayur Naik. IJCAI 2019.
  29. Continuously Reasoning about Programs using Differential Bayesian Inference. Kihong Heo*, Mukund Raghothaman*, Xujie Si, Mayur Naik. PLDI 2019. Distinguished Paper Award.
  30. Learning Neurosymbolic Generative Models via Program Synthesis. Halley Young, Osbert Bastani, Mayur Naik. ICML 2019.
  31. Learning a Meta-Solver for Syntax-Guided Program Synthesis. Xujie Si*, Yuan Yang*, Hanjun Dai, Mayur Naik, Le Song. ICLR 2019.
  32. Learning Loop Invariants for Program Verification. Xujie Si*, Hanjun Dai*, Mukund Raghothaman, Mayur Naik, Le Song. NeurIPS 2018. Spotlight Paper.
  33. Syntax-Guided Synthesis of Datalog Programs. Xujie Si*, Woosuk Lee*, Richard Zhang, Aws Albarghouthi, Paris Koutris, Mayur Naik. FSE 2018.
  34. Effective Program Debloating via Reinforcement Learning. Kihong Heo*, Woosuk Lee*, Pardis Pashakhanloo, Mayur Naik. CCS 2018.
  35. User-Guided Program Reasoning Using Bayesian Inference. Mukund Raghothaman*, Sulekha Kulkarni*, Kihong Heo, Mayur Naik. PLDI 2018.
  36. Accelerating Search-Based Program Synthesis Using Learned Probabilistic Models. Woosuk Lee, Kihong Heo, Rajeev Alur, Mayur Naik. PLDI 2018.
  37. Effective Interactive Resolution of Static Analysis Alarms. Xin Zhang, Radu Grigore, Xujie Si, Mayur Naik. OOPSLA 2017.
  38. Constraint-Based Synthesis of Datalog Programs. Aws Albarghouthi, Paraschos Koutris, Mayur Naik, Calvin Smith. CP 2017.
  39. Accelerating Program Analyses by Cross-Program Training. Sulekha Kulkarni, Ravi Mangal, Xin Zhang, Mayur Naik. OOPSLA 2016.
  40. On Incremental Core-Guided MaxSAT Solving. Xujie Si, Xin Zhang, Vasco Manquinho, Mikolas Janota, Alexey Ignatiev, Mayur Naik. CP 2016.
  41. APISan: Sanitizing API Usages through Semantic Cross-checking. Insu Yun, Changwoo Min, Xujie Si, Yeongjin Jang, Taesoo Kim, Mayur Naik. USENIX Security 2016.
  42. Scaling Relational Inference Using Proofs and Refutations. Ravi Mangal, Xin Zhang, Aditya Kamath, Aditya Nori, Mayur Naik. AAAI 2016.
  43. Query-Guided Maximum Satisfiability. Xin Zhang, Ravi Mangal, Aditya Nori, Mayur Naik. POPL 2016.
  44. Mantis: Efficient Predictions of Execution Time, Energy Usage, Memory Usage and Network Usage on Smart Mobile Devices. Yongin Kwon, Sangmin Lee, Hayoon Yi, Donghyun Kwon, Seungjun Yang, Byung-Gon Chun, Ling Huang, Petros Maniatis, Mayur Naik, Yunheung Paek. IEEE TMC 2015.
  45. Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances. Ravi Mangal, Xin Zhang, Aditya Nori, Mayur Naik. SAT 2015.
  46. A User-Guided Approach to Program Analysis. Ravi Mangal, Xin Zhang, Aditya Nori, Mayur Naik. FSE 2015. Distinguished Paper Award.
  47. FlexJava: Language Support for Safe and Modular Approximate Programming. Jongse Park, Hadi Esmaeilzadeh, Xin Zhang, Mayur Naik, William Harris. FSE 2015.
  48. Modularity in Lattices: A Case Study on the Correspondence between Top-Down and Bottom-Up Analysis. Ghila Castelnuovo, Mayur Naik, Noam Rinetzky, Mooly Sagiv, Hongseok Yang. SAS 2015.
  49. COSMOS: Computation Offloading as a Service for Mobile Devices. Cong Shi, Karim Habak, Pranesh Pandurangan, Mostafa Ammar, Mayur Naik, Ellen Zegura. MobiHoc 2014.
  50. On Abstraction Refinement for Program Analyses in Datalog. Xin Zhang, Ravi Mangal, Radu Grigore, Mayur Naik, Hongseok Yang. PLDI 2014. Distinguished Paper Award.
  51. Hybrid Top-Down and Bottom-Up Interprocedural Analysis. Xin Zhang, Ravi Mangal, Mayur Naik, Hongseok Yang. PLDI 2014.
  52. A Correspondence between Two Approaches to Interprocedural Analysis in the Presence of Join. Ravi Mangal, Mayur Naik, Hongseok Yang. ESOP 2014. Best Paper Award Nominee.
  53. Dynodroid: An Input Generation System for Android Apps. Aravind Machiry, Rohan Tahiliani, Mayur Naik. FSE 2013. Test-of-Time Paper Award and Distinguished Artifact Award.
  54. Mantis: Automatic Performance Prediction for Smartphone Applications. Yongin Kwon, Sangmin Lee, Hayoon Yi, Donghyun Kwon, Seungjun Yang, Byung-Gon Chun, Ling Huang, Petros Maniatis, Mayur Naik, Yunheung Paek. USENIX ATC 2013.
  55. Finding Optimum Abstractions in Parametric Dataflow Analysis. Xin Zhang, Mayur Naik, Hongseok Yang. PLDI 2013.
  56. Automated Concolic Testing of Smartphone Apps. Saswat Anand, Mayur Naik, Hongseok Yang, Mary Jean Harrold. FSE 2012. Test-of-Time Paper Award.
  57. Abstractions from Tests. Mayur Naik, Hongseok Yang, Ghila Castelnuovo, Mooly Sagiv. POPL 2012.
  58. Yada: Straightforward Parallel Programming. David Gay, Joel Galenson, Mayur Naik, Kathy Yelick. Parallel Computing, Elsevier, 2011.
  59. Scaling Abstraction Refinement via Pruning. Percy Liang and Mayur Naik. PLDI 2011.
  60. CloneCloud: Elastic Execution between Mobile Device and Cloud. Byung-Gon Chun, Sunghwan Ihm, Petros Maniatis, Mayur Naik, Ashwin Patti. EuroSys 2011.
  61. Learning Minimal Abstractions. Percy Liang, Omer Tripp, Mayur Naik. POPL 2011.
  62. Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression. Ling Huang, Jinzhu Jia, Bin Yu, Byung-Gon Chun, Petros Maniatis, Mayur Naik. NIPS 2010.
  63. An Effective Dynamic Analysis for Detecting Generalized Deadlocks. Pallavi Joshi, Mayur Naik, Koushik Sen, David Gay. FSE 2010.
  64. A Dynamic Evaluation of the Precision of Static Heap Abstractions. Percy Liang, Omer Tripp, Mayur Naik, Mooly Sagiv. OOPSLA 2010.
  65. CalFuzzer: An Extensible Active Testing Framework for Concurrent Programs. Pallavi Joshi, Mayur Naik, Chang-Seo Park, Koushik Sen. CAV 2009.
  66. Lightweight Annotations for Controlling Sharing in Concurrent Data Structures. Zachary Anderson, David Gay, Mayur Naik. PLDI 2009.
  67. A Randomized Dynamic Program Analysis Technique for Detecting Real Deadlocks. Pallavi Joshi, Chang-Seo Park, Koushik Sen, Mayur Naik. PLDI 2009.
  68. Effective Static Deadlock Detection. Mayur Naik, Chang-Seo Park, Koushik Sen, David Gay. ICSE 2009. Distinguished Paper Award.
  69. A Type System Equivalent to a Model Checker. Mayur Naik and Jens Palsberg. ACM TOPLAS 2008.
  70. Conditional Must Not Aliasing for Static Race Detection. Mayur Naik and Alex Aiken. POPL 2007.
  71. Effective Static Race Detection for Java. Mayur Naik, Alex Aiken, John Whaley. PLDI 2006.
  72. Statistical Debugging: Simultaneous Isolation of Multiple Bugs. Alice Zheng, Michael Jordan, Ben Liblit, Mayur Naik, Alex Aiken. ICML 2006.
  73. Scalable Statistical Bug Isolation. Ben Liblit, Mayur Naik, Alice Zheng, Alex Aiken, Michael Jordan. PLDI 2005.
  74. A Type System Equivalent to a Model Checker. Mayur Naik and Jens Palsberg. ESOP 2005.
  75. Compiling with Code-Size Constraints. Mayur Naik and Jens Palsberg. ACM TECS 2004.
  76. From Symptom to Cause: Localizing Errors in Counterexample Traces. Thomas Ball, Mayur Naik, Sriram Rajamani. POPL 2003.
  77. Compiling with Code-Size Constraints. Mayur Naik and Jens Palsberg. LCTES 2002.

Invited Articles

  1. Rethinking Static Analysis by Combining Discrete and Continuous Reasoning. Mayur Naik. SAS 2019.
  2. Maximum Satisfiability in Program Analysis: Applications and Techniques. Mayur Naik, Xujie Si, Xin Zhang, Radu Grigore. VMCAI 2018.
  3. Maximum Satisfiability in Software Analysis: Applications and Techniques. Xujie Si, Xin Zhang, Radu Grigore, Mayur Naik. CAV 2017.
  4. ILP-based Resource-aware Compilation. Jens Palsberg and Mayur Naik. Multiprocessor Systems-on-Chips, Elsevier, 2004.