Please check out the following paper discussion schedule and prepare a 20-minute presentation followed by a 15-minute discussion.

Paper Presentation Schedule

Date Paper Discussion Leader
4/21/2025 9. Oracle-Guided Component-Based Program Synthesis. MK
4/21/2025 5. DreamCoder: Bootstrapping Inductive Program Synthesis with Wake-Sleep Library Learning. AMN
4/23/2025 3. Programmatic and Direct Manipulation, Together at Last. JL
4/23/2025 11. Superfusion: Eliminating Intermediate Data Structures via Inductive Synthesis. OG
4/28/2025 7. Temporal Stream Logic: Synthesis Beyond the Bools. JA
4/28/2025 2. What’s Decidable about Syntax-Guided Synthesis? HyL
4/30/2025 4. Wrex: A Unified Programming-by-Example Interaction for Synthesizing Readable Code for Data Scientists. YL
4/30/2025 10. A Theory of Formal Synthesis via Inductive Learning. JK
5/12/2025 21. Unrealizability Logic YK
5/12/2025 23. Deepseek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search YH
5/14/2025 8. Automating String Processing in Spreadsheets Using Input-Output Examples. HoL
5/14/2025 15. Towards AI-Assisted Synthesis of Verified Dafny Methods. TR
5/19/2025 20. Programmatically Interpretable Reinforcement Learning. JY
5/19/2025 22. An In-Context Learning Agent for Formal Theorem-Proving YN
5/21/2025 6. Can Large Language Models Transform Natural Language Intent into Formal Method Postconditions? TL
5/21/2025 14. Scallop: A Language for Neurosymbolic Programming. TTF

List of Papers for Presentation

  1. A. Blasi, A. Goffi, K. Kuznetsov, A. Gorla, M. D. Ernst, M. Pezzè, and S. D. Castellanos.
    Translating Code Comments to Procedure Specifications.
    Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), 2018.
    [DOI]

  2. B. Caulfield, M. N. Rabe, S. A. Seshia, and S. Tripakis.
    What’s Decidable about Syntax-Guided Synthesis?
    arXiv preprint arXiv:1510.08393, 2016.
    [arXiv]

  3. R. Chugh, B. Hempel, M. Spradlin, and J. Albers.
    Programmatic and Direct Manipulation, Together at Last.
    Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2016.
    [DOI]

  4. I. Drosos, T. Barik, P. J. Guo, R. DeLine, and S. Gulwani.
    Wrex: A Unified Programming-by-Example Interaction for Synthesizing Readable Code for Data Scientists.
    Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI), 2020.
    [DOI]

  5. K. Ellis, C. Wong, M. Nye, M. Sablé-Meyer, L. Morales, L. Hewitt, L. Cary, and A. Solar-Lezama.
    DreamCoder: Bootstrapping Inductive Program Synthesis with Wake-Sleep Library Learning.
    Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation (PLDI), 2021.
    [DOI]

  6. M. Endres, S. Fakhoury, S. Chakraborty, and S. K. Lahiri.
    Can Large Language Models Transform Natural Language Intent into Formal Method Postconditions?
    Proceedings of the ACM on Software Engineering, Volume 1, Issue FSE. 2024.
    [DOI]

  7. B. Finkbeiner, F. Klein, R. Piskac, and M. Santolucito.
    Temporal Stream Logic: Synthesis Beyond the Bools.
    In Computer Aided Verification (CAV), Lecture Notes in Computer Science, vol. 11561, 2019.
    [DOI]

  8. S. Gulwani.
    Automating String Processing in Spreadsheets Using Input-Output Examples.
    Proceedings of the ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL), 2011.
    [DOI]

  9. S. Jha, S. Gulwani, S. A. Seshia, and A. Tiwari.
    Oracle-Guided Component-Based Program Synthesis.
    Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering (ICSE), 2010.
    [DOI]

  10. S. Jha and S. A. Seshia.
    A Theory of Formal Synthesis via Inductive Learning.
    Acta Informatica, 54(7), 2017.
    [DOI]

  11. R. Ji, Y. Zhao, N. Polikarpova, Y. Xiong, and Z. Hu.
    Superfusion: Eliminating Intermediate Data Structures via Inductive Synthesis.
    Proceedings of the ACM on Programming Languages (PACMPL), Volume 8, Issue PLDI. 2024.
    [DOI]

  12. P. Krogmeier and P. Madhusudan.
    Languages with Decidable Learning: A Meta-theorem.
    Proceedings of the ACM on Programming Languages (PACMPL), Volume 7, Issue OOPSLA1. 2023.
    [DOI]

  13. W. Lee.
    Combining the Top-Down Propagation and Bottom-Up Enumeration for Inductive Program Synthesis.
    Proceedings of the ACM on Programming Languages (PACMPL), Volume 5, Issue POPL. 2021.
    [DOI]

  14. Z. Li, J. Huang, and M. Naik.
    Scallop: A Language for Neurosymbolic Programming.
    Proceedings of the ACM on Programming Languages (PACMPL), Volume 7, Issue PLDI. 2023.
    [DOI]

  15. M. R. H. Misu, C. V. Lopes, I. Ma, and J. Noble.
    Towards AI-Assisted Synthesis of Verified Dafny Methods.
    Proceedings of the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE), 2024.
    [DOI]

  16. S. Pailoor, Y. Wang, and I. Dillig.
    Semantic Code Refactoring for Abstract Data Types.
    Proceedings of the ACM on Programming Languages (PACMPL), Volume 8, Issue POPL. 2024.
    [DOI]

  17. R. Singh, R. Singh, Z. Xu, R. Krosnick, and A. Solar-Lezama.
    Modular Synthesis of Sketches Using Models.
    In Verification, Model Checking, and Abstract Interpretation (VMCAI), Lecture Notes in Computer Science, vol. 8318, 2014.
    [DOI]

  18. S. Srivastava, S. Gulwani, and S. Foster.
    From Program Verification to Program Synthesis.
    Proceedings of the ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL), 2010.
    [DOI]

  19. E. Torlak and R. Bodík.
    A Lightweight Symbolic Virtual Machine for Solver-Aided Host Languages.
    Proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2014.
    [DOI]

  20. A. Verma, V. Murali, R. Singh, P. Kohli, and S. Chaudhuri.
    Programmatically Interpretable Reinforcement Learning.
    Proceedings of the 35th International Conference on Machine Learning (ICML), 2018.
    [URL]

  21. J Kim, L. D’Antoni, T. Reps.
    Unrealizability Logic.
    Proceedings of the ACM on Programming Languages, Volume 7, Issue POPL, 2023.
    [DOI]

  22. A. Thakur, G. Tsoukalas, Y. Wen, J. Xin, and S. Chaudhuri.
    An In-Context Learning Agent for Formal Theorem-Proving.
    In Proceedings of the 2025 Conference on Language Modeling (COLM), 2024. [URL]

  23. H. Xin, Z. Z. Ren, J. Song, Z. Shao, W. Zhao, H. Wang, B. Liu, L. Zhang, X. Lu, Q. Du, W. Gao, H. Zhang, Q. Zhu, D. Yang, Z. Gou, Z. F. Wu, F. Luo, and C. Ruan.
    DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search.
    In Proceedings of the 13th International Conference on Learning Representations (ICLR), 2025. [URL]