Paper Review 1: Learning Invariants

Follow the Paper Review Guide for the review format, grading scale, and course policies.

Choose one paper

Choose exactly one of the following three peer-reviewed conference papers. Read the main paper; appendices and supplementary material are optional.

1. Pranav Garg, Daniel Neider, P. Madhusudan, and Dan Roth. “Learning Invariants using Decision Trees and Implication Counterexamples.” POPL 2016, pp. 499–512. Paper page and citation · Author PDF

2. Jianan Yao, Gabriel Ryan, Justin Wong, Suman Jana, and Ronghui Gu. “Learning Nonlinear Loop Invariants with Gated Continuous Logic Networks.” PLDI 2020, pp. 106–120. Paper page and citation · Author PDF

3. Cheng Wen, Jialun Cao, Jie Su, Zhiwu Xu, Shengchao Qin, Mengda He, Haokun Li, Shing-Chi Cheung, and Cong Tian. “Enchanting Program Specification Synthesis by Large Language Models Using Static Analysis and Program Verification.” CAV 2024, pp. 302–328. Paper, PDF, and citation

Write your review

Follow the Paper Review Guide: write exactly four short paragraphs, in the required order, with a maximum of 700 words. The PDF should contain only those four paragraphs. The guide explains the review contents, formatting requirements, and grading scale.

Submit through Classroom50

1. Accept Paper Review 1 on Classroom50 to access your submission repository.
2. Save your finished review as submission.pdf and add it to that repository. The repository root is the easiest place to find it.
3. Commit and push your submission before Wednesday, October 7, 2026, at 11:59 p.m. MT. Check the repository on GitHub to confirm that submission.pdf is present and opens correctly.

You may add any other documents to your repository, including notes, drafts, and source files. The instructor must be able to find your final submission.pdf easily; this PDF is the document that will be graded.

This is an individual review. The five shared late days for programming labs do not apply to paper reviews; see the guide for the submission policies.