This program is tentative and subject to change.

Thu 24 Oct 2024 15:00 - 15:20 at IBR East - Machine Learning and Programming Languages

Compiler correctness is crucial, as miscompilation can falsify program behaviors, leading to serious consequences over the software supply chain. In the literature, fuzzing has been extensively studied to uncover compiler defects. However, compiler fuzzing remains challenging: Existing arts focus on black- and grey-box fuzzing, which generates test programs without sufficient understanding of internal compiler behaviors. As such, they often fail to construct test programs to exercise intricate optimizations. Meanwhile, traditional white-box techniques, such as symbolic execution, are computationally inapplicable to the giant codebase of compiler systems. Recent advances demonstrate that Large Language Models (LLMs) excel in code generation/understanding tasks and even have achieved state-of-the-art performance in black-box fuzzing. Nonetheless, guiding LLMs with compiler source-code information remains a missing piece of research in compiler testing.

To this end, we propose WhiteFox, the first white-box compiler fuzzer using LLMs with source-code information to test compiler optimization, with a spotlight on detecting deep logic bugs in the emerging deep learning (DL) compilers. WhiteFox adopts a multi-agent framework: (i) an LLM-based analysis agent examines the low-level optimization source code and produces requirements on the high-level test programs that can trigger the optimization; (ii) an LLM-based generation agent produces test programs based on the summarized requirements. Additionally, optimization-triggering tests are also used as feedback to further enhance the test generation prompt on the fly. Our evaluation on the three most popular DL compilers (i.e., PyTorch Inductor, TensorFlow-XLA, and TensorFlow Lite) shows that WhiteFox can generate high-quality test programs to exercise deep optimizations requiring intricate conditions, practicing up to 8 times more optimizations than state-of-the-art fuzzers. To date, WhiteFox has found in total 101 bugs for the compilers under test, with 92 confirmed as previously unknown and 70 already fixed. Notably, WhiteFox has been recently acknowledged by the PyTorch team, and is in the process of being incorporated into its development workflow. Finally, beyond DL compilers, WhiteFox can also be adapted for compilers in different domains, such as LLVM, where WhiteFox has already found multiple bugs.

This program is tentative and subject to change.

Thu 24 Oct

Displayed time zone: Pacific Time (US & Canada) change

13:40 - 15:20
Machine Learning and Programming LanguagesOOPSLA 2024 at IBR East
13:40
20m
Talk
CYCLE: Learning to Self-Refine the Code Generation
OOPSLA 2024
Yangruibo Ding Columbia University, Marcus J. Min Columbia University, Gail Kaiser Columbia University, Baishakhi Ray Columbia University, New York; AWS AI Lab
14:00
20m
Talk
Evaluating the effectiveness of Deep Learning Models for Foundational Program Analysis Tasks
OOPSLA 2024
Qian Chen Nanjing University, Chenyang Yu Department of Computer Science and Technology, Nanjing University, Ruyan Liu Department of Computer Science and Technology, Nanjing University, Chi Zhang Nanjing University, Yu Wang Nanjing University, Ke Wang , Ting Su East China Normal University, Linzhang Wang Nanjing University
14:20
20m
Talk
Knowledge Transfer from High-Resource to Low-Resource Programming Languages for Code LLMs
OOPSLA 2024
Federico Cassano Northeastern University, John Gouwar Northeastern University, Francesca Lucchetti Northeastern University, Claire Schlesinger Northeastern University, Anders Freeman Wellesley College, Carolyn Jane Anderson Wellesley College, Molly Q Feldman Oberlin College, Michael Greenberg Stevens Institute of Technology, Abhinav Jangda Microsoft Research, Arjun Guha Northeastern University; Roblox
Pre-print
14:40
20m
Talk
Statically Contextualizing Large Language Models with Typed Holes
OOPSLA 2024
Andrew Blinn University of Michigan, Xiang Li University of Michigan, Ann Arbor, June Hyung Kim University of Michigan, Cyrus Omar University of Michigan
15:00
20m
Talk
WhiteFox: White-box Compiler Fuzzing Empowered by Large Language Models
OOPSLA 2024
Chenyuan Yang University of Illinois at Urbana-Champaign, Yinlin Deng University of Illinois at Urbana-Champaign, Runyu Lu Huazhong University of Science and Technology, Jiayi Yao The Chinese University of Hong Kong, Shenzhen, Jiawei Liu University of Illinois at Urbana-Champaign, Reyhaneh Jabbarvand University of Illinois at Urbana-Champaign, Lingming Zhang University of Illinois at Urbana-Champaign