Execution-Aware Program Reduction for WebAssembly via Record and Replay

TL;DR

This paper introduces execution-aware program reduction techniques, RR-Reduce and Hybrid-Reduce, that leverage runtime behavior via record and replay to produce significantly smaller WebAssembly programs for debugging.

Contribution

The paper presents novel execution-aware reduction methods that outperform existing techniques by utilizing execution behavior to produce smaller, more manageable WebAssembly programs for debugging.

Findings

RR-Reduce reduces programs to 1.20% of original size in 14.5 minutes

Hybrid-Reduce reduces programs to 0.13% of original size in 3.5 hours

Both methods outperform state-of-the-art techniques in reduction speed and size

Abstract

WebAssembly (Wasm) programs may trigger bugs in their engine implementations. To aid debugging, program reduction techniques try to produce a smaller variant of the input program that still triggers the bug. However, existing execution-unaware program reduction techniques struggle with large and complex Wasm programs, because they rely on static information and apply syntactic transformations, while ignoring the valuable information offered by the input program's execution behavior. We present RR-Reduce and Hybrid-Reduce, novel execution-aware program reduction techniques that leverage execution behaviors via record and replay. RR-Reduce identifies a bug-triggering function as the target function, isolates that function from the rest of the program, and generates a reduced program that replays only the interactions between the target function and the rest of the program. Hybrid-Reduce combines a complementary execution-unaware reduction technique with RR-Reduce to further reduce program size. We evaluate RR-Reduce and Hybrid-Reduce on 28 Wasm programs that trigger a diverse set of bugs in three engines. On average, RR-Reduce reduces the programs to 1.20 percent of their original size in 14.5 minutes, which outperforms the state of the art by 33.15 times in terms of reduction time. Hybrid-Reduce reduces the programs to 0.13 percent of their original size in 3.5 hours, which outperforms the state of the art by 3.42 times in terms of reduced program size and 2.26 times in terms of reduction time. We envision RR-Reduce as the go-to tool for rapid, on-demand debugging in minutes, and Hybrid-Reduce for scenarios where developers require the smallest possible programs.