# Growing a Test Corpus with Bonsai Fuzzing

arXiv: https://arxiv.org/abs/2103.04388 · HTML: https://mlsanity.com/paper/2103.04388/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Mar 2021.

## Built on by (most cited first, 1 of 1)

- [Fuzzing with Agents? Generators Are All You Need](https://mlsanity.com/paper/2604.01442/) (2026)

## Abstract (arXiv)

This paper presents a coverage-guided grammar-based fuzzing technique for automatically generating a corpus of concise test inputs for programs such as compilers. We walk-through a case study of a compiler designed for education and the corresponding problem of generating meaningful test cases to provide to students. The prior state-of-the-art solution is a combination of fuzzing and test-case reduction techniques such as variants of delta-debugging. Our key insight is that instead of attempting to minimize convoluted fuzzer-generated test inputs, we can instead grow concise test inputs by construction using a form of iterative deepening. We call this approach Bonsai Fuzzing. Experimental results show that Bonsai Fuzzing can generate test corpora having inputs that are 16--45% smaller in size on average as compared to a fuzz-then-reduce approach, while achieving approximately the same code coverage and fault-detection capability.