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description: A practical guide to fuzz testing in Go, covering the history and types of fuzzing, Go's built-in fuzzing engine internals (introduced in Go 1.18), and how...
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# Fuzz Testing in Go

**[Medium](https://daily.dev/sources/medium_js)** · 13 min read · 1 upvotes · 1 comments

## Summary

A practical guide to fuzz testing in Go, covering the history and types of fuzzing, Go's built-in fuzzing engine internals (introduced in Go 1.18), and how mutation-based input generation works across different types (bool, int, string/[]byte). Includes a full implementation example of a currency converter with a fuzz test using round-trip testing and oracle-based error assertion techniques. Shows how to seed the corpus, run the fuzzer with `go test -fuzz`, and interpret the generated mutated inputs.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://medium.com/@elesm/fuzz-testing-in-go-aecec2a64fe3>

## Questions this post answers

### What primitive types does Go's built-in fuzzing engine support as fuzz function parameters?

Go's fuzzing engine, introduced in Go 1.18, only recognizes a fixed set of primitive types as valid fuzz parameters: []byte, string, bool, byte, rune, float32, float64, the signed integers int, int8, int16, int32, int64, and the unsigned integers uint, uint8, uint16, uint32, uint64. Anything else, like structs, slices of structs, or maps, must be broken down into these primitives inside the fuzz function itself.

_Developers wiring up FuzzConvert-style tests can compare Go testing approaches shared across daily.dev._

### How does Go's fuzzer mutate boolean input values during a fuzz test?

A boolean parameter is mutated with a simple coin flip: on each iteration there is roughly a 50% chance the mutator flips the value to its opposite, turning true into false or vice versa, with nothing more elaborate applied to bool inputs.

_Anyone debugging fuzzer behavior on bool fields can dig deeper into Go internals via daily.dev._

### What is the oracle problem in fuzz testing and how can it be solved?

The oracle problem is that fuzz testing lacks a pre-decided expected output since inputs are randomly generated rather than hand-picked, so there is no ready answer to check results against. Techniques like round-trip testing (converting back and forth and comparing results) and oracle-based error assertion (using errors.Is to confirm a specific expected error) solve this without computing an expected value for every case.

_Teams designing fuzz test assertions can compare oracle strategies across languages on daily.dev._

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---

Tags: [#testing](https://daily.dev/tags/testing), [#golang](https://daily.dev/tags/golang)

[View this post on daily.dev](https://daily.dev/posts/fuzz-testing-in-go-sq6gh04sy)

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