3 releases
0.1.2 | Jul 12, 2023 |
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0.1.1 | Jul 12, 2023 |
0.1.0 | Jul 8, 2023 |
#1740 in Algorithms
Used in regenerator
43KB
878 lines
Fuzzerang
Useful random generators and distributions for use in fuzzers and mutators
Instead of being very random, very fast, or very secure, these generators
and distributions are designed to be useful for fuzzing and mutation by efficiently
utilizing available input data. For example, the default Standard
distribution
in the rand
crate wastes 31 bits of input for every boolean value generated.
In comparison, StandardBuffered
uses the input data more efficiently by consuming
only 1 bit for a boolean, the minimum number of bits to generate a value in a range, and so
on.
Examples
use fuzzerang::{StandardSeedableRng, StandardBuffered, Ranged};
use rand::{SeedableRng, distributions::Distribution};
// Use a constant seed of 8 bytes, or 64 bits
let mut rng = StandardSeedableRng::from_seed((0..255).take(8).collect());
let dist = StandardBuffered::new();
// We can generate 10 bools from 8 bytes of input because we're only using 1 bit each
for i in 0..10 {
let x: bool = dist.sample(&mut rng);
println!("{}: {}", i, x);
}
// In fact, we are so efficient we can generate some alphabetic characters too, which
// each use 4 bits
for i in 0..10 {
let x: char = dist.sample_range_inclusive(&mut rng, 'A'..='Z');
println!("{}: {}", i, x);
}
Dependencies
~1.5MB
~30K SLoC