miden-crypto/src/merkle/mmr/full.rs

389 lines
14 KiB
Rust

//! A fully materialized Merkle mountain range (MMR).
//!
//! A MMR is a forest structure, i.e. it is an ordered set of disjoint rooted trees. The trees are
//! ordered by size, from the most to least number of leaves. Every tree is a perfect binary tree,
//! meaning a tree has all its leaves at the same depth, and every inner node has a branch-factor
//! of 2 with both children set.
//!
//! Additionally the structure only supports adding leaves to the right-most tree, the one with the
//! least number of leaves. The structure preserves the invariant that each tree has different
//! depths, i.e. as part of adding adding a new element to the forest the trees with same depth are
//! merged, creating a new tree with depth d+1, this process is continued until the property is
//! restabilished.
use super::{
super::{InnerNodeInfo, MerklePath, RpoDigest, Vec},
bit::TrueBitPositionIterator,
MmrPeaks, MmrProof, Rpo256,
};
use core::fmt::{Display, Formatter};
#[cfg(feature = "std")]
use std::error::Error;
// MMR
// ===============================================================================================
/// A fully materialized Merkle Mountain Range, with every tree in the forest and all their
/// elements.
///
/// Since this is a full representation of the MMR, elements are never removed and the MMR will
/// grow roughly `O(2n)` in number of leaf elements.
pub struct Mmr {
/// Refer to the `forest` method documentation for details of the semantics of this value.
pub(super) forest: usize,
/// Contains every element of the forest.
///
/// The trees are in postorder sequential representation. This representation allows for all
/// the elements of every tree in the forest to be stored in the same sequential buffer. It
/// also means new elements can be added to the forest, and merging of trees is very cheap with
/// no need to copy elements.
pub(super) nodes: Vec<RpoDigest>,
}
#[derive(Debug, PartialEq, Eq, Copy, Clone)]
pub enum MmrError {
InvalidPosition(usize),
}
impl Display for MmrError {
fn fmt(&self, fmt: &mut Formatter<'_>) -> Result<(), core::fmt::Error> {
match self {
MmrError::InvalidPosition(pos) => write!(fmt, "Mmr does not contain position {pos}"),
}
}
}
#[cfg(feature = "std")]
impl Error for MmrError {}
impl Default for Mmr {
fn default() -> Self {
Self::new()
}
}
impl Mmr {
// CONSTRUCTORS
// ============================================================================================
/// Constructor for an empty `Mmr`.
pub fn new() -> Mmr {
Mmr {
forest: 0,
nodes: Vec::new(),
}
}
// ACCESSORS
// ============================================================================================
/// Returns the MMR forest representation.
///
/// The forest value has the following interpretations:
/// - its value is the number of elements in the forest
/// - bit count corresponds to the number of trees in the forest
/// - each true bit position determines the depth of a tree in the forest
pub const fn forest(&self) -> usize {
self.forest
}
// FUNCTIONALITY
// ============================================================================================
/// Given a leaf position, returns the Merkle path to its corresponding peak. If the position
/// is greater-or-equal than the tree size an error is returned.
///
/// Note: The leaf position is the 0-indexed number corresponding to the order the leaves were
/// added, this corresponds to the MMR size _prior_ to adding the element. So the 1st element
/// has position 0, the second position 1, and so on.
pub fn open(&self, pos: usize) -> Result<MmrProof, MmrError> {
// find the target tree responsible for the MMR position
let tree_bit =
leaf_to_corresponding_tree(pos, self.forest).ok_or(MmrError::InvalidPosition(pos))?;
let forest_target = 1usize << tree_bit;
// isolate the trees before the target
let forest_before = self.forest & high_bitmask(tree_bit + 1);
let index_offset = nodes_in_forest(forest_before);
// find the root
let index = nodes_in_forest(forest_target) - 1;
// update the value position from global to the target tree
let relative_pos = pos - forest_before;
// collect the path and the final index of the target value
let (_, path) =
self.collect_merkle_path_and_value(tree_bit, relative_pos, index_offset, index);
Ok(MmrProof {
forest: self.forest,
position: pos,
merkle_path: MerklePath::new(path),
})
}
/// Returns the leaf value at position `pos`.
///
/// Note: The leaf position is the 0-indexed number corresponding to the order the leaves were
/// added, this corresponds to the MMR size _prior_ to adding the element. So the 1st element
/// has position 0, the second position 1, and so on.
pub fn get(&self, pos: usize) -> Result<RpoDigest, MmrError> {
// find the target tree responsible for the MMR position
let tree_bit =
leaf_to_corresponding_tree(pos, self.forest).ok_or(MmrError::InvalidPosition(pos))?;
let forest_target = 1usize << tree_bit;
// isolate the trees before the target
let forest_before = self.forest & high_bitmask(tree_bit + 1);
let index_offset = nodes_in_forest(forest_before);
// find the root
let index = nodes_in_forest(forest_target) - 1;
// update the value position from global to the target tree
let relative_pos = pos - forest_before;
// collect the path and the final index of the target value
let (value, _) =
self.collect_merkle_path_and_value(tree_bit, relative_pos, index_offset, index);
Ok(value)
}
/// Adds a new element to the MMR.
pub fn add(&mut self, el: RpoDigest) {
// Note: every node is also a tree of size 1, adding an element to the forest creates a new
// rooted-tree of size 1. This may temporarily break the invariant that every tree in the
// forest has different sizes, the loop below will eagerly merge trees of same size and
// restore the invariant.
self.nodes.push(el);
let mut left_offset = self.nodes.len().saturating_sub(2);
let mut right = el;
let mut left_tree = 1;
while self.forest & left_tree != 0 {
right = Rpo256::merge(&[self.nodes[left_offset], right]);
self.nodes.push(right);
left_offset = left_offset.saturating_sub(nodes_in_forest(left_tree));
left_tree <<= 1;
}
self.forest += 1;
}
/// Returns an accumulator representing the current state of the MMR.
pub fn accumulator(&self) -> MmrPeaks {
let peaks: Vec<RpoDigest> = TrueBitPositionIterator::new(self.forest)
.rev()
.map(|bit| nodes_in_forest(1 << bit))
.scan(0, |offset, el| {
*offset += el;
Some(*offset)
})
.map(|offset| self.nodes[offset - 1])
.collect();
MmrPeaks {
num_leaves: self.forest,
peaks,
}
}
/// An iterator over inner nodes in the MMR. The order of iteration is unspecified.
pub fn inner_nodes(&self) -> MmrNodes {
MmrNodes {
mmr: self,
forest: 0,
last_right: 0,
index: 0,
}
}
// UTILITIES
// ============================================================================================
/// Internal function used to collect the Merkle path of a value.
fn collect_merkle_path_and_value(
&self,
tree_bit: u32,
relative_pos: usize,
index_offset: usize,
mut index: usize,
) -> (RpoDigest, Vec<RpoDigest>) {
// collect the Merkle path
let mut tree_depth = tree_bit as usize;
let mut path = Vec::with_capacity(tree_depth + 1);
while tree_depth > 0 {
let bit = relative_pos & tree_depth;
let right_offset = index - 1;
let left_offset = right_offset - nodes_in_forest(tree_depth);
// Elements to the right have a higher position because they were
// added later. Therefore when the bit is true the node's path is
// to the right, and its sibling to the left.
let sibling = if bit != 0 {
index = right_offset;
self.nodes[index_offset + left_offset]
} else {
index = left_offset;
self.nodes[index_offset + right_offset]
};
tree_depth >>= 1;
path.push(sibling);
}
// the rest of the codebase has the elements going from leaf to root, adjust it here for
// easy of use/consistency sake
path.reverse();
let value = self.nodes[index_offset + index];
(value, path)
}
}
impl<T> From<T> for Mmr
where
T: IntoIterator<Item = RpoDigest>,
{
fn from(values: T) -> Self {
let mut mmr = Mmr::new();
for v in values {
mmr.add(v)
}
mmr
}
}
// ITERATOR
// ===============================================================================================
/// Yields inner nodes of the [Mmr].
pub struct MmrNodes<'a> {
/// [Mmr] being yielded, when its `forest` value is matched, the iterations is finished.
mmr: &'a Mmr,
/// Keeps track of the left nodes yielded so far waiting for a right pair, this matches the
/// semantics of the [Mmr]'s forest attribute, since that too works as a buffer of left nodes
/// waiting for a pair to be hashed together.
forest: usize,
/// Keeps track of the last right node yielded, after this value is set, the next iteration
/// will be its parent with its corresponding left node that has been yield already.
last_right: usize,
/// The current index in the `nodes` vector.
index: usize,
}
impl<'a> Iterator for MmrNodes<'a> {
type Item = InnerNodeInfo;
fn next(&mut self) -> Option<Self::Item> {
debug_assert!(self.last_right.count_ones() <= 1, "last_right tracks zero or one element");
// only parent nodes are emitted, remove the single node tree from the forest
let target = self.mmr.forest & (usize::MAX << 1);
if self.forest < target {
if self.last_right == 0 {
// yield the left leaf
debug_assert!(self.last_right == 0, "left must be before right");
self.forest |= 1;
self.index += 1;
// yield the right leaf
debug_assert!((self.forest & 1) == 1, "right must be after left");
self.last_right |= 1;
self.index += 1;
};
debug_assert!(
self.forest & self.last_right != 0,
"parent requires both a left and right",
);
// compute the number of nodes in the right tree, this is the offset to the
// previous left parent
let right_nodes = nodes_in_forest(self.last_right);
// the next parent position is one above the position of the pair
let parent = self.last_right << 1;
// the left node has been paired and the current parent yielded, removed it from the forest
self.forest ^= self.last_right;
if self.forest & parent == 0 {
// this iteration yielded the left parent node
debug_assert!(self.forest & 1 == 0, "next iteration yields a left leaf");
self.last_right = 0;
self.forest ^= parent;
} else {
// the left node of the parent level has been yielded already, this iteration
// was the right parent. Next iteration yields their parent.
self.last_right = parent;
}
// yields a parent
let value = self.mmr.nodes[self.index];
let right = self.mmr.nodes[self.index - 1];
let left = self.mmr.nodes[self.index - 1 - right_nodes];
self.index += 1;
let node = InnerNodeInfo { value, left, right };
Some(node)
} else {
None
}
}
}
// UTILITIES
// ===============================================================================================
/// Given a 0-indexed leaf position and the current forest, return the tree number responsible for
/// the position.
///
/// Note:
/// The result is a tree position `p`, it has the following interpretations. $p+1$ is the depth of
/// the tree, which corresponds to the size of a Merkle proof for that tree. $2^p$ is equal to the
/// number of leaves in this particular tree. and $2^(p+1)-1$ corresponds to size of the tree.
pub(crate) const fn leaf_to_corresponding_tree(pos: usize, forest: usize) -> Option<u32> {
if pos >= forest {
None
} else {
// - each bit in the forest is a unique tree and the bit position its power-of-two size
// - each tree owns a consecutive range of positions equal to its size from left-to-right
// - this means the first tree owns from `0` up to the `2^k_0` first positions, where `k_0`
// is the highest true bit position, the second tree from `2^k_0 + 1` up to `2^k_1` where
// `k_1` is the second higest bit, so on.
// - this means the highest bits work as a category marker, and the position is owned by
// the first tree which doesn't share a high bit with the position
let before = forest & pos;
let after = forest ^ before;
let tree = after.ilog2();
Some(tree)
}
}
/// Return a bitmask for the bits including and above the given position.
pub(crate) const fn high_bitmask(bit: u32) -> usize {
if bit > usize::BITS - 1 {
0
} else {
usize::MAX << bit
}
}
/// Return the total number of nodes of a given forest
///
/// Panics:
///
/// This will panic if the forest has size greater than `usize::MAX / 2`
pub(crate) const fn nodes_in_forest(forest: usize) -> usize {
// - the size of a perfect binary tree is $2^{k+1}-1$ or $2*2^k-1$
// - the forest represents the sum of $2^k$ so a single multiplication is necessary
// - the number of `-1` is the same as the number of trees, which is the same as the number
// bits set
let tree_count = forest.count_ones() as usize;
forest * 2 - tree_count
}