1use super::{super::Vec, super::ZERO, Felt, MmrProof, Rpo256, Word};
 2
 3#[derive(Debug, Clone, PartialEq)]
 4pub struct MmrPeaks {
 5    /// The number of leaves is used to differentiate accumulators that have the same number of
 6    /// peaks. This happens because the number of peaks goes up-and-down as the structure is used
 7    /// causing existing trees to be merged and new ones to be created. As an example, every time
 8    /// the MMR has a power-of-two number of leaves there is a single peak.
 9    ///
10    /// Every tree in the MMR forest has a distinct power-of-two size, this means only the right
11    /// most tree can have an odd number of elements (e.g. `1`). Additionally this means that the bits in
12    /// `num_leaves` conveniently encode the size of each individual tree.
13    ///
14    /// Examples:
15    ///
16    ///    - With 5 leaves, the binary `0b101`. The number of set bits is equal the number
17    ///      of peaks, in this case there are 2 peaks. The 0-indexed least-significant position of
18    ///      the bit determines the number of elements of a tree, so the rightmost tree has `2**0`
19    ///      elements and the left most has `2**2`.
20    ///    - With 12 leaves, the binary is `0b1100`, this case also has 2 peaks, the
21    ///      leftmost tree has `2**3=8` elements, and the right most has `2**2=4` elements.
22    pub num_leaves: usize,
23
24    /// All the peaks of every tree in the MMR forest. The peaks are always ordered by number of
25    /// leaves, starting from the peak with most children, to the one with least.
26    ///
27    /// Invariant: The length of `peaks` must be equal to the number of true bits in `num_leaves`.
28    pub peaks: Vec<Word>,
29}
30
31impl MmrPeaks {
32    /// Hashes the peaks.
33    ///
34    /// The procedure will:
35    /// - Flatten and pad the peaks to a vector of Felts.
36    /// - Hash the vector of Felts.
37    pub fn hash_peaks(&self) -> Word {
38        Rpo256::hash_elements(&self.flatten_and_pad_peaks()).into()
39    }
40
41    pub fn verify(&self, value: Word, opening: MmrProof) -> bool {
42        let root = &self.peaks[opening.peak_index()];
43        opening.merkle_path.verify(opening.relative_pos() as u64, value, root)
44    }
45
46    /// Flattens and pads the peaks to make hashing inside of the Miden VM easier.
47    ///
48    /// The procedure will:
49    /// - Flatten the vector of Words into a vector of Felts.
50    /// - Pad the peaks with ZERO to an even number of words, this removes the need to handle RPO
51    ///   padding.
52    /// - Pad the peaks to a minimum length of 16 words, which reduces the constant cost of
53    ///   hashing.
54    pub fn flatten_and_pad_peaks(&self) -> Vec<Felt> {
55        let num_peaks = self.peaks.len();
56
57        // To achieve the padding rules above we calculate the length of the final vector.
58        // This is calculated as the number of field elements. Each peak is 4 field elements.
59        // The length is calculated as follows:
60        // - If there are less than 16 peaks, the data is padded to 16 peaks and as such requires
61        //   64 field elements.
62        // - If there are more than 16 peaks and the number of peaks is odd, the data is padded to
63        //   an even number of peaks and as such requires `(num_peaks + 1) * 4` field elements.
64        // - If there are more than 16 peaks and the number of peaks is even, the data is not padded
65        //   and as such requires `num_peaks * 4` field elements.
66        let len = if num_peaks < 16 {
67            64
68        } else if num_peaks % 2 == 1 {
69            (num_peaks + 1) * 4
70        } else {
71            num_peaks * 4
72        };
73
74        let mut elements = Vec::with_capacity(len);
75        elements.extend_from_slice(&self.peaks.as_slice().concat());
76        elements.resize(len, ZERO);
77        elements
78    }
79}