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-rw-r--r--testing/mozharness/test/test_mozilla_merkle.py134
1 files changed, 134 insertions, 0 deletions
diff --git a/testing/mozharness/test/test_mozilla_merkle.py b/testing/mozharness/test/test_mozilla_merkle.py
new file mode 100644
index 0000000000..226499142f
--- /dev/null
+++ b/testing/mozharness/test/test_mozilla_merkle.py
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+import codecs
+import hashlib
+import random
+import unittest
+
+from mozharness.mozilla.merkle import InclusionProof, MerkleTree
+
+decode_hex = codecs.getdecoder("hex_codec")
+encode_hex = codecs.getencoder("hex_codec")
+
+# Pre-computed tree on 7 inputs
+#
+# ______F_____
+# / \
+# __D__ _E_
+# / \ / \
+# A B C |
+# / \ / \ / \ |
+# 0 1 2 3 4 5 6
+hash_fn = hashlib.sha256
+
+data = [
+ decode_hex("fbc459361fc111024c6d1fd83d23a9ff")[0],
+ decode_hex("ae3a44925afec860451cd8658b3cadde")[0],
+ decode_hex("418903fe6ef29fc8cab93d778a7b018b")[0],
+ decode_hex("3d1c53c00b2e137af8c4c23a06388c6b")[0],
+ decode_hex("e656ebd8e2758bc72599e5896be357be")[0],
+ decode_hex("81aae91cf90be172eedd1c75c349bf9e")[0],
+ decode_hex("00c262edf8b0bc345aca769e8733e25e")[0],
+]
+
+leaves = [
+ decode_hex("5cb551f87797381a24a5359a986e2cef25b1f2113b387197fe48e8babc9ad5c7")[0],
+ decode_hex("9899dc0be00306bda2a8e69cec32525ca6244f132479bcf840d8c1bc8bdfbff2")[0],
+ decode_hex("fdd27d0393e32637b474efb9b3efad29568c3ec9b091fdda40fd57ec9196f06d")[0],
+ decode_hex("c87292a6c8528c2a0679b6c1eefb47e4dbac7840d23645d5b7cb47cf1a8d365f")[0],
+ decode_hex("2ff3bdac9bec3580b82da8a357746f15919414d9cbe517e2dd96910c9814c30c")[0],
+ decode_hex("883e318240eccc0e2effafebdb0fd4fd26d0996da1b01439566cb9babef8725f")[0],
+ decode_hex("bb13dfb7b202a95f241ea1715c8549dc048d9936ec747028002f7c795de72fcf")[0],
+]
+
+nodeA = decode_hex("06447a7baa079cb0b4b6119d0f575bec508915403fdc30923eba982b63759805")[
+ 0
+]
+nodeB = decode_hex("3db98027c655ead4fe897bef3a4b361839a337941a9e624b475580c9d4e882ee")[
+ 0
+]
+nodeC = decode_hex("17524f8b0169b2745c67846925d55449ae80a8022ef8189dcf4cbb0ec7fcc470")[
+ 0
+]
+nodeD = decode_hex("380d0dc6fd7d4f37859a12dbfc7171b3cce29ab0688c6cffd2b15f3e0b21af49")[
+ 0
+]
+nodeE = decode_hex("3a9c2886a5179a6e1948876034f99d52a8f393f47a09887adee6d1b4a5c5fbd6")[
+ 0
+]
+nodeF = decode_hex("d1a0d3947db4ae8305f2ac32985957e02659b2ea3c10da52a48d2526e9af3bbc")[
+ 0
+]
+
+proofs = [
+ [leaves[1], nodeB, nodeE],
+ [leaves[0], nodeB, nodeE],
+ [leaves[3], nodeA, nodeE],
+ [leaves[2], nodeA, nodeE],
+ [leaves[5], leaves[6], nodeD],
+ [leaves[4], leaves[6], nodeD],
+ [nodeC, nodeD],
+]
+
+known_proof5 = decode_hex(
+ "020000"
+ + "0000000000000007"
+ + "0000000000000005"
+ + "0063"
+ + "20"
+ + encode_hex(leaves[4])[0].decode()
+ + "20"
+ + encode_hex(leaves[6])[0].decode()
+ + "20"
+ + encode_hex(nodeD)[0].decode()
+)[0]
+
+
+class TestMerkleTree(unittest.TestCase):
+ def testPreComputed(self):
+ tree = MerkleTree(hash_fn, data)
+ head = tree.head()
+ self.assertEqual(head, nodeF)
+
+ for i in range(len(data)):
+ proof = tree.inclusion_proof(i)
+
+ self.assertTrue(proof.verify(hash_fn, data[i], i, len(data), head))
+ self.assertEqual(proof.leaf_index, i)
+ self.assertEqual(proof.tree_size, tree.n)
+ self.assertEqual(proof.path_elements, proofs[i])
+
+ def testInclusionProofEncodeDecode(self):
+ tree = MerkleTree(hash_fn, data)
+
+ # Inclusion proof encode/decode round trip test
+ proof5 = tree.inclusion_proof(5)
+ serialized5 = proof5.to_rfc6962_bis()
+ deserialized5 = InclusionProof.from_rfc6962_bis(serialized5)
+ reserialized5 = deserialized5.to_rfc6962_bis()
+ self.assertEqual(serialized5, reserialized5)
+
+ # Inclusion proof encode known answer test
+ serialized5 = proof5.to_rfc6962_bis()
+ self.assertEqual(serialized5, known_proof5)
+
+ # Inclusion proof decode known answer test
+ known_deserialized5 = InclusionProof.from_rfc6962_bis(known_proof5)
+ self.assertEqual(proof5.leaf_index, known_deserialized5.leaf_index)
+ self.assertEqual(proof5.tree_size, known_deserialized5.tree_size)
+ self.assertEqual(proof5.path_elements, known_deserialized5.path_elements)
+
+ def testLargeTree(self):
+ TEST_SIZE = 5000
+ ELEM_SIZE_BYTES = 16
+ data = [
+ bytearray(random.getrandbits(8) for _ in range(ELEM_SIZE_BYTES))
+ for _ in range(TEST_SIZE)
+ ]
+ tree = MerkleTree(hash_fn, data)
+ head = tree.head()
+
+ for i in range(len(data)):
+ proof = tree.inclusion_proof(i)
+
+ self.assertTrue(proof.verify(hash_fn, data[i], i, len(data), head))
+ self.assertEqual(proof.leaf_index, i)
+ self.assertEqual(proof.tree_size, tree.n)