| 1 | /// Taken from SMHasher. | 
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| 2 |  | 
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| 3 | //----------------------------------------------------------------------------- | 
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| 4 | // Flipping a single bit of a key should cause an "avalanche" of changes in | 
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| 5 | // the hash function's output. Ideally, each output bits should flip 50% of | 
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| 6 | // the time - if the probability of an output bit flipping is not 50%, that bit | 
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| 7 | // is "biased". Too much bias means that patterns applied to the input will | 
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| 8 | // cause "echoes" of the patterns in the output, which in turn can cause the | 
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| 9 | // hash function to fail to create an even, random distribution of hash values. | 
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| 10 |  | 
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| 11 |  | 
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| 12 | #pragma once | 
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| 13 |  | 
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| 14 | #include "Random.h" | 
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| 15 |  | 
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| 16 | #include <vector> | 
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| 17 | #include <math.h> | 
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| 18 | #include <stdio.h> | 
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| 19 |  | 
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| 20 | // Avalanche fails if a bit is biased by more than 1% | 
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| 21 |  | 
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| 22 | #define AVALANCHE_FAIL 0.01 | 
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| 23 |  | 
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| 24 | double maxBias(std::vector<int> & counts, int reps); | 
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| 25 |  | 
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| 26 | typedef void (*pfHash)(const void * blob, const int len, const uint32_t seed, void * out); | 
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| 27 |  | 
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| 28 |  | 
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| 29 | inline uint32_t getbit(const void * block, int len, uint32_t bit) | 
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| 30 | { | 
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| 31 | uint8_t * b = reinterpret_cast<uint8_t *>(const_cast<void *>(block)); | 
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| 32 |  | 
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| 33 | int byte = bit >> 3; | 
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| 34 | bit = bit & 0x7; | 
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| 35 |  | 
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| 36 | if (byte < len) | 
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| 37 | return (b[byte] >> bit) & 1; | 
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| 38 |  | 
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| 39 | return 0; | 
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| 40 | } | 
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| 41 |  | 
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| 42 | template <typename T> | 
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| 43 | inline uint32_t getbit(T & blob, uint32_t bit) | 
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| 44 | { | 
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| 45 | return getbit(&blob, sizeof(blob), bit); | 
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| 46 | } | 
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| 47 |  | 
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| 48 | inline void flipbit(void * block, int len, uint32_t bit) | 
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| 49 | { | 
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| 50 | uint8_t * b = reinterpret_cast<uint8_t *>(block); | 
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| 51 |  | 
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| 52 | int byte = bit >> 3; | 
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| 53 | bit = bit & 0x7; | 
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| 54 |  | 
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| 55 | if (byte < len) | 
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| 56 | b[byte] ^= (1 << bit); | 
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| 57 | } | 
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| 58 |  | 
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| 59 | template <typename T> | 
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| 60 | inline void flipbit(T & blob, uint32_t bit) | 
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| 61 | { | 
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| 62 | flipbit(&blob, sizeof(blob), bit); | 
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| 63 | } | 
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| 64 |  | 
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| 65 | //----------------------------------------------------------------------------- | 
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| 66 |  | 
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| 67 | template <typename keytype, typename hashtype> | 
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| 68 | void calcBias(pfHash hash, std::vector<int> & counts, int reps, Rand & r) | 
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| 69 | { | 
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| 70 | const int keybytes = sizeof(keytype); | 
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| 71 | const int hashbytes = sizeof(hashtype); | 
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| 72 |  | 
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| 73 | const int keybits = keybytes * 8; | 
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| 74 | const int hashbits = hashbytes * 8; | 
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| 75 |  | 
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| 76 | keytype K; | 
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| 77 | hashtype A, B; | 
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| 78 |  | 
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| 79 | for (int irep = 0; irep < reps; irep++) | 
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| 80 | { | 
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| 81 | if (irep % (reps / 10) == 0) | 
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| 82 | printf( "."); | 
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| 83 |  | 
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| 84 | r.rand_p(&K, keybytes); | 
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| 85 |  | 
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| 86 | hash(&K, keybytes, 0, &A); | 
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| 87 |  | 
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| 88 | int * cursor = counts.data(); | 
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| 89 |  | 
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| 90 | for (int iBit = 0; iBit < keybits; iBit++) | 
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| 91 | { | 
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| 92 | flipbit(&K, keybytes, iBit); | 
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| 93 | hash(&K, keybytes, 0, &B); | 
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| 94 | flipbit(&K, keybytes, iBit); | 
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| 95 |  | 
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| 96 | for (int iOut = 0; iOut < hashbits; iOut++) | 
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| 97 | { | 
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| 98 | int bitA = getbit(&A, hashbytes, iOut); | 
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| 99 | int bitB = getbit(&B, hashbytes, iOut); | 
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| 100 |  | 
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| 101 | (*cursor++) += (bitA ^ bitB); | 
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| 102 | } | 
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| 103 | } | 
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| 104 | } | 
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| 105 | } | 
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| 106 |  | 
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| 107 | //----------------------------------------------------------------------------- | 
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| 108 |  | 
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| 109 | template <typename keytype, typename hashtype> | 
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| 110 | bool AvalancheTest(pfHash hash, const int reps) | 
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| 111 | { | 
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| 112 | Rand r(48273); | 
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| 113 |  | 
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| 114 | const int keybytes = sizeof(keytype); | 
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| 115 | const int hashbytes = sizeof(hashtype); | 
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| 116 |  | 
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| 117 | const int keybits = keybytes * 8; | 
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| 118 | const int hashbits = hashbytes * 8; | 
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| 119 |  | 
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| 120 | printf( "Testing %3d-bit keys -> %3d-bit hashes, %8d reps", keybits, hashbits, reps); | 
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| 121 |  | 
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| 122 | //---------- | 
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| 123 |  | 
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| 124 | std::vector<int> bins(keybits * hashbits, 0); | 
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| 125 |  | 
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| 126 | calcBias<keytype, hashtype>(hash, bins, reps, r); | 
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| 127 |  | 
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| 128 | //---------- | 
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| 129 |  | 
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| 130 | bool result = true; | 
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| 131 |  | 
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| 132 | double b = maxBias(bins, reps); | 
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| 133 |  | 
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| 134 | printf( " worst bias is %f%%", b * 100.0); | 
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| 135 |  | 
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| 136 | if (b > AVALANCHE_FAIL) | 
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| 137 | { | 
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| 138 | printf( " !!!!! "); | 
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| 139 | result = false; | 
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| 140 | } | 
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| 141 |  | 
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| 142 | printf( "\n"); | 
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| 143 |  | 
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| 144 | return result; | 
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| 145 | } | 
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| 146 |  | 
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| 147 |  | 
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| 148 | //----------------------------------------------------------------------------- | 
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| 149 | // BIC test variant - store all intermediate data in a table, draw diagram | 
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| 150 | // afterwards (much faster) | 
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| 151 |  | 
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| 152 | template <typename keytype, typename hashtype> | 
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| 153 | void BicTest3(pfHash hash, const int reps, bool verbose = true) | 
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| 154 | { | 
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| 155 | const int keybytes = sizeof(keytype); | 
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| 156 | const int keybits = keybytes * 8; | 
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| 157 | const int hashbytes = sizeof(hashtype); | 
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| 158 | const int hashbits = hashbytes * 8; | 
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| 159 | const int pagesize = hashbits * hashbits * 4; | 
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| 160 |  | 
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| 161 | Rand r(11938); | 
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| 162 |  | 
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| 163 | double maxBias = 0; | 
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| 164 | int maxK = 0; | 
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| 165 | int maxA = 0; | 
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| 166 | int maxB = 0; | 
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| 167 |  | 
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| 168 | keytype key; | 
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| 169 | hashtype h1, h2; | 
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| 170 |  | 
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| 171 | std::vector<int> bins(keybits * pagesize, 0); | 
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| 172 |  | 
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| 173 | for (int keybit = 0; keybit < keybits; keybit++) | 
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| 174 | { | 
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| 175 | if (keybit % (keybits / 10) == 0) | 
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| 176 | printf( "."); | 
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| 177 |  | 
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| 178 | int * page = &bins[keybit * pagesize]; | 
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| 179 |  | 
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| 180 | for (int irep = 0; irep < reps; irep++) | 
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| 181 | { | 
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| 182 | r.rand_p(&key, keybytes); | 
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| 183 | hash(&key, keybytes, 0, &h1); | 
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| 184 | flipbit(key, keybit); | 
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| 185 | hash(&key, keybytes, 0, &h2); | 
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| 186 |  | 
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| 187 | hashtype d = h1 ^ h2; | 
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| 188 |  | 
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| 189 | for (int out1 = 0; out1 < hashbits - 1; out1++) | 
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| 190 | for (int out2 = out1 + 1; out2 < hashbits; out2++) | 
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| 191 | { | 
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| 192 | int * b = &page[(out1 * hashbits + out2) * 4]; | 
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| 193 |  | 
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| 194 | uint32_t x = getbit(d, out1) | (getbit(d, out2) << 1); | 
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| 195 |  | 
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| 196 | b[x]++; | 
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| 197 | } | 
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| 198 | } | 
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| 199 | } | 
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| 200 |  | 
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| 201 | printf( "\n"); | 
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| 202 |  | 
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| 203 | for (int out1 = 0; out1 < hashbits - 1; out1++) | 
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| 204 | { | 
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| 205 | for (int out2 = out1 + 1; out2 < hashbits; out2++) | 
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| 206 | { | 
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| 207 | if (verbose) | 
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| 208 | printf( "(%3d,%3d) - ", out1, out2); | 
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| 209 |  | 
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| 210 | for (int keybit = 0; keybit < keybits; keybit++) | 
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| 211 | { | 
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| 212 | int * page = &bins[keybit * pagesize]; | 
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| 213 | int * bins_in_page = &page[(out1 * hashbits + out2) * 4]; | 
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| 214 |  | 
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| 215 | double bias = 0; | 
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| 216 |  | 
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| 217 | for (int b = 0; b < 4; b++) | 
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| 218 | { | 
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| 219 | double b2 = static_cast<double>(bins_in_page[b]) / static_cast<double>(reps / 2); | 
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| 220 | b2 = fabs(b2 * 2 - 1); | 
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| 221 |  | 
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| 222 | if (b2 > bias) | 
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| 223 | bias = b2; | 
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| 224 | } | 
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| 225 |  | 
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| 226 | if (bias > maxBias) | 
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| 227 | { | 
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| 228 | maxBias = bias; | 
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| 229 | maxK = keybit; | 
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| 230 | maxA = out1; | 
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| 231 | maxB = out2; | 
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| 232 | } | 
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| 233 |  | 
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| 234 | if (verbose) | 
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| 235 | { | 
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| 236 | if (bias < 0.01) | 
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| 237 | printf( "."); | 
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| 238 | else if (bias < 0.05) | 
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| 239 | printf( "o"); | 
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| 240 | else if (bias < 0.33) | 
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| 241 | printf( "O"); | 
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| 242 | else | 
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| 243 | printf( "X"); | 
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| 244 | } | 
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| 245 | } | 
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| 246 |  | 
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| 247 | // Finished keybit | 
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| 248 |  | 
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| 249 | if (verbose) | 
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| 250 | printf( "\n"); | 
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| 251 | } | 
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| 252 |  | 
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| 253 | if (verbose) | 
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| 254 | { | 
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| 255 | for (int i = 0; i < keybits + 12; i++) | 
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| 256 | printf( "-"); | 
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| 257 | printf( "\n"); | 
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| 258 | } | 
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| 259 | } | 
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| 260 |  | 
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| 261 | printf( "Max bias %f - (%3d : %3d,%3d)\n", maxBias, maxK, maxA, maxB); | 
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| 262 | } | 
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| 263 |  | 
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| 264 | //----------------------------------------------------------------------------- | 
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| 265 |  | 
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