diff --git a/src/bloom.cpp b/src/bloom.cpp
index 36a6e606a..856a65325 100644
--- a/src/bloom.cpp
+++ b/src/bloom.cpp
@@ -1,329 +1,318 @@
 // Copyright (c) 2012-2016 The Bitcoin Core developers
 // Distributed under the MIT software license, see the accompanying
 // file COPYING or http://www.opensource.org/licenses/mit-license.php.
 
 #include <bloom.h>
 
 #include <hash.h>
 #include <primitives/transaction.h>
 #include <random.h>
 #include <script/script.h>
 #include <script/standard.h>
 #include <streams.h>
 
 #include <cmath>
 #include <cstdlib>
 
 #include <algorithm>
 
 #define LN2SQUARED 0.4804530139182014246671025263266649717305529515945455
 #define LN2 0.6931471805599453094172321214581765680755001343602552
 
 /**
  * The ideal size for a bloom filter with a given number of elements and false
  * positive rate is:
  * - nElements * log(fp rate) / ln(2)^2
  * We ignore filter parameters which will create a bloom filter larger than the
  * protocol limits
  *
  * The ideal number of hash functions is filter size * ln(2) / number of
  * elements. Again, we ignore filter parameters which will create a bloom filter
  * with more hash functions than the protocol limits.
  * See https://en.wikipedia.org/wiki/Bloom_filter for an explanation of these
  * formulas.
  */
 CBloomFilter::CBloomFilter(const uint32_t nElements, const double nFPRate,
                            const uint32_t nTweakIn, uint8_t nFlagsIn)
     : vData(std::min<uint32_t>(-1 / LN2SQUARED * nElements * log(nFPRate),
                                MAX_BLOOM_FILTER_SIZE * 8) /
             8),
       isFull(false), isEmpty(true),
       nHashFuncs(std::min<uint32_t>(vData.size() * 8 / nElements * LN2,
                                     MAX_HASH_FUNCS)),
       nTweak(nTweakIn), nFlags(nFlagsIn) {}
 
 inline uint32_t
 CBloomFilter::Hash(uint32_t nHashNum,
                    const std::vector<uint8_t> &vDataToHash) const {
     // 0xFBA4C795 chosen as it guarantees a reasonable bit difference between
     // nHashNum values.
     return MurmurHash3(nHashNum * 0xFBA4C795 + nTweak, vDataToHash) %
            (vData.size() * 8);
 }
 
 void CBloomFilter::insert(const std::vector<uint8_t> &vKey) {
     if (isFull) {
         return;
     }
 
     for (uint32_t i = 0; i < nHashFuncs; i++) {
         uint32_t nIndex = Hash(i, vKey);
         // Sets bit nIndex of vData
         vData[nIndex >> 3] |= (1 << (7 & nIndex));
     }
     isEmpty = false;
 }
 
 void CBloomFilter::insert(const COutPoint &outpoint) {
     CDataStream stream(SER_NETWORK, PROTOCOL_VERSION);
     stream << outpoint;
     std::vector<uint8_t> data(stream.begin(), stream.end());
     insert(data);
 }
 
 void CBloomFilter::insert(const uint256 &hash) {
     std::vector<uint8_t> data(hash.begin(), hash.end());
     insert(data);
 }
 
 bool CBloomFilter::contains(const std::vector<uint8_t> &vKey) const {
     if (isFull) {
         return true;
     }
     if (isEmpty) {
         return false;
     }
     for (uint32_t i = 0; i < nHashFuncs; i++) {
         uint32_t nIndex = Hash(i, vKey);
         // Checks bit nIndex of vData
         if (!(vData[nIndex >> 3] & (1 << (7 & nIndex)))) {
             return false;
         }
     }
     return true;
 }
 
 bool CBloomFilter::contains(const COutPoint &outpoint) const {
     CDataStream stream(SER_NETWORK, PROTOCOL_VERSION);
     stream << outpoint;
     std::vector<uint8_t> data(stream.begin(), stream.end());
     return contains(data);
 }
 
 bool CBloomFilter::contains(const uint256 &hash) const {
     std::vector<uint8_t> data(hash.begin(), hash.end());
     return contains(data);
 }
 
-void CBloomFilter::clear() {
-    vData.assign(vData.size(), 0);
-    isFull = false;
-    isEmpty = true;
-}
-
-void CBloomFilter::reset(const uint32_t nNewTweak) {
-    clear();
-    nTweak = nNewTweak;
-}
-
 bool CBloomFilter::IsWithinSizeConstraints() const {
     return vData.size() <= MAX_BLOOM_FILTER_SIZE &&
            nHashFuncs <= MAX_HASH_FUNCS;
 }
 
 bool CBloomFilter::MatchAndInsertOutputs(const CTransaction &tx) {
     bool fFound = false;
     // Match if the filter contains the hash of tx for finding tx when they
     // appear in a block
     if (isFull) {
         return true;
     }
     if (isEmpty) {
         return false;
     }
 
     const TxId &txid = tx.GetId();
     if (contains(txid)) {
         fFound = true;
     }
 
     for (size_t i = 0; i < tx.vout.size(); i++) {
         const CTxOut &txout = tx.vout[i];
         // Match if the filter contains any arbitrary script data element in any
         // scriptPubKey in tx. If this matches, also add the specific output
         // that was matched. This means clients don't have to update the filter
         // themselves when a new relevant tx is discovered in order to find
         // spending transactions, which avoids round-tripping and race
         // conditions.
         CScript::const_iterator pc = txout.scriptPubKey.begin();
         std::vector<uint8_t> data;
         while (pc < txout.scriptPubKey.end()) {
             opcodetype opcode;
             if (!txout.scriptPubKey.GetOp(pc, opcode, data)) {
                 break;
             }
             if (data.size() != 0 && contains(data)) {
                 fFound = true;
                 if ((nFlags & BLOOM_UPDATE_MASK) == BLOOM_UPDATE_ALL) {
                     insert(COutPoint(txid, i));
                 } else if ((nFlags & BLOOM_UPDATE_MASK) ==
                            BLOOM_UPDATE_P2PUBKEY_ONLY) {
                     std::vector<std::vector<uint8_t>> vSolutions;
                     txnouttype type = Solver(txout.scriptPubKey, vSolutions);
                     if (type == TX_PUBKEY || type == TX_MULTISIG) {
                         insert(COutPoint(txid, i));
                     }
                 }
                 break;
             }
         }
     }
 
     return fFound;
 }
 
 bool CBloomFilter::MatchInputs(const CTransaction &tx) {
     if (isEmpty) {
         return false;
     }
 
     for (const CTxIn &txin : tx.vin) {
         // Match if the filter contains an outpoint tx spends
         if (contains(txin.prevout)) {
             return true;
         }
 
         // Match if the filter contains any arbitrary script data element in any
         // scriptSig in tx
         CScript::const_iterator pc = txin.scriptSig.begin();
         std::vector<uint8_t> data;
         while (pc < txin.scriptSig.end()) {
             opcodetype opcode;
             if (!txin.scriptSig.GetOp(pc, opcode, data)) {
                 break;
             }
             if (data.size() != 0 && contains(data)) {
                 return true;
             }
         }
     }
 
     return false;
 }
 
 void CBloomFilter::UpdateEmptyFull() {
     bool full = true;
     bool empty = true;
     for (const auto d : vData) {
         full &= (d == 0xff);
         empty &= (d == 0);
     }
     isFull = full;
     isEmpty = empty;
 }
 
 CRollingBloomFilter::CRollingBloomFilter(const uint32_t nElements,
                                          const double fpRate) {
     double logFpRate = log(fpRate);
     /* The optimal number of hash functions is log(fpRate) / log(0.5), but
      * restrict it to the range 1-50. */
     nHashFuncs = std::max(1, std::min<int>(round(logFpRate / log(0.5)), 50));
     /* In this rolling bloom filter, we'll store between 2 and 3 generations of
      * nElements / 2 entries. */
     nEntriesPerGeneration = (nElements + 1) / 2;
     uint32_t nMaxElements = nEntriesPerGeneration * 3;
     /* The maximum fpRate = pow(1.0 - exp(-nHashFuncs * nMaxElements /
      * nFilterBits), nHashFuncs)
      * =>          pow(fpRate, 1.0 / nHashFuncs) = 1.0 - exp(-nHashFuncs *
      * nMaxElements / nFilterBits)
      * =>          1.0 - pow(fpRate, 1.0 / nHashFuncs) = exp(-nHashFuncs *
      * nMaxElements / nFilterBits)
      * =>          log(1.0 - pow(fpRate, 1.0 / nHashFuncs)) = -nHashFuncs *
      * nMaxElements / nFilterBits
      * =>          nFilterBits = -nHashFuncs * nMaxElements / log(1.0 -
      * pow(fpRate, 1.0 / nHashFuncs))
      * =>          nFilterBits = -nHashFuncs * nMaxElements / log(1.0 -
      * exp(logFpRate / nHashFuncs))
      */
     uint32_t nFilterBits =
         uint32_t(ceil(-1.0 * nHashFuncs * nMaxElements /
                       log(1.0 - exp(logFpRate / nHashFuncs))));
     data.clear();
     /* For each data element we need to store 2 bits. If both bits are 0, the
      * bit is treated as unset. If the bits are (01), (10), or (11), the bit is
      * treated as set in generation 1, 2, or 3 respectively. These bits are
      * stored in separate integers: position P corresponds to bit (P & 63) of
      * the integers data[(P >> 6) * 2] and data[(P >> 6) * 2 + 1]. */
     data.resize(((nFilterBits + 63) / 64) << 1);
     reset();
 }
 
 /* Similar to CBloomFilter::Hash */
 static inline uint32_t
 RollingBloomHash(uint32_t nHashNum, uint32_t nTweak,
                  const std::vector<uint8_t> &vDataToHash) {
     return MurmurHash3(nHashNum * 0xFBA4C795 + nTweak, vDataToHash);
 }
 
 // A replacement for x % n. This assumes that x and n are 32bit integers, and x
 // is a uniformly random distributed 32bit value which should be the case for a
 // good hash. See
 // https://lemire.me/blog/2016/06/27/a-fast-alternative-to-the-modulo-reduction/
 static inline uint32_t FastMod(uint32_t x, size_t n) {
     return (uint64_t(x) * uint64_t(n)) >> 32;
 }
 
 void CRollingBloomFilter::insert(const std::vector<uint8_t> &vKey) {
     if (nEntriesThisGeneration == nEntriesPerGeneration) {
         nEntriesThisGeneration = 0;
         nGeneration++;
         if (nGeneration == 4) {
             nGeneration = 1;
         }
         uint64_t nGenerationMask1 = 0 - uint64_t(nGeneration & 1);
         uint64_t nGenerationMask2 = 0 - uint64_t(nGeneration >> 1);
         /* Wipe old entries that used this generation number. */
         for (uint32_t p = 0; p < data.size(); p += 2) {
             uint64_t p1 = data[p], p2 = data[p + 1];
             uint64_t mask = (p1 ^ nGenerationMask1) | (p2 ^ nGenerationMask2);
             data[p] = p1 & mask;
             data[p + 1] = p2 & mask;
         }
     }
     nEntriesThisGeneration++;
 
     for (int n = 0; n < nHashFuncs; n++) {
         uint32_t h = RollingBloomHash(n, nTweak, vKey);
         int bit = h & 0x3F;
         /* FastMod works with the upper bits of h, so it is safe to ignore that
          * the lower bits of h are already used for bit. */
         uint32_t pos = FastMod(h, data.size());
         /* The lowest bit of pos is ignored, and set to zero for the first bit,
          * and to one for the second. */
         data[pos & ~1] = (data[pos & ~1] & ~(uint64_t(1) << bit)) |
                          uint64_t(nGeneration & 1) << bit;
         data[pos | 1] = (data[pos | 1] & ~(uint64_t(1) << bit)) |
                         uint64_t(nGeneration >> 1) << bit;
     }
 }
 
 void CRollingBloomFilter::insert(const uint256 &hash) {
     std::vector<uint8_t> vData(hash.begin(), hash.end());
     insert(vData);
 }
 
 bool CRollingBloomFilter::contains(const std::vector<uint8_t> &vKey) const {
     for (int n = 0; n < nHashFuncs; n++) {
         uint32_t h = RollingBloomHash(n, nTweak, vKey);
         int bit = h & 0x3F;
         uint32_t pos = FastMod(h, data.size());
         /* If the relevant bit is not set in either data[pos & ~1] or data[pos |
          * 1], the filter does not contain vKey */
         if (!(((data[pos & ~1] | data[pos | 1]) >> bit) & 1)) {
             return false;
         }
     }
     return true;
 }
 
 bool CRollingBloomFilter::contains(const uint256 &hash) const {
     std::vector<uint8_t> vData(hash.begin(), hash.end());
     return contains(vData);
 }
 
 void CRollingBloomFilter::reset() {
     nTweak = GetRand(std::numeric_limits<unsigned int>::max());
     nEntriesThisGeneration = 0;
     nGeneration = 1;
     std::fill(data.begin(), data.end(), 0);
 }
diff --git a/src/bloom.h b/src/bloom.h
index 42024288a..f25fe08fe 100644
--- a/src/bloom.h
+++ b/src/bloom.h
@@ -1,154 +1,151 @@
 // Copyright (c) 2012-2016 The Bitcoin Core developers
 // Distributed under the MIT software license, see the accompanying
 // file COPYING or http://www.opensource.org/licenses/mit-license.php.
 
 #ifndef BITCOIN_BLOOM_H
 #define BITCOIN_BLOOM_H
 
 #include <serialize.h>
 
 #include <cstdint>
 #include <vector>
 
 class COutPoint;
 class CTransaction;
 class uint256;
 
 //! 20,000 items with fp rate < 0.1% or 10,000 items and <0.0001%
 static const uint32_t MAX_BLOOM_FILTER_SIZE = 36000; // bytes
 static const uint32_t MAX_HASH_FUNCS = 50;
 
 /**
  * First two bits of nFlags control how much IsRelevantAndUpdate actually
  * updates. The remaining bits are reserved.
  */
 enum bloomflags {
     BLOOM_UPDATE_NONE = 0,
     BLOOM_UPDATE_ALL = 1,
     // Only adds outpoints to the filter if the output is a
     // pay-to-pubkey/pay-to-multisig script
     BLOOM_UPDATE_P2PUBKEY_ONLY = 2,
     BLOOM_UPDATE_MASK = 3,
 };
 
 /**
  * BloomFilter is a probabilistic filter which SPV clients provide so that we
  * can filter the transactions we send them.
  *
  * This allows for significantly more efficient transaction and block downloads.
  *
  * Because bloom filters are probabilistic, a SPV node can increase the
  * false-positive rate, making us send it transactions which aren't actually
  * its, allowing clients to trade more bandwidth for more privacy by obfuscating
  * which keys are controlled by them.
  */
 class CBloomFilter {
 private:
     std::vector<uint8_t> vData;
     bool isFull;
     bool isEmpty;
     uint32_t nHashFuncs;
     uint32_t nTweak;
     uint8_t nFlags;
 
     uint32_t Hash(uint32_t nHashNum,
                   const std::vector<uint8_t> &vDataToHash) const;
 
 public:
     /**
      * Creates a new bloom filter which will provide the given fp rate when
      * filled with the given number of elements. Note that if the given
      * parameters will result in a filter outside the bounds of the protocol
      * limits, the filter created will be as close to the given parameters as
      * possible within the protocol limits. This will apply if nFPRate is very
      * low or nElements is unreasonably high. nTweak is a constant which is
      * added to the seed value passed to the hash function. It should generally
      * always be a random value (and is largely only exposed for unit testing)
      * nFlags should be one of the BLOOM_UPDATE_* enums (not _MASK)
      */
     CBloomFilter(const uint32_t nElements, const double nFPRate,
                  const uint32_t nTweak, uint8_t nFlagsIn);
     CBloomFilter()
         : isFull(true), isEmpty(false), nHashFuncs(0), nTweak(0), nFlags(0) {}
 
     ADD_SERIALIZE_METHODS;
 
     template <typename Stream, typename Operation>
     inline void SerializationOp(Stream &s, Operation ser_action) {
         READWRITE(vData);
         READWRITE(nHashFuncs);
         READWRITE(nTweak);
         READWRITE(nFlags);
     }
 
     void insert(const std::vector<uint8_t> &vKey);
     void insert(const COutPoint &outpoint);
     void insert(const uint256 &hash);
 
     bool contains(const std::vector<uint8_t> &vKey) const;
     bool contains(const COutPoint &outpoint) const;
     bool contains(const uint256 &hash) const;
 
-    void clear();
-    void reset(const uint32_t nNewTweak);
-
     //! True if the size is <= MAX_BLOOM_FILTER_SIZE and the number of hash
     //! functions is <= MAX_HASH_FUNCS (catch a filter which was just
     //! deserialized which was too big)
     bool IsWithinSizeConstraints() const;
 
     //! Scans output scripts for matches and adds those outpoints to the filter
     //! for spend detection. Returns true if any output matched, or the txid
     //! matches.
     bool MatchAndInsertOutputs(const CTransaction &tx);
 
     //! Scan inputs to see if the spent outpoints are a match, or the input
     //! scripts contain matching elements.
     bool MatchInputs(const CTransaction &tx);
 
     //! Check if the transaction is relevant for any reason.
     //! Also adds any outputs which match the filter to the filter (to match
     //! their spending txes)
     bool IsRelevantAndUpdate(const CTransaction &tx) {
         return MatchAndInsertOutputs(tx) || MatchInputs(tx);
     }
 
     //! Checks for empty and full filters to avoid wasting cpu
     void UpdateEmptyFull();
 };
 
 /**
  * RollingBloomFilter is a probabilistic "keep track of most recently inserted"
  * set. Construct it with the number of items to keep track of, and a
  * false-positive rate. Unlike CBloomFilter, by default nTweak is set to a
  * cryptographically secure random value for you. Similarly rather than clear()
  * the method reset() is provided, which also changes nTweak to decrease the
  * impact of false-positives.
  *
  * contains(item) will always return true if item was one of the last N to 1.5*N
  * insert()'ed ... but may also return true for items that were not inserted.
  *
  * It needs around 1.8 bytes per element per factor 0.1 of false positive rate.
  * (More accurately: 3/(log(256)*log(2)) * log(1/fpRate) * nElements bytes)
  */
 class CRollingBloomFilter {
 public:
     CRollingBloomFilter(const uint32_t nElements, const double nFPRate);
 
     void insert(const std::vector<uint8_t> &vKey);
     void insert(const uint256 &hash);
     bool contains(const std::vector<uint8_t> &vKey) const;
     bool contains(const uint256 &hash) const;
 
     void reset();
 
 private:
     int nEntriesPerGeneration;
     int nEntriesThisGeneration;
     int nGeneration;
     std::vector<uint64_t> data;
     uint32_t nTweak;
     int nHashFuncs;
 };
 
 #endif // BITCOIN_BLOOM_H
diff --git a/src/test/bloom_tests.cpp b/src/test/bloom_tests.cpp
index ec48f2235..524cc9b68 100644
--- a/src/test/bloom_tests.cpp
+++ b/src/test/bloom_tests.cpp
@@ -1,1172 +1,1171 @@
 // Copyright (c) 2012-2019 The Bitcoin Core developers
 // Distributed under the MIT software license, see the accompanying
 // file COPYING or http://www.opensource.org/licenses/mit-license.php.
 
 #include <bloom.h>
 
 #include <clientversion.h>
 #include <consensus/merkle.h>
 #include <key.h>
 #include <key_io.h>
 #include <merkleblock.h>
 #include <primitives/block.h>
 #include <random.h>
 #include <serialize.h>
 #include <streams.h>
 #include <uint256.h>
 #include <util/strencodings.h>
 #include <util/system.h>
 
 #include <test/util/setup_common.h>
 
 #include <boost/test/unit_test.hpp>
 
 #include <algorithm>
 #include <vector>
 
 BOOST_FIXTURE_TEST_SUITE(bloom_tests, BasicTestingSetup)
 
 BOOST_AUTO_TEST_CASE(bloom_create_insert_serialize) {
     CBloomFilter filter(3, 0.01, 0, BLOOM_UPDATE_ALL);
 
+    BOOST_CHECK_MESSAGE(
+        !filter.contains(ParseHex("99108ad8ed9bb6274d3980bab5a85c048f0950c8")),
+        "Bloom filter should be empty!");
     filter.insert(ParseHex("99108ad8ed9bb6274d3980bab5a85c048f0950c8"));
     BOOST_CHECK_MESSAGE(
         filter.contains(ParseHex("99108ad8ed9bb6274d3980bab5a85c048f0950c8")),
         "Bloom filter doesn't contain just-inserted object!");
     // One bit different in first byte
     BOOST_CHECK_MESSAGE(
         !filter.contains(ParseHex("19108ad8ed9bb6274d3980bab5a85c048f0950c8")),
         "Bloom filter contains something it shouldn't!");
 
     filter.insert(ParseHex("b5a2c786d9ef4658287ced5914b37a1b4aa32eee"));
     BOOST_CHECK_MESSAGE(
         filter.contains(ParseHex("b5a2c786d9ef4658287ced5914b37a1b4aa32eee")),
         "Bloom filter doesn't contain just-inserted object (2)!");
 
     filter.insert(ParseHex("b9300670b4c5366e95b2699e8b18bc75e5f729c5"));
     BOOST_CHECK_MESSAGE(
         filter.contains(ParseHex("b9300670b4c5366e95b2699e8b18bc75e5f729c5")),
         "Bloom filter doesn't contain just-inserted object (3)!");
 
     CDataStream stream(SER_NETWORK, PROTOCOL_VERSION);
     stream << filter;
 
     std::vector<uint8_t> vch = ParseHex("03614e9b050000000000000001");
     std::vector<char> expected(vch.size());
 
     for (size_t i = 0; i < vch.size(); i++) {
         expected[i] = (char)vch[i];
     }
 
     BOOST_CHECK_EQUAL_COLLECTIONS(stream.begin(), stream.end(),
                                   expected.begin(), expected.end());
 
     BOOST_CHECK_MESSAGE(
         filter.contains(ParseHex("99108ad8ed9bb6274d3980bab5a85c048f0950c8")),
         "Bloom filter doesn't contain just-inserted object!");
-    filter.clear();
-    BOOST_CHECK_MESSAGE(
-        !filter.contains(ParseHex("99108ad8ed9bb6274d3980bab5a85c048f0950c8")),
-        "Bloom filter should be empty!");
 }
 
 BOOST_AUTO_TEST_CASE(bloom_create_insert_serialize_with_tweak) {
     // Same test as bloom_create_insert_serialize, but we add a nTweak of 100
     CBloomFilter filter(3, 0.01, 2147483649UL, BLOOM_UPDATE_ALL);
 
     filter.insert(ParseHex("99108ad8ed9bb6274d3980bab5a85c048f0950c8"));
     BOOST_CHECK_MESSAGE(
         filter.contains(ParseHex("99108ad8ed9bb6274d3980bab5a85c048f0950c8")),
         "Bloom filter doesn't contain just-inserted object!");
     // One bit different in first byte
     BOOST_CHECK_MESSAGE(
         !filter.contains(ParseHex("19108ad8ed9bb6274d3980bab5a85c048f0950c8")),
         "Bloom filter contains something it shouldn't!");
 
     filter.insert(ParseHex("b5a2c786d9ef4658287ced5914b37a1b4aa32eee"));
     BOOST_CHECK_MESSAGE(
         filter.contains(ParseHex("b5a2c786d9ef4658287ced5914b37a1b4aa32eee")),
         "Bloom filter doesn't contain just-inserted object (2)!");
 
     filter.insert(ParseHex("b9300670b4c5366e95b2699e8b18bc75e5f729c5"));
     BOOST_CHECK_MESSAGE(
         filter.contains(ParseHex("b9300670b4c5366e95b2699e8b18bc75e5f729c5")),
         "Bloom filter doesn't contain just-inserted object (3)!");
 
     CDataStream stream(SER_NETWORK, PROTOCOL_VERSION);
     stream << filter;
 
     std::vector<uint8_t> vch = ParseHex("03ce4299050000000100008001");
     std::vector<char> expected(vch.size());
 
     for (size_t i = 0; i < vch.size(); i++) {
         expected[i] = (char)vch[i];
     }
 
     BOOST_CHECK_EQUAL_COLLECTIONS(stream.begin(), stream.end(),
                                   expected.begin(), expected.end());
 }
 
 BOOST_AUTO_TEST_CASE(bloom_create_insert_key) {
     std::string strSecret =
         std::string("5Kg1gnAjaLfKiwhhPpGS3QfRg2m6awQvaj98JCZBZQ5SuS2F15C");
     CKey key = DecodeSecret(strSecret);
     CPubKey pubkey = key.GetPubKey();
     std::vector<uint8_t> vchPubKey(pubkey.begin(), pubkey.end());
 
     CBloomFilter filter(2, 0.001, 0, BLOOM_UPDATE_ALL);
     filter.insert(vchPubKey);
     uint160 hash = pubkey.GetID();
     filter.insert(std::vector<uint8_t>(hash.begin(), hash.end()));
 
     CDataStream stream(SER_NETWORK, PROTOCOL_VERSION);
     stream << filter;
 
     std::vector<uint8_t> vch = ParseHex("038fc16b080000000000000001");
     std::vector<char> expected(vch.size());
 
     for (size_t i = 0; i < vch.size(); i++) {
         expected[i] = (char)vch[i];
     }
 
     BOOST_CHECK_EQUAL_COLLECTIONS(stream.begin(), stream.end(),
                                   expected.begin(), expected.end());
 }
 
 BOOST_AUTO_TEST_CASE(bloom_match) {
     // Random real transaction
     // (b4749f017444b051c44dfd2720e88f314ff94f3dd6d56d40ef65854fcd7fff6b)
     CDataStream stream(
         ParseHex("01000000010b26e9b7735eb6aabdf358bab62f9816a21ba9ebdb719d5299e"
                  "88607d722c190000000008b4830450220070aca44506c5cef3a16ed519d7c"
                  "3c39f8aab192c4e1c90d065f37b8a4af6141022100a8e160b856c2d43d27d"
                  "8fba71e5aef6405b8643ac4cb7cb3c462aced7f14711a0141046d11fee51b"
                  "0e60666d5049a9101a72741df480b96ee26488a4d3466b95c9a40ac5eeef8"
                  "7e10a5cd336c19a84565f80fa6c547957b7700ff4dfbdefe76036c339ffff"
                  "ffff021bff3d11000000001976a91404943fdd508053c75000106d3bc6e27"
                  "54dbcff1988ac2f15de00000000001976a914a266436d2965547608b9e15d"
                  "9032a7b9d64fa43188ac00000000"),
         SER_DISK, CLIENT_VERSION);
     CTransaction tx(deserialize, stream);
 
     // and one which spends it
     // (e2769b09e784f32f62ef849763d4f45b98e07ba658647343b915ff832b110436)
     uint8_t ch[] = {
         0x01, 0x00, 0x00, 0x00, 0x01, 0x6b, 0xff, 0x7f, 0xcd, 0x4f, 0x85, 0x65,
         0xef, 0x40, 0x6d, 0xd5, 0xd6, 0x3d, 0x4f, 0xf9, 0x4f, 0x31, 0x8f, 0xe8,
         0x20, 0x27, 0xfd, 0x4d, 0xc4, 0x51, 0xb0, 0x44, 0x74, 0x01, 0x9f, 0x74,
         0xb4, 0x00, 0x00, 0x00, 0x00, 0x8c, 0x49, 0x30, 0x46, 0x02, 0x21, 0x00,
         0xda, 0x0d, 0xc6, 0xae, 0xce, 0xfe, 0x1e, 0x06, 0xef, 0xdf, 0x05, 0x77,
         0x37, 0x57, 0xde, 0xb1, 0x68, 0x82, 0x09, 0x30, 0xe3, 0xb0, 0xd0, 0x3f,
         0x46, 0xf5, 0xfc, 0xf1, 0x50, 0xbf, 0x99, 0x0c, 0x02, 0x21, 0x00, 0xd2,
         0x5b, 0x5c, 0x87, 0x04, 0x00, 0x76, 0xe4, 0xf2, 0x53, 0xf8, 0x26, 0x2e,
         0x76, 0x3e, 0x2d, 0xd5, 0x1e, 0x7f, 0xf0, 0xbe, 0x15, 0x77, 0x27, 0xc4,
         0xbc, 0x42, 0x80, 0x7f, 0x17, 0xbd, 0x39, 0x01, 0x41, 0x04, 0xe6, 0xc2,
         0x6e, 0xf6, 0x7d, 0xc6, 0x10, 0xd2, 0xcd, 0x19, 0x24, 0x84, 0x78, 0x9a,
         0x6c, 0xf9, 0xae, 0xa9, 0x93, 0x0b, 0x94, 0x4b, 0x7e, 0x2d, 0xb5, 0x34,
         0x2b, 0x9d, 0x9e, 0x5b, 0x9f, 0xf7, 0x9a, 0xff, 0x9a, 0x2e, 0xe1, 0x97,
         0x8d, 0xd7, 0xfd, 0x01, 0xdf, 0xc5, 0x22, 0xee, 0x02, 0x28, 0x3d, 0x3b,
         0x06, 0xa9, 0xd0, 0x3a, 0xcf, 0x80, 0x96, 0x96, 0x8d, 0x7d, 0xbb, 0x0f,
         0x91, 0x78, 0xff, 0xff, 0xff, 0xff, 0x02, 0x8b, 0xa7, 0x94, 0x0e, 0x00,
         0x00, 0x00, 0x00, 0x19, 0x76, 0xa9, 0x14, 0xba, 0xde, 0xec, 0xfd, 0xef,
         0x05, 0x07, 0x24, 0x7f, 0xc8, 0xf7, 0x42, 0x41, 0xd7, 0x3b, 0xc0, 0x39,
         0x97, 0x2d, 0x7b, 0x88, 0xac, 0x40, 0x94, 0xa8, 0x02, 0x00, 0x00, 0x00,
         0x00, 0x19, 0x76, 0xa9, 0x14, 0xc1, 0x09, 0x32, 0x48, 0x3f, 0xec, 0x93,
         0xed, 0x51, 0xf5, 0xfe, 0x95, 0xe7, 0x25, 0x59, 0xf2, 0xcc, 0x70, 0x43,
         0xf9, 0x88, 0xac, 0x00, 0x00, 0x00, 0x00, 0x00};
     std::vector<uint8_t> vch(ch, ch + sizeof(ch) - 1);
     CDataStream spendStream(vch, SER_DISK, CLIENT_VERSION);
     CTransaction spendingTx(deserialize, spendStream);
 
     CBloomFilter filter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     filter.insert(uint256S(
         "0xb4749f017444b051c44dfd2720e88f314ff94f3dd6d56d40ef65854fcd7fff6b"));
     BOOST_CHECK_MESSAGE(filter.IsRelevantAndUpdate(tx),
                         "Simple Bloom filter didn't match tx hash");
 
     filter = CBloomFilter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     // byte-reversed tx hash
     filter.insert(ParseHex(
         "6bff7fcd4f8565ef406dd5d63d4ff94f318fe82027fd4dc451b04474019f74b4"));
     BOOST_CHECK_MESSAGE(
         filter.IsRelevantAndUpdate(tx),
         "Simple Bloom filter didn't match manually serialized tx hash");
 
     filter = CBloomFilter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     filter.insert(ParseHex("30450220070aca44506c5cef3a16ed519d7c3c39f8aab192c4e"
                            "1c90d065f37b8a4af6141022100a8e160b856c2d43d27d8fba7"
                            "1e5aef6405b8643ac4cb7cb3c462aced7f14711a01"));
     BOOST_CHECK_MESSAGE(filter.IsRelevantAndUpdate(tx),
                         "Simple Bloom filter didn't match input signature");
 
     filter = CBloomFilter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     filter.insert(ParseHex("046d11fee51b0e60666d5049a9101a72741df480b96ee26488a"
                            "4d3466b95c9a40ac5eeef87e10a5cd336c19a84565f80fa6c54"
                            "7957b7700ff4dfbdefe76036c339"));
     BOOST_CHECK_MESSAGE(filter.IsRelevantAndUpdate(tx),
                         "Simple Bloom filter didn't match input pub key");
 
     filter = CBloomFilter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     filter.insert(ParseHex("04943fdd508053c75000106d3bc6e2754dbcff19"));
     BOOST_CHECK_MESSAGE(filter.IsRelevantAndUpdate(tx),
                         "Simple Bloom filter didn't match output address");
     BOOST_CHECK_MESSAGE(filter.IsRelevantAndUpdate(spendingTx),
                         "Simple Bloom filter didn't add output");
 
     filter = CBloomFilter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     filter.insert(ParseHex("04943fdd508053c75000106d3bc6e2754dbcff19"));
     BOOST_CHECK_MESSAGE(filter.MatchAndInsertOutputs(tx),
                         "Simple Bloom filter didn't match output address");
     BOOST_CHECK_MESSAGE(!filter.MatchAndInsertOutputs(spendingTx),
                         "Simple Bloom filter matched unrelated output");
     BOOST_CHECK_MESSAGE(filter.MatchInputs(spendingTx),
                         "Simple Bloom filter didn't add output");
 
     filter = CBloomFilter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     filter.insert(ParseHex("a266436d2965547608b9e15d9032a7b9d64fa431"));
     BOOST_CHECK_MESSAGE(filter.IsRelevantAndUpdate(tx),
                         "Simple Bloom filter didn't match output address");
 
     const TxId txid(uint256S(
         "0x90c122d70786e899529d71dbeba91ba216982fb6ba58f3bdaab65e73b7e9260b"));
 
     filter = CBloomFilter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     filter.insert(COutPoint(txid, 0));
     BOOST_CHECK_MESSAGE(filter.IsRelevantAndUpdate(tx),
                         "Simple Bloom filter didn't match COutPoint");
 
     filter = CBloomFilter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     COutPoint prevOutPoint(txid, 0);
     {
         std::vector<uint8_t> data(32 + sizeof(uint32_t));
         memcpy(data.data(), prevOutPoint.GetTxId().begin(), 32);
         uint32_t n = prevOutPoint.GetN();
         memcpy(data.data() + 32, &n, sizeof(uint32_t));
         filter.insert(data);
     }
     BOOST_CHECK_MESSAGE(
         filter.IsRelevantAndUpdate(tx),
         "Simple Bloom filter didn't match manually serialized COutPoint");
 
     filter = CBloomFilter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     filter.insert(uint256S(
         "00000009e784f32f62ef849763d4f45b98e07ba658647343b915ff832b110436"));
     BOOST_CHECK_MESSAGE(!filter.IsRelevantAndUpdate(tx),
                         "Simple Bloom filter matched random tx hash");
 
     filter = CBloomFilter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     filter.insert(ParseHex("0000006d2965547608b9e15d9032a7b9d64fa431"));
     BOOST_CHECK_MESSAGE(!filter.IsRelevantAndUpdate(tx),
                         "Simple Bloom filter matched random address");
 
     filter = CBloomFilter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     filter.insert(COutPoint(txid, 1));
     BOOST_CHECK_MESSAGE(!filter.IsRelevantAndUpdate(tx),
                         "Simple Bloom filter matched COutPoint for an output "
                         "we didn't care about");
 
     const TxId lowtxid(uint256S(
         "0x000000d70786e899529d71dbeba91ba216982fb6ba58f3bdaab65e73b7e9260b"));
 
     filter = CBloomFilter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     filter.insert(COutPoint(lowtxid, 0));
     BOOST_CHECK_MESSAGE(!filter.IsRelevantAndUpdate(tx),
                         "Simple Bloom filter matched COutPoint for an output "
                         "we didn't care about");
 }
 
 BOOST_AUTO_TEST_CASE(merkle_block_1) {
     CBlock block = getBlock13b8a();
     CBloomFilter filter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     // Match the last transaction
     filter.insert(uint256S(
         "0x74d681e0e03bafa802c8aa084379aa98d9fcd632ddc2ed9782b586ec87451f20"));
 
     CMerkleBlock merkleBlock(block, filter);
     BOOST_CHECK_EQUAL(merkleBlock.header.GetHash().GetHex(),
                       block.GetHash().GetHex());
 
     BOOST_CHECK_EQUAL(merkleBlock.vMatchedTxn.size(), 1U);
     std::pair<size_t, uint256> pair = merkleBlock.vMatchedTxn[0];
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].second ==
                 uint256S("0x74d681e0e03bafa802c8aa084379aa98d9fcd632ddc2ed9782b"
                          "586ec87451f20"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].first == 8);
 
     std::vector<uint256> vMatched;
     std::vector<size_t> vIndex;
     BOOST_CHECK(merkleBlock.txn.ExtractMatches(vMatched, vIndex) ==
                 block.hashMerkleRoot);
     BOOST_CHECK(vMatched.size() == merkleBlock.vMatchedTxn.size());
     for (size_t i = 0; i < vMatched.size(); i++) {
         BOOST_CHECK(vMatched[i] == merkleBlock.vMatchedTxn[i].second);
     }
 
     // Also match the 8th transaction
     filter.insert(uint256S(
         "0xdd1fd2a6fc16404faf339881a90adbde7f4f728691ac62e8f168809cdfae1053"));
     merkleBlock = CMerkleBlock(block, filter);
     BOOST_CHECK(merkleBlock.header.GetHash() == block.GetHash());
 
     BOOST_CHECK(merkleBlock.vMatchedTxn.size() == 2);
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[1] == pair);
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].second ==
                 uint256S("0xdd1fd2a6fc16404faf339881a90adbde7f4f728691ac62e8f16"
                          "8809cdfae1053"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].first == 7);
 
     BOOST_CHECK(merkleBlock.txn.ExtractMatches(vMatched, vIndex) ==
                 block.hashMerkleRoot);
     BOOST_CHECK(vMatched.size() == merkleBlock.vMatchedTxn.size());
     for (size_t i = 0; i < vMatched.size(); i++) {
         BOOST_CHECK(vMatched[i] == merkleBlock.vMatchedTxn[i].second);
     }
 }
 
 BOOST_AUTO_TEST_CASE(merkle_block_2) {
     // Random real block
     // (000000005a4ded781e667e06ceefafb71410b511fe0d5adc3e5a27ecbec34ae6)
     // With 4 txes
     CBlock block;
     CDataStream stream(
         ParseHex(
             "0100000075616236cc2126035fadb38deb65b9102cc2c41c09cdf29fc051906800"
             "000000fe7d5e12ef0ff901f6050211249919b1c0653771832b3a80c66cea42847f"
             "0ae1d4d26e49ffff001d00f0a44104010000000100000000000000000000000000"
             "00000000000000000000000000000000000000ffffffff0804ffff001d029105ff"
             "ffffff0100f2052a010000004341046d8709a041d34357697dfcb30a9d05900a62"
             "94078012bf3bb09c6f9b525f1d16d5503d7905db1ada9501446ea00728668fc571"
             "9aa80be2fdfc8a858a4dbdd4fbac00000000010000000255605dc6f5c3dc148b6d"
             "a58442b0b2cd422be385eab2ebea4119ee9c268d28350000000049483045022100"
             "aa46504baa86df8a33b1192b1b9367b4d729dc41e389f2c04f3e5c7f0559aae702"
             "205e82253a54bf5c4f65b7428551554b2045167d6d206dfe6a2e198127d3f7df15"
             "01ffffffff55605dc6f5c3dc148b6da58442b0b2cd422be385eab2ebea4119ee9c"
             "268d2835010000004847304402202329484c35fa9d6bb32a55a70c0982f606ce0e"
             "3634b69006138683bcd12cbb6602200c28feb1e2555c3210f1dddb299738b4ff8b"
             "be9667b68cb8764b5ac17b7adf0001ffffffff0200e1f505000000004341046a07"
             "65b5865641ce08dd39690aade26dfbf5511430ca428a3089261361cef170e3929a"
             "68aee3d8d4848b0c5111b0a37b82b86ad559fd2a745b44d8e8d9dfdc0cac00180d"
             "8f000000004341044a656f065871a353f216ca26cef8dde2f03e8c16202d2e8ad7"
             "69f02032cb86a5eb5e56842e92e19141d60a01928f8dd2c875a390f67c1f6c94cf"
             "c617c0ea45afac0000000001000000025f9a06d3acdceb56be1bfeaa3e8a25e62d"
             "182fa24fefe899d1c17f1dad4c2028000000004847304402205d6058484157235b"
             "06028c30736c15613a28bdb768ee628094ca8b0030d4d6eb0220328789c9a2ec27"
             "ddaec0ad5ef58efded42e6ea17c2e1ce838f3d6913f5e95db601ffffffff5f9a06"
             "d3acdceb56be1bfeaa3e8a25e62d182fa24fefe899d1c17f1dad4c202801000000"
             "4a493046022100c45af050d3cea806cedd0ab22520c53ebe63b987b8954146cdca"
             "42487b84bdd6022100b9b027716a6b59e640da50a864d6dd8a0ef24c76ce62391f"
             "a3eabaf4d2886d2d01ffffffff0200e1f505000000004341046a0765b5865641ce"
             "08dd39690aade26dfbf5511430ca428a3089261361cef170e3929a68aee3d8d484"
             "8b0c5111b0a37b82b86ad559fd2a745b44d8e8d9dfdc0cac00180d8f0000000043"
             "41046a0765b5865641ce08dd39690aade26dfbf5511430ca428a3089261361cef1"
             "70e3929a68aee3d8d4848b0c5111b0a37b82b86ad559fd2a745b44d8e8d9dfdc0c"
             "ac000000000100000002e2274e5fea1bf29d963914bd301aa63b64daaf8a3e88f1"
             "19b5046ca5738a0f6b0000000048473044022016e7a727a061ea2254a6c358376a"
             "aa617ac537eb836c77d646ebda4c748aac8b0220192ce28bf9f2c06a6467e6531e"
             "27648d2b3e2e2bae85159c9242939840295ba501ffffffffe2274e5fea1bf29d96"
             "3914bd301aa63b64daaf8a3e88f119b5046ca5738a0f6b010000004a4930460221"
             "00b7a1a755588d4190118936e15cd217d133b0e4a53c3c15924010d5648d8925c9"
             "022100aaef031874db2114f2d869ac2de4ae53908fbfea5b2b1862e181626bb900"
             "5c9f01ffffffff0200e1f505000000004341044a656f065871a353f216ca26cef8"
             "dde2f03e8c16202d2e8ad769f02032cb86a5eb5e56842e92e19141d60a01928f8d"
             "d2c875a390f67c1f6c94cfc617c0ea45afac00180d8f000000004341046a0765b5"
             "865641ce08dd39690aade26dfbf5511430ca428a3089261361cef170e3929a68ae"
             "e3d8d4848b0c5111b0a37b82b86ad559fd2a745b44d8e8d9dfdc0cac00000000"),
         SER_NETWORK, PROTOCOL_VERSION);
     stream >> block;
 
     CBloomFilter filter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     // Match the first transaction
     filter.insert(uint256S(
         "0xe980fe9f792d014e73b95203dc1335c5f9ce19ac537a419e6df5b47aecb93b70"));
 
     CMerkleBlock merkleBlock(block, filter);
     BOOST_CHECK(merkleBlock.header.GetHash() == block.GetHash());
 
     BOOST_CHECK(merkleBlock.vMatchedTxn.size() == 1);
     std::pair<size_t, uint256> pair = merkleBlock.vMatchedTxn[0];
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].second ==
                 uint256S("0xe980fe9f792d014e73b95203dc1335c5f9ce19ac537a419e6df"
                          "5b47aecb93b70"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].first == 0);
 
     std::vector<uint256> vMatched;
     std::vector<size_t> vIndex;
     BOOST_CHECK(merkleBlock.txn.ExtractMatches(vMatched, vIndex) ==
                 block.hashMerkleRoot);
     BOOST_CHECK(vMatched.size() == merkleBlock.vMatchedTxn.size());
     for (size_t i = 0; i < vMatched.size(); i++) {
         BOOST_CHECK(vMatched[i] == merkleBlock.vMatchedTxn[i].second);
     }
 
     // Match an output from the second transaction (the pubkey for address
     // 1DZTzaBHUDM7T3QvUKBz4qXMRpkg8jsfB5)
     // This should match the third transaction because it spends the output
     // matched
     // It also matches the fourth transaction, which spends to the pubkey again
     filter.insert(ParseHex("044a656f065871a353f216ca26cef8dde2f03e8c16202d2e8ad"
                            "769f02032cb86a5eb5e56842e92e19141d60a01928f8dd2c875"
                            "a390f67c1f6c94cfc617c0ea45af"));
 
     merkleBlock = CMerkleBlock(block, filter);
     BOOST_CHECK(merkleBlock.header.GetHash() == block.GetHash());
 
     BOOST_CHECK(merkleBlock.vMatchedTxn.size() == 4);
 
     BOOST_CHECK(pair == merkleBlock.vMatchedTxn[0]);
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[1].second ==
                 uint256S("0x28204cad1d7fc1d199e8ef4fa22f182de6258a3eaafe1bbe56e"
                          "bdcacd3069a5f"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[1].first == 1);
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[2].second ==
                 uint256S("0x6b0f8a73a56c04b519f1883e8aafda643ba61a30bd1439969df"
                          "21bea5f4e27e2"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[2].first == 2);
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[3].second ==
                 uint256S("0x3c1d7e82342158e4109df2e0b6348b6e84e403d8b4046d70076"
                          "63ace63cddb23"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[3].first == 3);
 
     BOOST_CHECK(merkleBlock.txn.ExtractMatches(vMatched, vIndex) ==
                 block.hashMerkleRoot);
     BOOST_CHECK(vMatched.size() == merkleBlock.vMatchedTxn.size());
     for (size_t i = 0; i < vMatched.size(); i++) {
         BOOST_CHECK(vMatched[i] == merkleBlock.vMatchedTxn[i].second);
     }
 }
 
 BOOST_AUTO_TEST_CASE(merkle_block_2_reversed) {
     // Like merkle_block_2 except this block gets its transactions reversed in
     // order to check non-topological processing.
     // Random real block
     // (000000005a4ded781e667e06ceefafb71410b511fe0d5adc3e5a27ecbec34ae6)
     // With 4 txes
     CBlock block;
     CDataStream stream(
         ParseHex(
             "0100000075616236cc2126035fadb38deb65b9102cc2c41c09cdf29fc051906800"
             "000000fe7d5e12ef0ff901f6050211249919b1c0653771832b3a80c66cea42847f"
             "0ae1d4d26e49ffff001d00f0a44104010000000100000000000000000000000000"
             "00000000000000000000000000000000000000ffffffff0804ffff001d029105ff"
             "ffffff0100f2052a010000004341046d8709a041d34357697dfcb30a9d05900a62"
             "94078012bf3bb09c6f9b525f1d16d5503d7905db1ada9501446ea00728668fc571"
             "9aa80be2fdfc8a858a4dbdd4fbac00000000010000000255605dc6f5c3dc148b6d"
             "a58442b0b2cd422be385eab2ebea4119ee9c268d28350000000049483045022100"
             "aa46504baa86df8a33b1192b1b9367b4d729dc41e389f2c04f3e5c7f0559aae702"
             "205e82253a54bf5c4f65b7428551554b2045167d6d206dfe6a2e198127d3f7df15"
             "01ffffffff55605dc6f5c3dc148b6da58442b0b2cd422be385eab2ebea4119ee9c"
             "268d2835010000004847304402202329484c35fa9d6bb32a55a70c0982f606ce0e"
             "3634b69006138683bcd12cbb6602200c28feb1e2555c3210f1dddb299738b4ff8b"
             "be9667b68cb8764b5ac17b7adf0001ffffffff0200e1f505000000004341046a07"
             "65b5865641ce08dd39690aade26dfbf5511430ca428a3089261361cef170e3929a"
             "68aee3d8d4848b0c5111b0a37b82b86ad559fd2a745b44d8e8d9dfdc0cac00180d"
             "8f000000004341044a656f065871a353f216ca26cef8dde2f03e8c16202d2e8ad7"
             "69f02032cb86a5eb5e56842e92e19141d60a01928f8dd2c875a390f67c1f6c94cf"
             "c617c0ea45afac0000000001000000025f9a06d3acdceb56be1bfeaa3e8a25e62d"
             "182fa24fefe899d1c17f1dad4c2028000000004847304402205d6058484157235b"
             "06028c30736c15613a28bdb768ee628094ca8b0030d4d6eb0220328789c9a2ec27"
             "ddaec0ad5ef58efded42e6ea17c2e1ce838f3d6913f5e95db601ffffffff5f9a06"
             "d3acdceb56be1bfeaa3e8a25e62d182fa24fefe899d1c17f1dad4c202801000000"
             "4a493046022100c45af050d3cea806cedd0ab22520c53ebe63b987b8954146cdca"
             "42487b84bdd6022100b9b027716a6b59e640da50a864d6dd8a0ef24c76ce62391f"
             "a3eabaf4d2886d2d01ffffffff0200e1f505000000004341046a0765b5865641ce"
             "08dd39690aade26dfbf5511430ca428a3089261361cef170e3929a68aee3d8d484"
             "8b0c5111b0a37b82b86ad559fd2a745b44d8e8d9dfdc0cac00180d8f0000000043"
             "41046a0765b5865641ce08dd39690aade26dfbf5511430ca428a3089261361cef1"
             "70e3929a68aee3d8d4848b0c5111b0a37b82b86ad559fd2a745b44d8e8d9dfdc0c"
             "ac000000000100000002e2274e5fea1bf29d963914bd301aa63b64daaf8a3e88f1"
             "19b5046ca5738a0f6b0000000048473044022016e7a727a061ea2254a6c358376a"
             "aa617ac537eb836c77d646ebda4c748aac8b0220192ce28bf9f2c06a6467e6531e"
             "27648d2b3e2e2bae85159c9242939840295ba501ffffffffe2274e5fea1bf29d96"
             "3914bd301aa63b64daaf8a3e88f119b5046ca5738a0f6b010000004a4930460221"
             "00b7a1a755588d4190118936e15cd217d133b0e4a53c3c15924010d5648d8925c9"
             "022100aaef031874db2114f2d869ac2de4ae53908fbfea5b2b1862e181626bb900"
             "5c9f01ffffffff0200e1f505000000004341044a656f065871a353f216ca26cef8"
             "dde2f03e8c16202d2e8ad769f02032cb86a5eb5e56842e92e19141d60a01928f8d"
             "d2c875a390f67c1f6c94cfc617c0ea45afac00180d8f000000004341046a0765b5"
             "865641ce08dd39690aade26dfbf5511430ca428a3089261361cef170e3929a68ae"
             "e3d8d4848b0c5111b0a37b82b86ad559fd2a745b44d8e8d9dfdc0cac00000000"),
         SER_NETWORK, PROTOCOL_VERSION);
     stream >> block;
 
     // Reverse the transactions and recalculate merkle root. The remainder of
     // this test is the same as merkle_block_2 above except the transaction
     // indices get reversed too.
     std::reverse(block.vtx.begin(), block.vtx.end());
     block.hashMerkleRoot = BlockMerkleRoot(block);
 
     CBloomFilter filter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     // Match the fourth (was first) transaction
     filter.insert(uint256S(
         "0xe980fe9f792d014e73b95203dc1335c5f9ce19ac537a419e6df5b47aecb93b70"));
 
     CMerkleBlock merkleBlock(block, filter);
     BOOST_CHECK(merkleBlock.header.GetHash() == block.GetHash());
 
     BOOST_CHECK(merkleBlock.vMatchedTxn.size() == 1);
     std::pair<size_t, uint256> pair = merkleBlock.vMatchedTxn[0];
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].second ==
                 uint256S("0xe980fe9f792d014e73b95203dc1335c5f9ce19ac537a419e6df"
                          "5b47aecb93b70"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].first == 3);
 
     std::vector<uint256> vMatched;
     std::vector<size_t> vIndex;
     BOOST_CHECK(merkleBlock.txn.ExtractMatches(vMatched, vIndex) ==
                 block.hashMerkleRoot);
     BOOST_CHECK(vMatched.size() == merkleBlock.vMatchedTxn.size());
     for (size_t i = 0; i < vMatched.size(); i++) {
         BOOST_CHECK(vMatched[i] == merkleBlock.vMatchedTxn[i].second);
     }
 
     // Match an output from the third (was second) transaction (the pubkey for
     // address 1DZTzaBHUDM7T3QvUKBz4qXMRpkg8jsfB5) This should match the second
     // (was third) transaction because it spends the output matched
     // It also matches the first (was fourth) transaction, which spends to the
     // pubkey again
     filter.insert(ParseHex("044a656f065871a353f216ca26cef8dde2f03e8c16202d2e8ad"
                            "769f02032cb86a5eb5e56842e92e19141d60a01928f8dd2c875"
                            "a390f67c1f6c94cfc617c0ea45af"));
 
     merkleBlock = CMerkleBlock(block, filter);
     BOOST_CHECK(merkleBlock.header.GetHash() == block.GetHash());
 
     BOOST_CHECK(merkleBlock.vMatchedTxn.size() == 4);
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].second ==
                 uint256S("0x3c1d7e82342158e4109df2e0b6348b6e84e403d8b4046d70076"
                          "63ace63cddb23"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].first == 0);
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[1].second ==
                 uint256S("0x6b0f8a73a56c04b519f1883e8aafda643ba61a30bd1439969df"
                          "21bea5f4e27e2"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[1].first == 1);
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[2].second ==
                 uint256S("0x28204cad1d7fc1d199e8ef4fa22f182de6258a3eaafe1bbe56e"
                          "bdcacd3069a5f"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[2].first == 2);
 
     BOOST_CHECK(pair == merkleBlock.vMatchedTxn[3]);
 
     BOOST_CHECK(merkleBlock.txn.ExtractMatches(vMatched, vIndex) ==
                 block.hashMerkleRoot);
     BOOST_CHECK(vMatched.size() == merkleBlock.vMatchedTxn.size());
     for (size_t i = 0; i < vMatched.size(); i++) {
         BOOST_CHECK(vMatched[i] == merkleBlock.vMatchedTxn[i].second);
     }
 }
 
 BOOST_AUTO_TEST_CASE(merkle_block_2_with_update_none) {
     // Random real block
     // (000000005a4ded781e667e06ceefafb71410b511fe0d5adc3e5a27ecbec34ae6)
     // With 4 txes
     CBlock block;
     CDataStream stream(
         ParseHex(
             "0100000075616236cc2126035fadb38deb65b9102cc2c41c09cdf29fc051906800"
             "000000fe7d5e12ef0ff901f6050211249919b1c0653771832b3a80c66cea42847f"
             "0ae1d4d26e49ffff001d00f0a44104010000000100000000000000000000000000"
             "00000000000000000000000000000000000000ffffffff0804ffff001d029105ff"
             "ffffff0100f2052a010000004341046d8709a041d34357697dfcb30a9d05900a62"
             "94078012bf3bb09c6f9b525f1d16d5503d7905db1ada9501446ea00728668fc571"
             "9aa80be2fdfc8a858a4dbdd4fbac00000000010000000255605dc6f5c3dc148b6d"
             "a58442b0b2cd422be385eab2ebea4119ee9c268d28350000000049483045022100"
             "aa46504baa86df8a33b1192b1b9367b4d729dc41e389f2c04f3e5c7f0559aae702"
             "205e82253a54bf5c4f65b7428551554b2045167d6d206dfe6a2e198127d3f7df15"
             "01ffffffff55605dc6f5c3dc148b6da58442b0b2cd422be385eab2ebea4119ee9c"
             "268d2835010000004847304402202329484c35fa9d6bb32a55a70c0982f606ce0e"
             "3634b69006138683bcd12cbb6602200c28feb1e2555c3210f1dddb299738b4ff8b"
             "be9667b68cb8764b5ac17b7adf0001ffffffff0200e1f505000000004341046a07"
             "65b5865641ce08dd39690aade26dfbf5511430ca428a3089261361cef170e3929a"
             "68aee3d8d4848b0c5111b0a37b82b86ad559fd2a745b44d8e8d9dfdc0cac00180d"
             "8f000000004341044a656f065871a353f216ca26cef8dde2f03e8c16202d2e8ad7"
             "69f02032cb86a5eb5e56842e92e19141d60a01928f8dd2c875a390f67c1f6c94cf"
             "c617c0ea45afac0000000001000000025f9a06d3acdceb56be1bfeaa3e8a25e62d"
             "182fa24fefe899d1c17f1dad4c2028000000004847304402205d6058484157235b"
             "06028c30736c15613a28bdb768ee628094ca8b0030d4d6eb0220328789c9a2ec27"
             "ddaec0ad5ef58efded42e6ea17c2e1ce838f3d6913f5e95db601ffffffff5f9a06"
             "d3acdceb56be1bfeaa3e8a25e62d182fa24fefe899d1c17f1dad4c202801000000"
             "4a493046022100c45af050d3cea806cedd0ab22520c53ebe63b987b8954146cdca"
             "42487b84bdd6022100b9b027716a6b59e640da50a864d6dd8a0ef24c76ce62391f"
             "a3eabaf4d2886d2d01ffffffff0200e1f505000000004341046a0765b5865641ce"
             "08dd39690aade26dfbf5511430ca428a3089261361cef170e3929a68aee3d8d484"
             "8b0c5111b0a37b82b86ad559fd2a745b44d8e8d9dfdc0cac00180d8f0000000043"
             "41046a0765b5865641ce08dd39690aade26dfbf5511430ca428a3089261361cef1"
             "70e3929a68aee3d8d4848b0c5111b0a37b82b86ad559fd2a745b44d8e8d9dfdc0c"
             "ac000000000100000002e2274e5fea1bf29d963914bd301aa63b64daaf8a3e88f1"
             "19b5046ca5738a0f6b0000000048473044022016e7a727a061ea2254a6c358376a"
             "aa617ac537eb836c77d646ebda4c748aac8b0220192ce28bf9f2c06a6467e6531e"
             "27648d2b3e2e2bae85159c9242939840295ba501ffffffffe2274e5fea1bf29d96"
             "3914bd301aa63b64daaf8a3e88f119b5046ca5738a0f6b010000004a4930460221"
             "00b7a1a755588d4190118936e15cd217d133b0e4a53c3c15924010d5648d8925c9"
             "022100aaef031874db2114f2d869ac2de4ae53908fbfea5b2b1862e181626bb900"
             "5c9f01ffffffff0200e1f505000000004341044a656f065871a353f216ca26cef8"
             "dde2f03e8c16202d2e8ad769f02032cb86a5eb5e56842e92e19141d60a01928f8d"
             "d2c875a390f67c1f6c94cfc617c0ea45afac00180d8f000000004341046a0765b5"
             "865641ce08dd39690aade26dfbf5511430ca428a3089261361cef170e3929a68ae"
             "e3d8d4848b0c5111b0a37b82b86ad559fd2a745b44d8e8d9dfdc0cac00000000"),
         SER_NETWORK, PROTOCOL_VERSION);
     stream >> block;
 
     CBloomFilter filter(10, 0.000001, 0, BLOOM_UPDATE_NONE);
     // Match the first transaction
     filter.insert(uint256S(
         "0xe980fe9f792d014e73b95203dc1335c5f9ce19ac537a419e6df5b47aecb93b70"));
 
     CMerkleBlock merkleBlock(block, filter);
     BOOST_CHECK(merkleBlock.header.GetHash() == block.GetHash());
 
     BOOST_CHECK(merkleBlock.vMatchedTxn.size() == 1);
     std::pair<size_t, uint256> pair = merkleBlock.vMatchedTxn[0];
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].second ==
                 uint256S("0xe980fe9f792d014e73b95203dc1335c5f9ce19ac537a419e6df"
                          "5b47aecb93b70"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].first == 0);
 
     std::vector<uint256> vMatched;
     std::vector<size_t> vIndex;
     BOOST_CHECK(merkleBlock.txn.ExtractMatches(vMatched, vIndex) ==
                 block.hashMerkleRoot);
     BOOST_CHECK(vMatched.size() == merkleBlock.vMatchedTxn.size());
     for (size_t i = 0; i < vMatched.size(); i++) {
         BOOST_CHECK(vMatched[i] == merkleBlock.vMatchedTxn[i].second);
     }
 
     // Match an output from the second transaction (the pubkey for address
     // 1DZTzaBHUDM7T3QvUKBz4qXMRpkg8jsfB5)
     // This should not match the third transaction though it spends the output
     // matched
     // It will match the fourth transaction, which has another pay-to-pubkey
     // output to the same address
     filter.insert(ParseHex("044a656f065871a353f216ca26cef8dde2f03e8c16202d2e8ad"
                            "769f02032cb86a5eb5e56842e92e19141d60a01928f8dd2c875"
                            "a390f67c1f6c94cfc617c0ea45af"));
 
     merkleBlock = CMerkleBlock(block, filter);
     BOOST_CHECK(merkleBlock.header.GetHash() == block.GetHash());
 
     BOOST_CHECK(merkleBlock.vMatchedTxn.size() == 3);
 
     BOOST_CHECK(pair == merkleBlock.vMatchedTxn[0]);
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[1].second ==
                 uint256S("0x28204cad1d7fc1d199e8ef4fa22f182de6258a3eaafe1bbe56e"
                          "bdcacd3069a5f"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[1].first == 1);
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[2].second ==
                 uint256S("0x3c1d7e82342158e4109df2e0b6348b6e84e403d8b4046d70076"
                          "63ace63cddb23"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[2].first == 3);
 
     BOOST_CHECK(merkleBlock.txn.ExtractMatches(vMatched, vIndex) ==
                 block.hashMerkleRoot);
     BOOST_CHECK(vMatched.size() == merkleBlock.vMatchedTxn.size());
     for (size_t i = 0; i < vMatched.size(); i++) {
         BOOST_CHECK(vMatched[i] == merkleBlock.vMatchedTxn[i].second);
     }
 }
 
 BOOST_AUTO_TEST_CASE(merkle_block_3_and_serialize) {
     // Random real block
     // (000000000000dab0130bbcc991d3d7ae6b81aa6f50a798888dfe62337458dc45)
     // With one tx
     CBlock block;
     CDataStream stream(
         ParseHex("0100000079cda856b143d9db2c1caff01d1aecc8630d30625d10e8b4b8b00"
                  "00000000000b50cc069d6a3e33e3ff84a5c41d9d3febe7c770fdcc96b2c3f"
                  "f60abe184f196367291b4d4c86041b8fa45d6301010000000100000000000"
                  "00000000000000000000000000000000000000000000000000000ffffffff"
                  "08044c86041b020a02ffffffff0100f2052a01000000434104ecd3229b057"
                  "1c3be876feaac0442a9f13c5a572742927af1dc623353ecf8c202225f6486"
                  "8137a18cdd85cbbb4c74fbccfd4f49639cf1bdc94a5672bb15ad5d4cac000"
                  "00000"),
         SER_NETWORK, PROTOCOL_VERSION);
     stream >> block;
 
     CBloomFilter filter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     // Match the only transaction
     filter.insert(uint256S(
         "0x63194f18be0af63f2c6bc9dc0f777cbefed3d9415c4af83f3ee3a3d669c00cb5"));
 
     CMerkleBlock merkleBlock(block, filter);
     BOOST_CHECK(merkleBlock.header.GetHash() == block.GetHash());
 
     BOOST_CHECK(merkleBlock.vMatchedTxn.size() == 1);
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].second ==
                 uint256S("0x63194f18be0af63f2c6bc9dc0f777cbefed3d9415c4af83f3ee"
                          "3a3d669c00cb5"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].first == 0);
 
     std::vector<uint256> vMatched;
     std::vector<size_t> vIndex;
     BOOST_CHECK(merkleBlock.txn.ExtractMatches(vMatched, vIndex) ==
                 block.hashMerkleRoot);
     BOOST_CHECK(vMatched.size() == merkleBlock.vMatchedTxn.size());
     for (size_t i = 0; i < vMatched.size(); i++) {
         BOOST_CHECK(vMatched[i] == merkleBlock.vMatchedTxn[i].second);
     }
 
     CDataStream merkleStream(SER_NETWORK, PROTOCOL_VERSION);
     merkleStream << merkleBlock;
 
     std::vector<uint8_t> vch =
         ParseHex("0100000079cda856b143d9db2c1caff01d1aecc8630d30625d10e8b4b8b00"
                  "00000000000b50cc069d6a3e33e3ff84a5c41d9d3febe7c770fdcc96b2c3f"
                  "f60abe184f196367291b4d4c86041b8fa45d630100000001b50cc069d6a3e"
                  "33e3ff84a5c41d9d3febe7c770fdcc96b2c3ff60abe184f19630101");
     std::vector<char> expected(vch.size());
 
     for (size_t i = 0; i < vch.size(); i++) {
         expected[i] = (char)vch[i];
     }
 
     BOOST_CHECK_EQUAL_COLLECTIONS(expected.begin(), expected.end(),
                                   merkleStream.begin(), merkleStream.end());
 }
 
 BOOST_AUTO_TEST_CASE(merkle_block_4) {
     // Random real block
     // (000000000000b731f2eef9e8c63173adfb07e41bd53eb0ef0a6b720d6cb6dea4)
     // With 7 txes
     CBlock block;
     CDataStream stream(
         ParseHex(
             "0100000082bb869cf3a793432a66e826e05a6fc37469f8efb7421dc88067010000"
             "0000007f16c5962e8bd963659c793ce370d95f093bc7e367117b3c30c1f8fdd0d9"
             "728776381b4d4c86041b554b852907010000000100000000000000000000000000"
             "00000000000000000000000000000000000000ffffffff07044c86041b0136ffff"
             "ffff0100f2052a01000000434104eaafc2314def4ca98ac970241bcab022b9c1e1"
             "f4ea423a20f134c876f2c01ec0f0dd5b2e86e7168cefe0d81113c3807420ce13ad"
             "1357231a2252247d97a46a91ac000000000100000001bcad20a6a29827d1424f08"
             "989255120bf7f3e9e3cdaaa6bb31b0737fe048724300000000494830450220356e"
             "834b046cadc0f8ebb5a8a017b02de59c86305403dad52cd77b55af062ea1022100"
             "9253cd6c119d4729b77c978e1e2aa19f5ea6e0e52b3f16e32fa608cd5bab753901"
             "ffffffff02008d380c010000001976a9142b4b8072ecbba129b6453c63e129e643"
             "207249ca88ac0065cd1d000000001976a9141b8dd13b994bcfc787b32aeadf58cc"
             "b3615cbd5488ac000000000100000003fdacf9b3eb077412e7a968d2e4f11b9a9d"
             "ee312d666187ed77ee7d26af16cb0b000000008c493046022100ea1608e70911ca"
             "0de5af51ba57ad23b9a51db8d28f82c53563c56a05c20f5a87022100a8bdc8b4a8"
             "acc8634c6b420410150775eb7f2474f5615f7fccd65af30f310fbf01410465fdf4"
             "9e29b06b9a1582287b6279014f834edc317695d125ef623c1cc3aaece245bd69fc"
             "ad7508666e9c74a49dc9056d5fc14338ef38118dc4afae5fe2c585caffffffff30"
             "9e1913634ecb50f3c4f83e96e70b2df071b497b8973a3e75429df397b5af830000"
             "00004948304502202bdb79c596a9ffc24e96f4386199aba386e9bc7b6071516e2b"
             "51dda942b3a1ed022100c53a857e76b724fc14d45311eac5019650d415c3abb542"
             "8f3aae16d8e69bec2301ffffffff2089e33491695080c9edc18a428f7d834db5b6"
             "d372df13ce2b1b0e0cbcb1e6c10000000049483045022100d4ce67c5896ee251c8"
             "10ac1ff9ceccd328b497c8f553ab6e08431e7d40bad6b5022033119c0c2b7d792d"
             "31f1187779c7bd95aefd93d90a715586d73801d9b47471c601ffffffff01007144"
             "60030000001976a914c7b55141d097ea5df7a0ed330cf794376e53ec8d88ac0000"
             "000001000000045bf0e214aa4069a3e792ecee1e1bf0c1d397cde8dd08138f4b72"
             "a00681743447000000008b48304502200c45de8c4f3e2c1821f2fc878cba97b1e6"
             "f8807d94930713aa1c86a67b9bf1e40221008581abfef2e30f957815fc89978423"
             "746b2086375ca8ecf359c85c2a5b7c88ad01410462bb73f76ca0994fcb8b4271e6"
             "fb7561f5c0f9ca0cf6485261c4a0dc894f4ab844c6cdfb97cd0b60ffb5018ffd62"
             "38f4d87270efb1d3ae37079b794a92d7ec95ffffffffd669f7d7958d40fc59d225"
             "3d88e0f248e29b599c80bbcec344a83dda5f9aa72c000000008a47304402207812"
             "4c8beeaa825f9e0b30bff96e564dd859432f2d0cb3b72d3d5d93d38d7e93022069"
             "1d233b6c0f995be5acb03d70a7f7a65b6bc9bdd426260f38a1346669507a360141"
             "0462bb73f76ca0994fcb8b4271e6fb7561f5c0f9ca0cf6485261c4a0dc894f4ab8"
             "44c6cdfb97cd0b60ffb5018ffd6238f4d87270efb1d3ae37079b794a92d7ec95ff"
             "fffffff878af0d93f5229a68166cf051fd372bb7a537232946e0a46f53636b4daf"
             "daa4000000008c493046022100c717d1714551663f69c3c5759bdbb3a0fcd3fab0"
             "23abc0e522fe6440de35d8290221008d9cbe25bffc44af2b18e81c58eb37293fd7"
             "fe1c2e7b46fc37ee8c96c50ab1e201410462bb73f76ca0994fcb8b4271e6fb7561"
             "f5c0f9ca0cf6485261c4a0dc894f4ab844c6cdfb97cd0b60ffb5018ffd6238f4d8"
             "7270efb1d3ae37079b794a92d7ec95ffffffff27f2b668859cd7f2f894aa0fd2d9"
             "e60963bcd07c88973f425f999b8cbfd7a1e2000000008c493046022100e0084714"
             "7cbf517bcc2f502f3ddc6d284358d102ed20d47a8aa788a62f0db780022100d17b"
             "2d6fa84dcaf1c95d88d7e7c30385aecf415588d749afd3ec81f6022cecd7014104"
             "62bb73f76ca0994fcb8b4271e6fb7561f5c0f9ca0cf6485261c4a0dc894f4ab844"
             "c6cdfb97cd0b60ffb5018ffd6238f4d87270efb1d3ae37079b794a92d7ec95ffff"
             "ffff0100c817a8040000001976a914b6efd80d99179f4f4ff6f4dd0a007d018c38"
             "5d2188ac000000000100000001834537b2f1ce8ef9373a258e10545ce5a50b758d"
             "f616cd4356e0032554ebd3c4000000008b483045022100e68f422dd7c34fdce11e"
             "eb4509ddae38201773dd62f284e8aa9d96f85099d0b002202243bd399ff96b649a"
             "0fad05fa759d6a882f0af8c90cf7632c2840c29070aec20141045e58067e815c2f"
             "464c6a2a15f987758374203895710c2d452442e28496ff38ba8f5fd901dc20e29e"
             "88477167fe4fc299bf818fd0d9e1632d467b2a3d9503b1aaffffffff0280d7e636"
             "030000001976a914f34c3e10eb387efe872acb614c89e78bfca7815d88ac404b4c"
             "00000000001976a914a84e272933aaf87e1715d7786c51dfaeb5b65a6f88ac0000"
             "0000010000000143ac81c8e6f6ef307dfe17f3d906d999e23e0189fda838c5510d"
             "850927e03ae7000000008c4930460221009c87c344760a64cb8ae6685a3eec2c1a"
             "c1bed5b88c87de51acd0e124f266c16602210082d07c037359c3a257b5c63ebd90"
             "f5a5edf97b2ac1c434b08ca998839f346dd40141040ba7e521fa7946d12edbb1d1"
             "e95a15c34bd4398195e86433c92b431cd315f455fe30032ede69cad9d1e1ed6c3c"
             "4ec0dbfced53438c625462afb792dcb098544bffffffff0240420f000000000019"
             "76a9144676d1b820d63ec272f1900d59d43bc6463d96f888ac40420f0000000000"
             "1976a914648d04341d00d7968b3405c034adc38d4d8fb9bd88ac00000000010000"
             "000248cc917501ea5c55f4a8d2009c0567c40cfe037c2e71af017d0a452ff705e3"
             "f1000000008b483045022100bf5fdc86dc5f08a5d5c8e43a8c9d5b1ed8c65562e2"
             "80007b52b133021acd9acc02205e325d613e555f772802bf413d36ba807892ed1a"
             "690a77811d3033b3de226e0a01410429fa713b124484cb2bd7b5557b2c0b9df7b2"
             "b1fee61825eadc5ae6c37a9920d38bfccdc7dc3cb0c47d7b173dbc9db8d37db0a3"
             "3ae487982c59c6f8606e9d1791ffffffff41ed70551dd7e841883ab8f0b16bf041"
             "76b7d1480e4f0af9f3d4c3595768d068000000008b4830450221008513ad65187b"
             "903aed1102d1d0c47688127658c51106753fed0151ce9c16b80902201432b9ebcb"
             "87bd04ceb2de66035fbbaf4bf8b00d1cfe41f1a1f7338f9ad79d210141049d4cf8"
             "0125bf50be1709f718c07ad15d0fc612b7da1f5570dddc35f2a352f0f27c978b06"
             "820edca9ef982c35fda2d255afba340068c5035552368bc7200c1488ffffffff01"
             "00093d00000000001976a9148edb68822f1ad580b043c7b3df2e400f8699eb4888"
             "ac00000000"),
         SER_NETWORK, PROTOCOL_VERSION);
     stream >> block;
 
     CBloomFilter filter(10, 0.000001, 0, BLOOM_UPDATE_ALL);
     // Match the last transaction
     filter.insert(uint256S(
         "0x0a2a92f0bda4727d0a13eaddf4dd9ac6b5c61a1429e6b2b818f19b15df0ac154"));
 
     CMerkleBlock merkleBlock(block, filter);
     BOOST_CHECK(merkleBlock.header.GetHash() == block.GetHash());
 
     BOOST_CHECK(merkleBlock.vMatchedTxn.size() == 1);
     std::pair<size_t, uint256> pair = merkleBlock.vMatchedTxn[0];
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].second ==
                 uint256S("0x0a2a92f0bda4727d0a13eaddf4dd9ac6b5c61a1429e6b2b818f"
                          "19b15df0ac154"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].first == 6);
 
     std::vector<uint256> vMatched;
     std::vector<size_t> vIndex;
     BOOST_CHECK(merkleBlock.txn.ExtractMatches(vMatched, vIndex) ==
                 block.hashMerkleRoot);
     BOOST_CHECK(vMatched.size() == merkleBlock.vMatchedTxn.size());
     for (size_t i = 0; i < vMatched.size(); i++) {
         BOOST_CHECK(vMatched[i] == merkleBlock.vMatchedTxn[i].second);
     }
 
     // Also match the 4th transaction
     filter.insert(uint256S(
         "0x02981fa052f0481dbc5868f4fc2166035a10f27a03cfd2de67326471df5bc041"));
     merkleBlock = CMerkleBlock(block, filter);
     BOOST_CHECK(merkleBlock.header.GetHash() == block.GetHash());
 
     BOOST_CHECK(merkleBlock.vMatchedTxn.size() == 2);
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].second ==
                 uint256S("0x02981fa052f0481dbc5868f4fc2166035a10f27a03cfd2de673"
                          "26471df5bc041"));
     BOOST_CHECK(merkleBlock.vMatchedTxn[0].first == 3);
 
     BOOST_CHECK(merkleBlock.vMatchedTxn[1] == pair);
 
     BOOST_CHECK(merkleBlock.txn.ExtractMatches(vMatched, vIndex) ==
                 block.hashMerkleRoot);
     BOOST_CHECK(vMatched.size() == merkleBlock.vMatchedTxn.size());
     for (size_t i = 0; i < vMatched.size(); i++) {
         BOOST_CHECK(vMatched[i] == merkleBlock.vMatchedTxn[i].second);
     }
 }
 
 BOOST_AUTO_TEST_CASE(merkle_block_4_test_p2pubkey_only) {
     // Random real block
     // (000000000000b731f2eef9e8c63173adfb07e41bd53eb0ef0a6b720d6cb6dea4)
     // With 7 txes
     CBlock block;
     CDataStream stream(
         ParseHex(
             "0100000082bb869cf3a793432a66e826e05a6fc37469f8efb7421dc88067010000"
             "0000007f16c5962e8bd963659c793ce370d95f093bc7e367117b3c30c1f8fdd0d9"
             "728776381b4d4c86041b554b852907010000000100000000000000000000000000"
             "00000000000000000000000000000000000000ffffffff07044c86041b0136ffff"
             "ffff0100f2052a01000000434104eaafc2314def4ca98ac970241bcab022b9c1e1"
             "f4ea423a20f134c876f2c01ec0f0dd5b2e86e7168cefe0d81113c3807420ce13ad"
             "1357231a2252247d97a46a91ac000000000100000001bcad20a6a29827d1424f08"
             "989255120bf7f3e9e3cdaaa6bb31b0737fe048724300000000494830450220356e"
             "834b046cadc0f8ebb5a8a017b02de59c86305403dad52cd77b55af062ea1022100"
             "9253cd6c119d4729b77c978e1e2aa19f5ea6e0e52b3f16e32fa608cd5bab753901"
             "ffffffff02008d380c010000001976a9142b4b8072ecbba129b6453c63e129e643"
             "207249ca88ac0065cd1d000000001976a9141b8dd13b994bcfc787b32aeadf58cc"
             "b3615cbd5488ac000000000100000003fdacf9b3eb077412e7a968d2e4f11b9a9d"
             "ee312d666187ed77ee7d26af16cb0b000000008c493046022100ea1608e70911ca"
             "0de5af51ba57ad23b9a51db8d28f82c53563c56a05c20f5a87022100a8bdc8b4a8"
             "acc8634c6b420410150775eb7f2474f5615f7fccd65af30f310fbf01410465fdf4"
             "9e29b06b9a1582287b6279014f834edc317695d125ef623c1cc3aaece245bd69fc"
             "ad7508666e9c74a49dc9056d5fc14338ef38118dc4afae5fe2c585caffffffff30"
             "9e1913634ecb50f3c4f83e96e70b2df071b497b8973a3e75429df397b5af830000"
             "00004948304502202bdb79c596a9ffc24e96f4386199aba386e9bc7b6071516e2b"
             "51dda942b3a1ed022100c53a857e76b724fc14d45311eac5019650d415c3abb542"
             "8f3aae16d8e69bec2301ffffffff2089e33491695080c9edc18a428f7d834db5b6"
             "d372df13ce2b1b0e0cbcb1e6c10000000049483045022100d4ce67c5896ee251c8"
             "10ac1ff9ceccd328b497c8f553ab6e08431e7d40bad6b5022033119c0c2b7d792d"
             "31f1187779c7bd95aefd93d90a715586d73801d9b47471c601ffffffff01007144"
             "60030000001976a914c7b55141d097ea5df7a0ed330cf794376e53ec8d88ac0000"
             "000001000000045bf0e214aa4069a3e792ecee1e1bf0c1d397cde8dd08138f4b72"
             "a00681743447000000008b48304502200c45de8c4f3e2c1821f2fc878cba97b1e6"
             "f8807d94930713aa1c86a67b9bf1e40221008581abfef2e30f957815fc89978423"
             "746b2086375ca8ecf359c85c2a5b7c88ad01410462bb73f76ca0994fcb8b4271e6"
             "fb7561f5c0f9ca0cf6485261c4a0dc894f4ab844c6cdfb97cd0b60ffb5018ffd62"
             "38f4d87270efb1d3ae37079b794a92d7ec95ffffffffd669f7d7958d40fc59d225"
             "3d88e0f248e29b599c80bbcec344a83dda5f9aa72c000000008a47304402207812"
             "4c8beeaa825f9e0b30bff96e564dd859432f2d0cb3b72d3d5d93d38d7e93022069"
             "1d233b6c0f995be5acb03d70a7f7a65b6bc9bdd426260f38a1346669507a360141"
             "0462bb73f76ca0994fcb8b4271e6fb7561f5c0f9ca0cf6485261c4a0dc894f4ab8"
             "44c6cdfb97cd0b60ffb5018ffd6238f4d87270efb1d3ae37079b794a92d7ec95ff"
             "fffffff878af0d93f5229a68166cf051fd372bb7a537232946e0a46f53636b4daf"
             "daa4000000008c493046022100c717d1714551663f69c3c5759bdbb3a0fcd3fab0"
             "23abc0e522fe6440de35d8290221008d9cbe25bffc44af2b18e81c58eb37293fd7"
             "fe1c2e7b46fc37ee8c96c50ab1e201410462bb73f76ca0994fcb8b4271e6fb7561"
             "f5c0f9ca0cf6485261c4a0dc894f4ab844c6cdfb97cd0b60ffb5018ffd6238f4d8"
             "7270efb1d3ae37079b794a92d7ec95ffffffff27f2b668859cd7f2f894aa0fd2d9"
             "e60963bcd07c88973f425f999b8cbfd7a1e2000000008c493046022100e0084714"
             "7cbf517bcc2f502f3ddc6d284358d102ed20d47a8aa788a62f0db780022100d17b"
             "2d6fa84dcaf1c95d88d7e7c30385aecf415588d749afd3ec81f6022cecd7014104"
             "62bb73f76ca0994fcb8b4271e6fb7561f5c0f9ca0cf6485261c4a0dc894f4ab844"
             "c6cdfb97cd0b60ffb5018ffd6238f4d87270efb1d3ae37079b794a92d7ec95ffff"
             "ffff0100c817a8040000001976a914b6efd80d99179f4f4ff6f4dd0a007d018c38"
             "5d2188ac000000000100000001834537b2f1ce8ef9373a258e10545ce5a50b758d"
             "f616cd4356e0032554ebd3c4000000008b483045022100e68f422dd7c34fdce11e"
             "eb4509ddae38201773dd62f284e8aa9d96f85099d0b002202243bd399ff96b649a"
             "0fad05fa759d6a882f0af8c90cf7632c2840c29070aec20141045e58067e815c2f"
             "464c6a2a15f987758374203895710c2d452442e28496ff38ba8f5fd901dc20e29e"
             "88477167fe4fc299bf818fd0d9e1632d467b2a3d9503b1aaffffffff0280d7e636"
             "030000001976a914f34c3e10eb387efe872acb614c89e78bfca7815d88ac404b4c"
             "00000000001976a914a84e272933aaf87e1715d7786c51dfaeb5b65a6f88ac0000"
             "0000010000000143ac81c8e6f6ef307dfe17f3d906d999e23e0189fda838c5510d"
             "850927e03ae7000000008c4930460221009c87c344760a64cb8ae6685a3eec2c1a"
             "c1bed5b88c87de51acd0e124f266c16602210082d07c037359c3a257b5c63ebd90"
             "f5a5edf97b2ac1c434b08ca998839f346dd40141040ba7e521fa7946d12edbb1d1"
             "e95a15c34bd4398195e86433c92b431cd315f455fe30032ede69cad9d1e1ed6c3c"
             "4ec0dbfced53438c625462afb792dcb098544bffffffff0240420f000000000019"
             "76a9144676d1b820d63ec272f1900d59d43bc6463d96f888ac40420f0000000000"
             "1976a914648d04341d00d7968b3405c034adc38d4d8fb9bd88ac00000000010000"
             "000248cc917501ea5c55f4a8d2009c0567c40cfe037c2e71af017d0a452ff705e3"
             "f1000000008b483045022100bf5fdc86dc5f08a5d5c8e43a8c9d5b1ed8c65562e2"
             "80007b52b133021acd9acc02205e325d613e555f772802bf413d36ba807892ed1a"
             "690a77811d3033b3de226e0a01410429fa713b124484cb2bd7b5557b2c0b9df7b2"
             "b1fee61825eadc5ae6c37a9920d38bfccdc7dc3cb0c47d7b173dbc9db8d37db0a3"
             "3ae487982c59c6f8606e9d1791ffffffff41ed70551dd7e841883ab8f0b16bf041"
             "76b7d1480e4f0af9f3d4c3595768d068000000008b4830450221008513ad65187b"
             "903aed1102d1d0c47688127658c51106753fed0151ce9c16b80902201432b9ebcb"
             "87bd04ceb2de66035fbbaf4bf8b00d1cfe41f1a1f7338f9ad79d210141049d4cf8"
             "0125bf50be1709f718c07ad15d0fc612b7da1f5570dddc35f2a352f0f27c978b06"
             "820edca9ef982c35fda2d255afba340068c5035552368bc7200c1488ffffffff01"
             "00093d00000000001976a9148edb68822f1ad580b043c7b3df2e400f8699eb4888"
             "ac00000000"),
         SER_NETWORK, PROTOCOL_VERSION);
     stream >> block;
 
     CBloomFilter filter(10, 0.000001, 0, BLOOM_UPDATE_P2PUBKEY_ONLY);
     // Match the generation pubkey
     filter.insert(ParseHex("04eaafc2314def4ca98ac970241bcab022b9c1e1f4ea423a20f"
                            "134c876f2c01ec0f0dd5b2e86e7168cefe0d81113c3807420ce"
                            "13ad1357231a2252247d97a46a91"));
     // ...and the output address of the 4th transaction
     filter.insert(ParseHex("b6efd80d99179f4f4ff6f4dd0a007d018c385d21"));
 
     CMerkleBlock merkleBlock(block, filter);
     BOOST_CHECK(merkleBlock.header.GetHash() == block.GetHash());
 
     // We should match the generation outpoint
     const TxId txid1(uint256S(
         "0x147caa76786596590baa4e98f5d9f48b86c7765e489f7a6ff3360fe5c674360b"));
     BOOST_CHECK(filter.contains(COutPoint(txid1, 0)));
     // ... but not the 4th transaction's output (its not pay-2-pubkey)
     const TxId txid2(uint256S(
         "0x02981fa052f0481dbc5868f4fc2166035a10f27a03cfd2de67326471df5bc041"));
     BOOST_CHECK(!filter.contains(COutPoint(txid2, 0)));
 }
 
 BOOST_AUTO_TEST_CASE(merkle_block_4_test_update_none) {
     // Random real block
     // (000000000000b731f2eef9e8c63173adfb07e41bd53eb0ef0a6b720d6cb6dea4)
     // With 7 txes
     CBlock block;
     CDataStream stream(
         ParseHex(
             "0100000082bb869cf3a793432a66e826e05a6fc37469f8efb7421dc88067010000"
             "0000007f16c5962e8bd963659c793ce370d95f093bc7e367117b3c30c1f8fdd0d9"
             "728776381b4d4c86041b554b852907010000000100000000000000000000000000"
             "00000000000000000000000000000000000000ffffffff07044c86041b0136ffff"
             "ffff0100f2052a01000000434104eaafc2314def4ca98ac970241bcab022b9c1e1"
             "f4ea423a20f134c876f2c01ec0f0dd5b2e86e7168cefe0d81113c3807420ce13ad"
             "1357231a2252247d97a46a91ac000000000100000001bcad20a6a29827d1424f08"
             "989255120bf7f3e9e3cdaaa6bb31b0737fe048724300000000494830450220356e"
             "834b046cadc0f8ebb5a8a017b02de59c86305403dad52cd77b55af062ea1022100"
             "9253cd6c119d4729b77c978e1e2aa19f5ea6e0e52b3f16e32fa608cd5bab753901"
             "ffffffff02008d380c010000001976a9142b4b8072ecbba129b6453c63e129e643"
             "207249ca88ac0065cd1d000000001976a9141b8dd13b994bcfc787b32aeadf58cc"
             "b3615cbd5488ac000000000100000003fdacf9b3eb077412e7a968d2e4f11b9a9d"
             "ee312d666187ed77ee7d26af16cb0b000000008c493046022100ea1608e70911ca"
             "0de5af51ba57ad23b9a51db8d28f82c53563c56a05c20f5a87022100a8bdc8b4a8"
             "acc8634c6b420410150775eb7f2474f5615f7fccd65af30f310fbf01410465fdf4"
             "9e29b06b9a1582287b6279014f834edc317695d125ef623c1cc3aaece245bd69fc"
             "ad7508666e9c74a49dc9056d5fc14338ef38118dc4afae5fe2c585caffffffff30"
             "9e1913634ecb50f3c4f83e96e70b2df071b497b8973a3e75429df397b5af830000"
             "00004948304502202bdb79c596a9ffc24e96f4386199aba386e9bc7b6071516e2b"
             "51dda942b3a1ed022100c53a857e76b724fc14d45311eac5019650d415c3abb542"
             "8f3aae16d8e69bec2301ffffffff2089e33491695080c9edc18a428f7d834db5b6"
             "d372df13ce2b1b0e0cbcb1e6c10000000049483045022100d4ce67c5896ee251c8"
             "10ac1ff9ceccd328b497c8f553ab6e08431e7d40bad6b5022033119c0c2b7d792d"
             "31f1187779c7bd95aefd93d90a715586d73801d9b47471c601ffffffff01007144"
             "60030000001976a914c7b55141d097ea5df7a0ed330cf794376e53ec8d88ac0000"
             "000001000000045bf0e214aa4069a3e792ecee1e1bf0c1d397cde8dd08138f4b72"
             "a00681743447000000008b48304502200c45de8c4f3e2c1821f2fc878cba97b1e6"
             "f8807d94930713aa1c86a67b9bf1e40221008581abfef2e30f957815fc89978423"
             "746b2086375ca8ecf359c85c2a5b7c88ad01410462bb73f76ca0994fcb8b4271e6"
             "fb7561f5c0f9ca0cf6485261c4a0dc894f4ab844c6cdfb97cd0b60ffb5018ffd62"
             "38f4d87270efb1d3ae37079b794a92d7ec95ffffffffd669f7d7958d40fc59d225"
             "3d88e0f248e29b599c80bbcec344a83dda5f9aa72c000000008a47304402207812"
             "4c8beeaa825f9e0b30bff96e564dd859432f2d0cb3b72d3d5d93d38d7e93022069"
             "1d233b6c0f995be5acb03d70a7f7a65b6bc9bdd426260f38a1346669507a360141"
             "0462bb73f76ca0994fcb8b4271e6fb7561f5c0f9ca0cf6485261c4a0dc894f4ab8"
             "44c6cdfb97cd0b60ffb5018ffd6238f4d87270efb1d3ae37079b794a92d7ec95ff"
             "fffffff878af0d93f5229a68166cf051fd372bb7a537232946e0a46f53636b4daf"
             "daa4000000008c493046022100c717d1714551663f69c3c5759bdbb3a0fcd3fab0"
             "23abc0e522fe6440de35d8290221008d9cbe25bffc44af2b18e81c58eb37293fd7"
             "fe1c2e7b46fc37ee8c96c50ab1e201410462bb73f76ca0994fcb8b4271e6fb7561"
             "f5c0f9ca0cf6485261c4a0dc894f4ab844c6cdfb97cd0b60ffb5018ffd6238f4d8"
             "7270efb1d3ae37079b794a92d7ec95ffffffff27f2b668859cd7f2f894aa0fd2d9"
             "e60963bcd07c88973f425f999b8cbfd7a1e2000000008c493046022100e0084714"
             "7cbf517bcc2f502f3ddc6d284358d102ed20d47a8aa788a62f0db780022100d17b"
             "2d6fa84dcaf1c95d88d7e7c30385aecf415588d749afd3ec81f6022cecd7014104"
             "62bb73f76ca0994fcb8b4271e6fb7561f5c0f9ca0cf6485261c4a0dc894f4ab844"
             "c6cdfb97cd0b60ffb5018ffd6238f4d87270efb1d3ae37079b794a92d7ec95ffff"
             "ffff0100c817a8040000001976a914b6efd80d99179f4f4ff6f4dd0a007d018c38"
             "5d2188ac000000000100000001834537b2f1ce8ef9373a258e10545ce5a50b758d"
             "f616cd4356e0032554ebd3c4000000008b483045022100e68f422dd7c34fdce11e"
             "eb4509ddae38201773dd62f284e8aa9d96f85099d0b002202243bd399ff96b649a"
             "0fad05fa759d6a882f0af8c90cf7632c2840c29070aec20141045e58067e815c2f"
             "464c6a2a15f987758374203895710c2d452442e28496ff38ba8f5fd901dc20e29e"
             "88477167fe4fc299bf818fd0d9e1632d467b2a3d9503b1aaffffffff0280d7e636"
             "030000001976a914f34c3e10eb387efe872acb614c89e78bfca7815d88ac404b4c"
             "00000000001976a914a84e272933aaf87e1715d7786c51dfaeb5b65a6f88ac0000"
             "0000010000000143ac81c8e6f6ef307dfe17f3d906d999e23e0189fda838c5510d"
             "850927e03ae7000000008c4930460221009c87c344760a64cb8ae6685a3eec2c1a"
             "c1bed5b88c87de51acd0e124f266c16602210082d07c037359c3a257b5c63ebd90"
             "f5a5edf97b2ac1c434b08ca998839f346dd40141040ba7e521fa7946d12edbb1d1"
             "e95a15c34bd4398195e86433c92b431cd315f455fe30032ede69cad9d1e1ed6c3c"
             "4ec0dbfced53438c625462afb792dcb098544bffffffff0240420f000000000019"
             "76a9144676d1b820d63ec272f1900d59d43bc6463d96f888ac40420f0000000000"
             "1976a914648d04341d00d7968b3405c034adc38d4d8fb9bd88ac00000000010000"
             "000248cc917501ea5c55f4a8d2009c0567c40cfe037c2e71af017d0a452ff705e3"
             "f1000000008b483045022100bf5fdc86dc5f08a5d5c8e43a8c9d5b1ed8c65562e2"
             "80007b52b133021acd9acc02205e325d613e555f772802bf413d36ba807892ed1a"
             "690a77811d3033b3de226e0a01410429fa713b124484cb2bd7b5557b2c0b9df7b2"
             "b1fee61825eadc5ae6c37a9920d38bfccdc7dc3cb0c47d7b173dbc9db8d37db0a3"
             "3ae487982c59c6f8606e9d1791ffffffff41ed70551dd7e841883ab8f0b16bf041"
             "76b7d1480e4f0af9f3d4c3595768d068000000008b4830450221008513ad65187b"
             "903aed1102d1d0c47688127658c51106753fed0151ce9c16b80902201432b9ebcb"
             "87bd04ceb2de66035fbbaf4bf8b00d1cfe41f1a1f7338f9ad79d210141049d4cf8"
             "0125bf50be1709f718c07ad15d0fc612b7da1f5570dddc35f2a352f0f27c978b06"
             "820edca9ef982c35fda2d255afba340068c5035552368bc7200c1488ffffffff01"
             "00093d00000000001976a9148edb68822f1ad580b043c7b3df2e400f8699eb4888"
             "ac00000000"),
         SER_NETWORK, PROTOCOL_VERSION);
     stream >> block;
 
     CBloomFilter filter(10, 0.000001, 0, BLOOM_UPDATE_NONE);
     // Match the generation pubkey
     filter.insert(ParseHex("04eaafc2314def4ca98ac970241bcab022b9c1e1f4ea423a20f"
                            "134c876f2c01ec0f0dd5b2e86e7168cefe0d81113c3807420ce"
                            "13ad1357231a2252247d97a46a91"));
     // ...and the output address of the 4th transaction
     filter.insert(ParseHex("b6efd80d99179f4f4ff6f4dd0a007d018c385d21"));
 
     CMerkleBlock merkleBlock(block, filter);
     BOOST_CHECK(merkleBlock.header.GetHash() == block.GetHash());
 
     // We shouldn't match any outpoints (UPDATE_NONE)
     const TxId txid1(uint256S(
         "0x147caa76786596590baa4e98f5d9f48b86c7765e489f7a6ff3360fe5c674360b"));
     BOOST_CHECK(!filter.contains(COutPoint(txid1, 0)));
     const TxId txid2(uint256S(
         "0x02981fa052f0481dbc5868f4fc2166035a10f27a03cfd2de67326471df5bc041"));
     BOOST_CHECK(!filter.contains(COutPoint(txid2, 0)));
 }
 
 static std::vector<uint8_t> RandomData() {
     uint256 r = InsecureRand256();
     return std::vector<uint8_t>(r.begin(), r.end());
 }
 
 BOOST_AUTO_TEST_CASE(rolling_bloom) {
     SeedInsecureRand(SeedRand::ZEROS);
     g_mock_deterministic_tests = true;
 
     // last-100-entry, 1% false positive:
     CRollingBloomFilter rb1(100, 0.01);
 
     // Overfill:
     static const int DATASIZE = 399;
     std::vector<uint8_t> data[DATASIZE];
     for (int i = 0; i < DATASIZE; i++) {
         data[i] = RandomData();
         rb1.insert(data[i]);
     }
     // Last 100 guaranteed to be remembered:
     for (int i = 299; i < DATASIZE; i++) {
         BOOST_CHECK(rb1.contains(data[i]));
     }
 
     // false positive rate is 1%, so we should get about 100 hits if
     // testing 10,000 random keys. We get worst-case false positive
     // behavior when the filter is as full as possible, which is
     // when we've inserted one minus an integer multiple of nElement*2.
     unsigned int nHits = 0;
     for (int i = 0; i < 10000; i++) {
         if (rb1.contains(RandomData())) {
             ++nHits;
         }
     }
     // Expect about 100 hits
     BOOST_CHECK_EQUAL(nHits, 75);
 
     BOOST_CHECK(rb1.contains(data[DATASIZE - 1]));
     rb1.reset();
     BOOST_CHECK(!rb1.contains(data[DATASIZE - 1]));
 
     // Now roll through data, make sure last 100 entries
     // are always remembered:
     for (int i = 0; i < DATASIZE; i++) {
         if (i >= 100) {
             BOOST_CHECK(rb1.contains(data[i - 100]));
         }
         rb1.insert(data[i]);
         BOOST_CHECK(rb1.contains(data[i]));
     }
 
     // Insert 999 more random entries:
     for (int i = 0; i < 999; i++) {
         std::vector<uint8_t> d = RandomData();
         rb1.insert(d);
         BOOST_CHECK(rb1.contains(d));
     }
     // Sanity check to make sure the filter isn't just filling up:
     nHits = 0;
     for (int i = 0; i < DATASIZE; i++) {
         if (rb1.contains(data[i])) {
             ++nHits;
         }
     }
     // Expect about 5 false positives
     BOOST_CHECK_EQUAL(nHits, 6);
 
     // last-1000-entry, 0.01% false positive:
     CRollingBloomFilter rb2(1000, 0.001);
     for (int i = 0; i < DATASIZE; i++) {
         rb2.insert(data[i]);
     }
     // ... room for all of them:
     for (int i = 0; i < DATASIZE; i++) {
         BOOST_CHECK(rb2.contains(data[i]));
     }
     g_mock_deterministic_tests = false;
 }
 
 BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/test/fuzz/bloom_filter.cpp b/src/test/fuzz/bloom_filter.cpp
index dfd8ba806..2e7a48e3b 100644
--- a/src/test/fuzz/bloom_filter.cpp
+++ b/src/test/fuzz/bloom_filter.cpp
@@ -1,87 +1,80 @@
 // Copyright (c) 2020 The Bitcoin Core developers
 // Distributed under the MIT software license, see the accompanying
 // file COPYING or http://www.opensource.org/licenses/mit-license.php.
 
 #include <bloom.h>
 #include <primitives/transaction.h>
 #include <test/fuzz/FuzzedDataProvider.h>
 #include <test/fuzz/fuzz.h>
 #include <test/fuzz/util.h>
 #include <uint256.h>
 
 #include <cassert>
 #include <cstdint>
 #include <string>
 #include <vector>
 
 void test_one_input(const std::vector<uint8_t> &buffer) {
     FuzzedDataProvider fuzzed_data_provider(buffer.data(), buffer.size());
 
     CBloomFilter bloom_filter{
         fuzzed_data_provider.ConsumeIntegralInRange<unsigned int>(1, 10000000),
         1.0 / fuzzed_data_provider.ConsumeIntegralInRange<unsigned int>(
                   1, std::numeric_limits<unsigned int>::max()),
         fuzzed_data_provider.ConsumeIntegral<unsigned int>(),
         static_cast<uint8_t>(fuzzed_data_provider.PickValueInArray(
             {BLOOM_UPDATE_NONE, BLOOM_UPDATE_ALL, BLOOM_UPDATE_P2PUBKEY_ONLY,
              BLOOM_UPDATE_MASK}))};
     while (fuzzed_data_provider.remaining_bytes() > 0) {
-        switch (fuzzed_data_provider.ConsumeIntegralInRange(0, 6)) {
+        switch (fuzzed_data_provider.ConsumeIntegralInRange(0, 4)) {
             case 0: {
                 const std::vector<uint8_t> &b =
                     ConsumeRandomLengthByteVector(fuzzed_data_provider);
                 (void)bloom_filter.contains(b);
                 bloom_filter.insert(b);
                 const bool present = bloom_filter.contains(b);
                 assert(present);
                 break;
             }
             case 1: {
                 const std::optional<COutPoint> out_point =
                     ConsumeDeserializable<COutPoint>(fuzzed_data_provider);
                 if (!out_point) {
                     break;
                 }
                 (void)bloom_filter.contains(*out_point);
                 bloom_filter.insert(*out_point);
                 const bool present = bloom_filter.contains(*out_point);
                 assert(present);
                 break;
             }
             case 2: {
                 const std::optional<uint256> u256 =
                     ConsumeDeserializable<uint256>(fuzzed_data_provider);
                 if (!u256) {
                     break;
                 }
                 (void)bloom_filter.contains(*u256);
                 bloom_filter.insert(*u256);
                 const bool present = bloom_filter.contains(*u256);
                 assert(present);
                 break;
             }
-            case 3:
-                bloom_filter.clear();
-                break;
-            case 4:
-                bloom_filter.reset(
-                    fuzzed_data_provider.ConsumeIntegral<unsigned int>());
-                break;
-            case 5: {
+            case 3: {
                 const std::optional<CMutableTransaction> mut_tx =
                     ConsumeDeserializable<CMutableTransaction>(
                         fuzzed_data_provider);
                 if (!mut_tx) {
                     break;
                 }
                 const CTransaction tx{*mut_tx};
                 (void)bloom_filter.IsRelevantAndUpdate(tx);
                 break;
             }
-            case 6:
+            case 4:
                 bloom_filter.UpdateEmptyFull();
                 break;
         }
         (void)bloom_filter.IsWithinSizeConstraints();
     }
 }