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957 lines
39 KiB
C++
957 lines
39 KiB
C++
// Copyright (c) The Bitcoin Core developers
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// Distributed under the MIT software license, see the accompanying
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// file COPYING or http://www.opensource.org/licenses/mit-license.php.
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#include <cluster_linearize.h>
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#include <serialize.h>
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#include <streams.h>
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#include <test/fuzz/fuzz.h>
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#include <test/fuzz/FuzzedDataProvider.h>
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#include <test/util/cluster_linearize.h>
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#include <util/bitset.h>
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#include <util/feefrac.h>
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#include <algorithm>
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#include <stdint.h>
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#include <vector>
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#include <utility>
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using namespace cluster_linearize;
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namespace {
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/** A simple finder class for candidate sets.
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*
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* This class matches SearchCandidateFinder in interface and behavior, though with fewer
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* optimizations.
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*/
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template<typename SetType>
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class SimpleCandidateFinder
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{
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/** Internal dependency graph. */
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const DepGraph<SetType>& m_depgraph;
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/** Which transaction are left to include. */
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SetType m_todo;
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public:
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/** Construct an SimpleCandidateFinder for a given graph. */
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SimpleCandidateFinder(const DepGraph<SetType>& depgraph LIFETIMEBOUND) noexcept :
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m_depgraph(depgraph), m_todo{SetType::Fill(depgraph.TxCount())} {}
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/** Remove a set of transactions from the set of to-be-linearized ones. */
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void MarkDone(SetType select) noexcept { m_todo -= select; }
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/** Determine whether unlinearized transactions remain. */
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bool AllDone() const noexcept { return m_todo.None(); }
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/** Find a candidate set using at most max_iterations iterations, and the number of iterations
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* actually performed. If that number is less than max_iterations, then the result is optimal.
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*
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* Complexity: O(N * M), where M is the number of connected topological subsets of the cluster.
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* That number is bounded by M <= 2^(N-1).
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*/
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std::pair<SetInfo<SetType>, uint64_t> FindCandidateSet(uint64_t max_iterations) const noexcept
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{
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uint64_t iterations_left = max_iterations;
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// Queue of work units. Each consists of:
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// - inc: set of transactions definitely included
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// - und: set of transactions that can be added to inc still
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std::vector<std::pair<SetType, SetType>> queue;
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// Initially we have just one queue element, with the entire graph in und.
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queue.emplace_back(SetType{}, m_todo);
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// Best solution so far.
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SetInfo best(m_depgraph, m_todo);
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// Process the queue.
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while (!queue.empty() && iterations_left) {
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--iterations_left;
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// Pop top element of the queue.
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auto [inc, und] = queue.back();
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queue.pop_back();
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// Look for a transaction to consider adding/removing.
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bool inc_none = inc.None();
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for (auto split : und) {
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// If inc is empty, consider any split transaction. Otherwise only consider
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// transactions that share ancestry with inc so far (which means only connected
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// sets will be considered).
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if (inc_none || inc.Overlaps(m_depgraph.Ancestors(split))) {
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// Add a queue entry with split included.
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SetInfo new_inc(m_depgraph, inc | (m_todo & m_depgraph.Ancestors(split)));
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queue.emplace_back(new_inc.transactions, und - new_inc.transactions);
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// Add a queue entry with split excluded.
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queue.emplace_back(inc, und - m_depgraph.Descendants(split));
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// Update statistics to account for the candidate new_inc.
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if (new_inc.feerate > best.feerate) best = new_inc;
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break;
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}
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}
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}
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return {std::move(best), max_iterations - iterations_left};
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}
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};
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/** A very simple finder class for optimal candidate sets, which tries every subset.
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*
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* It is even simpler than SimpleCandidateFinder, and is primarily included here to test the
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* correctness of SimpleCandidateFinder, which is then used to test the correctness of
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* SearchCandidateFinder.
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*/
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template<typename SetType>
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class ExhaustiveCandidateFinder
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{
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/** Internal dependency graph. */
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const DepGraph<SetType>& m_depgraph;
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/** Which transaction are left to include. */
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SetType m_todo;
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public:
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/** Construct an ExhaustiveCandidateFinder for a given graph. */
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ExhaustiveCandidateFinder(const DepGraph<SetType>& depgraph LIFETIMEBOUND) noexcept :
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m_depgraph(depgraph), m_todo{SetType::Fill(depgraph.TxCount())} {}
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/** Remove a set of transactions from the set of to-be-linearized ones. */
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void MarkDone(SetType select) noexcept { m_todo -= select; }
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/** Determine whether unlinearized transactions remain. */
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bool AllDone() const noexcept { return m_todo.None(); }
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/** Find the optimal remaining candidate set.
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*
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* Complexity: O(N * 2^N).
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*/
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SetInfo<SetType> FindCandidateSet() const noexcept
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{
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// Best solution so far.
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SetInfo<SetType> best{m_todo, m_depgraph.FeeRate(m_todo)};
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// The number of combinations to try.
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uint64_t limit = (uint64_t{1} << m_todo.Count()) - 1;
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// Try the transitive closure of every non-empty subset of m_todo.
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for (uint64_t x = 1; x < limit; ++x) {
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// If bit number b is set in x, then the remaining ancestors of the b'th remaining
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// transaction in m_todo are included.
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SetType txn;
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auto x_shifted{x};
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for (auto i : m_todo) {
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if (x_shifted & 1) txn |= m_depgraph.Ancestors(i);
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x_shifted >>= 1;
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}
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SetInfo cur(m_depgraph, txn & m_todo);
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if (cur.feerate > best.feerate) best = cur;
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}
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return best;
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}
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};
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/** A simple linearization algorithm.
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*
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* This matches Linearize() in interface and behavior, though with fewer optimizations, lacking
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* the ability to pass in an existing linearization, and using just SimpleCandidateFinder rather
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* than AncestorCandidateFinder and SearchCandidateFinder.
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*/
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template<typename SetType>
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std::pair<std::vector<ClusterIndex>, bool> SimpleLinearize(const DepGraph<SetType>& depgraph, uint64_t max_iterations)
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{
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std::vector<ClusterIndex> linearization;
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SimpleCandidateFinder finder(depgraph);
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SetType todo = SetType::Fill(depgraph.TxCount());
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bool optimal = true;
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while (todo.Any()) {
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auto [candidate, iterations_done] = finder.FindCandidateSet(max_iterations);
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if (iterations_done == max_iterations) optimal = false;
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depgraph.AppendTopo(linearization, candidate.transactions);
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todo -= candidate.transactions;
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finder.MarkDone(candidate.transactions);
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max_iterations -= iterations_done;
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}
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return {std::move(linearization), optimal};
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}
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/** Given a dependency graph, and a todo set, read a topological subset of todo from reader. */
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template<typename SetType>
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SetType ReadTopologicalSet(const DepGraph<SetType>& depgraph, const SetType& todo, SpanReader& reader)
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{
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uint64_t mask{0};
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try {
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reader >> VARINT(mask);
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} catch(const std::ios_base::failure&) {}
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SetType ret;
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for (auto i : todo) {
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if (!ret[i]) {
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if (mask & 1) ret |= depgraph.Ancestors(i);
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mask >>= 1;
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}
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}
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return ret & todo;
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}
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/** Given a dependency graph, construct any valid linearization for it, reading from a SpanReader. */
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template<typename BS>
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std::vector<ClusterIndex> ReadLinearization(const DepGraph<BS>& depgraph, SpanReader& reader)
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{
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std::vector<ClusterIndex> linearization;
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TestBitSet todo = TestBitSet::Fill(depgraph.TxCount());
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// In every iteration one topologically-valid transaction is appended to linearization.
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while (todo.Any()) {
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// Compute the set of transactions with no not-yet-included ancestors.
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TestBitSet potential_next;
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for (auto j : todo) {
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if ((depgraph.Ancestors(j) & todo) == TestBitSet::Singleton(j)) {
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potential_next.Set(j);
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}
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}
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// There must always be one (otherwise there is a cycle in the graph).
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assert(potential_next.Any());
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// Read a number from reader, and interpret it as index into potential_next.
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uint64_t idx{0};
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try {
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reader >> VARINT(idx);
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} catch (const std::ios_base::failure&) {}
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idx %= potential_next.Count();
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// Find out which transaction that corresponds to.
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for (auto j : potential_next) {
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if (idx == 0) {
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// When found, add it to linearization and remove it from todo.
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linearization.push_back(j);
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assert(todo[j]);
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todo.Reset(j);
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break;
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}
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--idx;
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}
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}
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return linearization;
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}
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} // namespace
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FUZZ_TARGET(clusterlin_add_dependency)
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{
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// Verify that computing a DepGraph from a cluster, or building it step by step using AddDependency
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// have the same effect.
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// Construct a cluster of a certain length, with no dependencies.
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FuzzedDataProvider provider(buffer.data(), buffer.size());
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auto num_tx = provider.ConsumeIntegralInRange<ClusterIndex>(2, 32);
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Cluster<TestBitSet> cluster(num_tx, std::pair{FeeFrac{0, 1}, TestBitSet{}});
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// Construct the corresponding DepGraph object (also no dependencies).
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DepGraph depgraph(cluster);
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SanityCheck(depgraph);
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// Read (parent, child) pairs, and add them to the cluster and depgraph.
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LIMITED_WHILE(provider.remaining_bytes() > 0, TestBitSet::Size() * TestBitSet::Size()) {
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auto parent = provider.ConsumeIntegralInRange<ClusterIndex>(0, num_tx - 1);
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auto child = provider.ConsumeIntegralInRange<ClusterIndex>(0, num_tx - 2);
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child += (child >= parent);
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cluster[child].second.Set(parent);
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depgraph.AddDependency(parent, child);
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assert(depgraph.Ancestors(child)[parent]);
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assert(depgraph.Descendants(parent)[child]);
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}
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// Sanity check the result.
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SanityCheck(depgraph);
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// Verify that the resulting DepGraph matches one recomputed from the cluster.
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assert(DepGraph(cluster) == depgraph);
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}
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FUZZ_TARGET(clusterlin_cluster_serialization)
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{
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// Verify that any graph of transactions has its ancestry correctly computed by DepGraph, and
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// if it is a DAG, that it can be serialized as a DepGraph in a way that roundtrips. This
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// guarantees that any acyclic cluster has a corresponding DepGraph serialization.
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FuzzedDataProvider provider(buffer.data(), buffer.size());
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// Construct a cluster in a naive way (using a FuzzedDataProvider-based serialization).
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Cluster<TestBitSet> cluster;
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auto num_tx = provider.ConsumeIntegralInRange<ClusterIndex>(1, 32);
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cluster.resize(num_tx);
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for (ClusterIndex i = 0; i < num_tx; ++i) {
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cluster[i].first.size = provider.ConsumeIntegralInRange<int32_t>(1, 0x3fffff);
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cluster[i].first.fee = provider.ConsumeIntegralInRange<int64_t>(-0x8000000000000, 0x7ffffffffffff);
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for (ClusterIndex j = 0; j < num_tx; ++j) {
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if (i == j) continue;
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if (provider.ConsumeBool()) cluster[i].second.Set(j);
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}
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}
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// Construct dependency graph, and verify it matches the cluster (which includes a round-trip
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// check for the serialization).
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DepGraph depgraph(cluster);
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VerifyDepGraphFromCluster(cluster, depgraph);
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}
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FUZZ_TARGET(clusterlin_depgraph_serialization)
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{
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// Verify that any deserialized depgraph is acyclic and roundtrips to an identical depgraph.
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// Construct a graph by deserializing.
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SpanReader reader(buffer);
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DepGraph<TestBitSet> depgraph;
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try {
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reader >> Using<DepGraphFormatter>(depgraph);
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} catch (const std::ios_base::failure&) {}
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SanityCheck(depgraph);
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// Verify the graph is a DAG.
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assert(IsAcyclic(depgraph));
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}
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FUZZ_TARGET(clusterlin_components)
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{
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// Verify the behavior of DepGraphs's FindConnectedComponent and IsConnected functions.
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// Construct a depgraph.
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SpanReader reader(buffer);
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DepGraph<TestBitSet> depgraph;
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try {
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reader >> Using<DepGraphFormatter>(depgraph);
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} catch (const std::ios_base::failure&) {}
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TestBitSet todo = TestBitSet::Fill(depgraph.TxCount());
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while (todo.Any()) {
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// Find a connected component inside todo.
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auto component = depgraph.FindConnectedComponent(todo);
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// The component must be a subset of todo and non-empty.
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assert(component.IsSubsetOf(todo));
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assert(component.Any());
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// If todo is the entire graph, and the entire graph is connected, then the component must
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// be the entire graph.
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if (todo == TestBitSet::Fill(depgraph.TxCount())) {
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assert((component == todo) == depgraph.IsConnected());
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}
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// If subset is connected, then component must match subset.
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assert((component == todo) == depgraph.IsConnected(todo));
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// The component cannot have any ancestors or descendants outside of component but in todo.
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for (auto i : component) {
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assert((depgraph.Ancestors(i) & todo).IsSubsetOf(component));
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assert((depgraph.Descendants(i) & todo).IsSubsetOf(component));
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}
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// Starting from any component element, we must be able to reach every element.
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for (auto i : component) {
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// Start with just i as reachable.
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TestBitSet reachable = TestBitSet::Singleton(i);
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// Add in-todo descendants and ancestors to reachable until it does not change anymore.
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while (true) {
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TestBitSet new_reachable = reachable;
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for (auto j : new_reachable) {
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new_reachable |= depgraph.Ancestors(j) & todo;
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new_reachable |= depgraph.Descendants(j) & todo;
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}
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if (new_reachable == reachable) break;
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reachable = new_reachable;
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}
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// Verify that the result is the entire component.
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assert(component == reachable);
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}
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// Construct an arbitrary subset of todo.
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uint64_t subset_bits{0};
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try {
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reader >> VARINT(subset_bits);
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} catch (const std::ios_base::failure&) {}
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TestBitSet subset;
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for (ClusterIndex i = 0; i < depgraph.TxCount(); ++i) {
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if (todo[i]) {
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if (subset_bits & 1) subset.Set(i);
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subset_bits >>= 1;
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}
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}
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// Which must be non-empty.
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if (subset.None()) subset = TestBitSet::Singleton(todo.First());
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// Remove it from todo.
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todo -= subset;
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}
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// No components can be found in an empty subset.
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assert(depgraph.FindConnectedComponent(todo).None());
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}
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FUZZ_TARGET(clusterlin_chunking)
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{
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// Verify the correctness of the ChunkLinearization function.
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// Construct a graph by deserializing.
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SpanReader reader(buffer);
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DepGraph<TestBitSet> depgraph;
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try {
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reader >> Using<DepGraphFormatter>(depgraph);
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} catch (const std::ios_base::failure&) {}
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// Read a valid linearization for depgraph.
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auto linearization = ReadLinearization(depgraph, reader);
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// Invoke the chunking function.
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auto chunking = ChunkLinearization(depgraph, linearization);
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// Verify that chunk feerates are monotonically non-increasing.
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for (size_t i = 1; i < chunking.size(); ++i) {
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assert(!(chunking[i] >> chunking[i - 1]));
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}
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// Naively recompute the chunks (each is the highest-feerate prefix of what remains).
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auto todo = TestBitSet::Fill(depgraph.TxCount());
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for (const auto& chunk_feerate : chunking) {
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assert(todo.Any());
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SetInfo<TestBitSet> accumulator, best;
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for (ClusterIndex idx : linearization) {
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if (todo[idx]) {
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accumulator |= SetInfo(depgraph, idx);
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if (best.feerate.IsEmpty() || accumulator.feerate >> best.feerate) {
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best = accumulator;
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}
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}
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}
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assert(chunk_feerate == best.feerate);
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assert(best.transactions.IsSubsetOf(todo));
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todo -= best.transactions;
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}
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assert(todo.None());
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}
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FUZZ_TARGET(clusterlin_ancestor_finder)
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{
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// Verify that AncestorCandidateFinder works as expected.
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// Retrieve a depgraph from the fuzz input.
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SpanReader reader(buffer);
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DepGraph<TestBitSet> depgraph;
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try {
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reader >> Using<DepGraphFormatter>(depgraph);
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} catch (const std::ios_base::failure&) {}
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AncestorCandidateFinder anc_finder(depgraph);
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auto todo = TestBitSet::Fill(depgraph.TxCount());
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while (todo.Any()) {
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// Call the ancestor finder's FindCandidateSet for what remains of the graph.
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assert(!anc_finder.AllDone());
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auto best_anc = anc_finder.FindCandidateSet();
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// Sanity check the result.
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assert(best_anc.transactions.Any());
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assert(best_anc.transactions.IsSubsetOf(todo));
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assert(depgraph.FeeRate(best_anc.transactions) == best_anc.feerate);
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assert(depgraph.IsConnected(best_anc.transactions));
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// Check that it is topologically valid.
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for (auto i : best_anc.transactions) {
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assert((depgraph.Ancestors(i) & todo).IsSubsetOf(best_anc.transactions));
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}
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// Compute all remaining ancestor sets.
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std::optional<SetInfo<TestBitSet>> real_best_anc;
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for (auto i : todo) {
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SetInfo info(depgraph, todo & depgraph.Ancestors(i));
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if (!real_best_anc.has_value() || info.feerate > real_best_anc->feerate) {
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real_best_anc = info;
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}
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}
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// The set returned by anc_finder must equal the real best ancestor sets.
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assert(real_best_anc.has_value());
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assert(*real_best_anc == best_anc);
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// Find a topologically valid subset of transactions to remove from the graph.
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auto del_set = ReadTopologicalSet(depgraph, todo, reader);
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// If we did not find anything, use best_anc itself, because we should remove something.
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if (del_set.None()) del_set = best_anc.transactions;
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todo -= del_set;
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anc_finder.MarkDone(del_set);
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}
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assert(anc_finder.AllDone());
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}
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static constexpr auto MAX_SIMPLE_ITERATIONS = 300000;
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FUZZ_TARGET(clusterlin_search_finder)
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{
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// Verify that SearchCandidateFinder works as expected by sanity checking the results
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// and comparing with the results from SimpleCandidateFinder, ExhaustiveCandidateFinder, and
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// AncestorCandidateFinder.
|
|
|
|
// Retrieve an RNG seed and a depgraph from the fuzz input.
|
|
SpanReader reader(buffer);
|
|
DepGraph<TestBitSet> depgraph;
|
|
uint64_t rng_seed{0};
|
|
try {
|
|
reader >> Using<DepGraphFormatter>(depgraph) >> rng_seed;
|
|
} catch (const std::ios_base::failure&) {}
|
|
|
|
// Instantiate ALL the candidate finders.
|
|
SearchCandidateFinder src_finder(depgraph, rng_seed);
|
|
SimpleCandidateFinder smp_finder(depgraph);
|
|
ExhaustiveCandidateFinder exh_finder(depgraph);
|
|
AncestorCandidateFinder anc_finder(depgraph);
|
|
|
|
auto todo = TestBitSet::Fill(depgraph.TxCount());
|
|
while (todo.Any()) {
|
|
assert(!src_finder.AllDone());
|
|
assert(!smp_finder.AllDone());
|
|
assert(!exh_finder.AllDone());
|
|
assert(!anc_finder.AllDone());
|
|
|
|
// For each iteration, read an iteration count limit from the fuzz input.
|
|
uint64_t max_iterations = 1;
|
|
try {
|
|
reader >> VARINT(max_iterations);
|
|
} catch (const std::ios_base::failure&) {}
|
|
max_iterations &= 0xfffff;
|
|
|
|
// Read an initial subset from the fuzz input.
|
|
SetInfo init_best(depgraph, ReadTopologicalSet(depgraph, todo, reader));
|
|
|
|
// Call the search finder's FindCandidateSet for what remains of the graph.
|
|
auto [found, iterations_done] = src_finder.FindCandidateSet(max_iterations, init_best);
|
|
|
|
// Sanity check the result.
|
|
assert(iterations_done <= max_iterations);
|
|
assert(found.transactions.Any());
|
|
assert(found.transactions.IsSubsetOf(todo));
|
|
assert(depgraph.FeeRate(found.transactions) == found.feerate);
|
|
if (!init_best.feerate.IsEmpty()) assert(found.feerate >= init_best.feerate);
|
|
// Check that it is topologically valid.
|
|
for (auto i : found.transactions) {
|
|
assert(found.transactions.IsSupersetOf(depgraph.Ancestors(i) & todo));
|
|
}
|
|
|
|
// At most 2^N-1 iterations can be required: the number of non-empty subsets a graph with N
|
|
// transactions has.
|
|
assert(iterations_done <= ((uint64_t{1} << todo.Count()) - 1));
|
|
|
|
// Perform quality checks only if SearchCandidateFinder claims an optimal result.
|
|
if (iterations_done < max_iterations) {
|
|
// Optimal sets are always connected.
|
|
assert(depgraph.IsConnected(found.transactions));
|
|
|
|
// Compare with SimpleCandidateFinder.
|
|
auto [simple, simple_iters] = smp_finder.FindCandidateSet(MAX_SIMPLE_ITERATIONS);
|
|
assert(found.feerate >= simple.feerate);
|
|
if (simple_iters < MAX_SIMPLE_ITERATIONS) {
|
|
assert(found.feerate == simple.feerate);
|
|
}
|
|
|
|
// Compare with AncestorCandidateFinder;
|
|
auto anc = anc_finder.FindCandidateSet();
|
|
assert(found.feerate >= anc.feerate);
|
|
|
|
// Compare with ExhaustiveCandidateFinder. This quickly gets computationally expensive
|
|
// for large clusters (O(2^n)), so only do it for sufficiently small ones.
|
|
if (todo.Count() <= 12) {
|
|
auto exhaustive = exh_finder.FindCandidateSet();
|
|
assert(exhaustive.feerate == found.feerate);
|
|
// Also compare ExhaustiveCandidateFinder with SimpleCandidateFinder (this is
|
|
// primarily a test for SimpleCandidateFinder's correctness).
|
|
assert(exhaustive.feerate >= simple.feerate);
|
|
if (simple_iters < MAX_SIMPLE_ITERATIONS) {
|
|
assert(exhaustive.feerate == simple.feerate);
|
|
}
|
|
}
|
|
}
|
|
|
|
// Find a topologically valid subset of transactions to remove from the graph.
|
|
auto del_set = ReadTopologicalSet(depgraph, todo, reader);
|
|
// If we did not find anything, use found itself, because we should remove something.
|
|
if (del_set.None()) del_set = found.transactions;
|
|
todo -= del_set;
|
|
src_finder.MarkDone(del_set);
|
|
smp_finder.MarkDone(del_set);
|
|
exh_finder.MarkDone(del_set);
|
|
anc_finder.MarkDone(del_set);
|
|
}
|
|
|
|
assert(src_finder.AllDone());
|
|
assert(smp_finder.AllDone());
|
|
assert(exh_finder.AllDone());
|
|
assert(anc_finder.AllDone());
|
|
}
|
|
|
|
FUZZ_TARGET(clusterlin_linearization_chunking)
|
|
{
|
|
// Verify the behavior of LinearizationChunking.
|
|
|
|
// Retrieve a depgraph from the fuzz input.
|
|
SpanReader reader(buffer);
|
|
DepGraph<TestBitSet> depgraph;
|
|
try {
|
|
reader >> Using<DepGraphFormatter>(depgraph);
|
|
} catch (const std::ios_base::failure&) {}
|
|
|
|
// Retrieve a topologically-valid subset of depgraph.
|
|
auto todo = TestBitSet::Fill(depgraph.TxCount());
|
|
auto subset = SetInfo(depgraph, ReadTopologicalSet(depgraph, todo, reader));
|
|
|
|
// Retrieve a valid linearization for depgraph.
|
|
auto linearization = ReadLinearization(depgraph, reader);
|
|
|
|
// Construct a LinearizationChunking object, initially for the whole linearization.
|
|
LinearizationChunking chunking(depgraph, linearization);
|
|
|
|
// Incrementally remove transactions from the chunking object, and check various properties at
|
|
// every step.
|
|
while (todo.Any()) {
|
|
assert(chunking.NumChunksLeft() > 0);
|
|
|
|
// Construct linearization with just todo.
|
|
std::vector<ClusterIndex> linearization_left;
|
|
for (auto i : linearization) {
|
|
if (todo[i]) linearization_left.push_back(i);
|
|
}
|
|
|
|
// Compute the chunking for linearization_left.
|
|
auto chunking_left = ChunkLinearization(depgraph, linearization_left);
|
|
|
|
// Verify that it matches the feerates of the chunks of chunking.
|
|
assert(chunking.NumChunksLeft() == chunking_left.size());
|
|
for (ClusterIndex i = 0; i < chunking.NumChunksLeft(); ++i) {
|
|
assert(chunking.GetChunk(i).feerate == chunking_left[i]);
|
|
}
|
|
|
|
// Check consistency of chunking.
|
|
TestBitSet combined;
|
|
for (ClusterIndex i = 0; i < chunking.NumChunksLeft(); ++i) {
|
|
const auto& chunk_info = chunking.GetChunk(i);
|
|
// Chunks must be non-empty.
|
|
assert(chunk_info.transactions.Any());
|
|
// Chunk feerates must be monotonically non-increasing.
|
|
if (i > 0) assert(!(chunk_info.feerate >> chunking.GetChunk(i - 1).feerate));
|
|
// Chunks must be a subset of what is left of the linearization.
|
|
assert(chunk_info.transactions.IsSubsetOf(todo));
|
|
// Chunks' claimed feerates must match their transactions' aggregate feerate.
|
|
assert(depgraph.FeeRate(chunk_info.transactions) == chunk_info.feerate);
|
|
// Chunks must be the highest-feerate remaining prefix.
|
|
SetInfo<TestBitSet> accumulator, best;
|
|
for (auto j : linearization) {
|
|
if (todo[j] && !combined[j]) {
|
|
accumulator |= SetInfo(depgraph, j);
|
|
if (best.feerate.IsEmpty() || accumulator.feerate > best.feerate) {
|
|
best = accumulator;
|
|
}
|
|
}
|
|
}
|
|
assert(best.transactions == chunk_info.transactions);
|
|
assert(best.feerate == chunk_info.feerate);
|
|
// Chunks cannot overlap.
|
|
assert(!chunk_info.transactions.Overlaps(combined));
|
|
combined |= chunk_info.transactions;
|
|
// Chunks must be topological.
|
|
for (auto idx : chunk_info.transactions) {
|
|
assert((depgraph.Ancestors(idx) & todo).IsSubsetOf(combined));
|
|
}
|
|
}
|
|
assert(combined == todo);
|
|
|
|
// Verify the expected properties of LinearizationChunking::IntersectPrefixes:
|
|
auto intersect = chunking.IntersectPrefixes(subset);
|
|
// - Intersecting again doesn't change the result.
|
|
assert(chunking.IntersectPrefixes(intersect) == intersect);
|
|
// - The intersection is topological.
|
|
TestBitSet intersect_anc;
|
|
for (auto idx : intersect.transactions) {
|
|
intersect_anc |= (depgraph.Ancestors(idx) & todo);
|
|
}
|
|
assert(intersect.transactions == intersect_anc);
|
|
// - The claimed intersection feerate matches its transactions.
|
|
assert(intersect.feerate == depgraph.FeeRate(intersect.transactions));
|
|
// - The intersection may only be empty if its input is empty.
|
|
assert(intersect.transactions.Any() == subset.transactions.Any());
|
|
// - The intersection feerate must be as high as the input.
|
|
assert(intersect.feerate >= subset.feerate);
|
|
// - No non-empty intersection between the intersection and a prefix of the chunks of the
|
|
// remainder of the linearization may be better than the intersection.
|
|
TestBitSet prefix;
|
|
for (ClusterIndex i = 0; i < chunking.NumChunksLeft(); ++i) {
|
|
prefix |= chunking.GetChunk(i).transactions;
|
|
auto reintersect = SetInfo(depgraph, prefix & intersect.transactions);
|
|
if (!reintersect.feerate.IsEmpty()) {
|
|
assert(reintersect.feerate <= intersect.feerate);
|
|
}
|
|
}
|
|
|
|
// Find a subset to remove from linearization.
|
|
auto done = ReadTopologicalSet(depgraph, todo, reader);
|
|
if (done.None()) {
|
|
// We need to remove a non-empty subset, so fall back to the unlinearized ancestors of
|
|
// the first transaction in todo if done is empty.
|
|
done = depgraph.Ancestors(todo.First()) & todo;
|
|
}
|
|
todo -= done;
|
|
chunking.MarkDone(done);
|
|
subset = SetInfo(depgraph, subset.transactions - done);
|
|
}
|
|
|
|
assert(chunking.NumChunksLeft() == 0);
|
|
}
|
|
|
|
FUZZ_TARGET(clusterlin_linearize)
|
|
{
|
|
// Verify the behavior of Linearize().
|
|
|
|
// Retrieve an RNG seed, an iteration count, and a depgraph from the fuzz input.
|
|
SpanReader reader(buffer);
|
|
DepGraph<TestBitSet> depgraph;
|
|
uint64_t rng_seed{0};
|
|
uint64_t iter_count{0};
|
|
try {
|
|
reader >> VARINT(iter_count) >> Using<DepGraphFormatter>(depgraph) >> rng_seed;
|
|
} catch (const std::ios_base::failure&) {}
|
|
|
|
// Optionally construct an old linearization for it.
|
|
std::vector<ClusterIndex> old_linearization;
|
|
{
|
|
uint8_t have_old_linearization{0};
|
|
try {
|
|
reader >> have_old_linearization;
|
|
} catch(const std::ios_base::failure&) {}
|
|
if (have_old_linearization & 1) {
|
|
old_linearization = ReadLinearization(depgraph, reader);
|
|
SanityCheck(depgraph, old_linearization);
|
|
}
|
|
}
|
|
|
|
// Invoke Linearize().
|
|
iter_count &= 0x7ffff;
|
|
auto [linearization, optimal] = Linearize(depgraph, iter_count, rng_seed, old_linearization);
|
|
SanityCheck(depgraph, linearization);
|
|
auto chunking = ChunkLinearization(depgraph, linearization);
|
|
|
|
// Linearization must always be as good as the old one, if provided.
|
|
if (!old_linearization.empty()) {
|
|
auto old_chunking = ChunkLinearization(depgraph, old_linearization);
|
|
auto cmp = CompareChunks(chunking, old_chunking);
|
|
assert(cmp >= 0);
|
|
}
|
|
|
|
// If the iteration count is sufficiently high, an optimal linearization must be found.
|
|
// Each linearization step can use up to 2^k iterations, with steps k=1..n. That sum is
|
|
// 2 * (2^n - 1)
|
|
const uint64_t n = depgraph.TxCount();
|
|
if (n <= 18 && iter_count > 2U * ((uint64_t{1} << n) - 1U)) {
|
|
assert(optimal);
|
|
}
|
|
|
|
// If Linearize claims optimal result, run quality tests.
|
|
if (optimal) {
|
|
// It must be as good as SimpleLinearize.
|
|
auto [simple_linearization, simple_optimal] = SimpleLinearize(depgraph, MAX_SIMPLE_ITERATIONS);
|
|
SanityCheck(depgraph, simple_linearization);
|
|
auto simple_chunking = ChunkLinearization(depgraph, simple_linearization);
|
|
auto cmp = CompareChunks(chunking, simple_chunking);
|
|
assert(cmp >= 0);
|
|
// If SimpleLinearize finds the optimal result too, they must be equal (if not,
|
|
// SimpleLinearize is broken).
|
|
if (simple_optimal) assert(cmp == 0);
|
|
|
|
// Only for very small clusters, test every topologically-valid permutation.
|
|
if (depgraph.TxCount() <= 7) {
|
|
std::vector<ClusterIndex> perm_linearization(depgraph.TxCount());
|
|
for (ClusterIndex i = 0; i < depgraph.TxCount(); ++i) perm_linearization[i] = i;
|
|
// Iterate over all valid permutations.
|
|
do {
|
|
// Determine whether perm_linearization is topological.
|
|
TestBitSet perm_done;
|
|
bool perm_is_topo{true};
|
|
for (auto i : perm_linearization) {
|
|
perm_done.Set(i);
|
|
if (!depgraph.Ancestors(i).IsSubsetOf(perm_done)) {
|
|
perm_is_topo = false;
|
|
break;
|
|
}
|
|
}
|
|
// If so, verify that the obtained linearization is as good as the permutation.
|
|
if (perm_is_topo) {
|
|
auto perm_chunking = ChunkLinearization(depgraph, perm_linearization);
|
|
auto cmp = CompareChunks(chunking, perm_chunking);
|
|
assert(cmp >= 0);
|
|
}
|
|
} while(std::next_permutation(perm_linearization.begin(), perm_linearization.end()));
|
|
}
|
|
}
|
|
}
|
|
|
|
FUZZ_TARGET(clusterlin_postlinearize)
|
|
{
|
|
// Verify expected properties of PostLinearize() on arbitrary linearizations.
|
|
|
|
// Retrieve a depgraph from the fuzz input.
|
|
SpanReader reader(buffer);
|
|
DepGraph<TestBitSet> depgraph;
|
|
try {
|
|
reader >> Using<DepGraphFormatter>(depgraph);
|
|
} catch (const std::ios_base::failure&) {}
|
|
|
|
// Retrieve a linearization from the fuzz input.
|
|
std::vector<ClusterIndex> linearization;
|
|
linearization = ReadLinearization(depgraph, reader);
|
|
SanityCheck(depgraph, linearization);
|
|
|
|
// Produce a post-processed version.
|
|
auto post_linearization = linearization;
|
|
PostLinearize(depgraph, post_linearization);
|
|
SanityCheck(depgraph, post_linearization);
|
|
|
|
// Compare diagrams: post-linearization cannot worsen anywhere.
|
|
auto chunking = ChunkLinearization(depgraph, linearization);
|
|
auto post_chunking = ChunkLinearization(depgraph, post_linearization);
|
|
auto cmp = CompareChunks(post_chunking, chunking);
|
|
assert(cmp >= 0);
|
|
|
|
// Run again, things can keep improving (and never get worse)
|
|
auto post_post_linearization = post_linearization;
|
|
PostLinearize(depgraph, post_post_linearization);
|
|
SanityCheck(depgraph, post_post_linearization);
|
|
auto post_post_chunking = ChunkLinearization(depgraph, post_post_linearization);
|
|
cmp = CompareChunks(post_post_chunking, post_chunking);
|
|
assert(cmp >= 0);
|
|
|
|
// The chunks that come out of postlinearizing are always connected.
|
|
LinearizationChunking linchunking(depgraph, post_linearization);
|
|
while (linchunking.NumChunksLeft()) {
|
|
assert(depgraph.IsConnected(linchunking.GetChunk(0).transactions));
|
|
linchunking.MarkDone(linchunking.GetChunk(0).transactions);
|
|
}
|
|
}
|
|
|
|
FUZZ_TARGET(clusterlin_postlinearize_tree)
|
|
{
|
|
// Verify expected properties of PostLinearize() on linearizations of graphs that form either
|
|
// an upright or reverse tree structure.
|
|
|
|
// Construct a direction, RNG seed, and an arbitrary graph from the fuzz input.
|
|
SpanReader reader(buffer);
|
|
uint64_t rng_seed{0};
|
|
DepGraph<TestBitSet> depgraph_gen;
|
|
uint8_t direction{0};
|
|
try {
|
|
reader >> direction >> rng_seed >> Using<DepGraphFormatter>(depgraph_gen);
|
|
} catch (const std::ios_base::failure&) {}
|
|
|
|
// Now construct a new graph, copying the nodes, but leaving only the first parent (even
|
|
// direction) or the first child (odd direction).
|
|
DepGraph<TestBitSet> depgraph_tree;
|
|
for (ClusterIndex i = 0; i < depgraph_gen.TxCount(); ++i) {
|
|
depgraph_tree.AddTransaction(depgraph_gen.FeeRate(i));
|
|
}
|
|
if (direction & 1) {
|
|
for (ClusterIndex i = 0; i < depgraph_gen.TxCount(); ++i) {
|
|
auto children = depgraph_gen.Descendants(i) - TestBitSet::Singleton(i);
|
|
// Remove descendants that are children of other descendants.
|
|
for (auto j : children) {
|
|
if (!children[j]) continue;
|
|
children -= depgraph_gen.Descendants(j);
|
|
children.Set(j);
|
|
}
|
|
if (children.Any()) depgraph_tree.AddDependency(i, children.First());
|
|
}
|
|
} else {
|
|
for (ClusterIndex i = 0; i < depgraph_gen.TxCount(); ++i) {
|
|
auto parents = depgraph_gen.Ancestors(i) - TestBitSet::Singleton(i);
|
|
// Remove ancestors that are parents of other ancestors.
|
|
for (auto j : parents) {
|
|
if (!parents[j]) continue;
|
|
parents -= depgraph_gen.Ancestors(j);
|
|
parents.Set(j);
|
|
}
|
|
if (parents.Any()) depgraph_tree.AddDependency(parents.First(), i);
|
|
}
|
|
}
|
|
|
|
// Retrieve a linearization from the fuzz input.
|
|
std::vector<ClusterIndex> linearization;
|
|
linearization = ReadLinearization(depgraph_tree, reader);
|
|
SanityCheck(depgraph_tree, linearization);
|
|
|
|
// Produce a postlinearized version.
|
|
auto post_linearization = linearization;
|
|
PostLinearize(depgraph_tree, post_linearization);
|
|
SanityCheck(depgraph_tree, post_linearization);
|
|
|
|
// Compare diagrams.
|
|
auto chunking = ChunkLinearization(depgraph_tree, linearization);
|
|
auto post_chunking = ChunkLinearization(depgraph_tree, post_linearization);
|
|
auto cmp = CompareChunks(post_chunking, chunking);
|
|
assert(cmp >= 0);
|
|
|
|
// Verify that post-linearizing again does not change the diagram. The result must be identical
|
|
// as post_linearization ought to be optimal already with a tree-structured graph.
|
|
auto post_post_linearization = post_linearization;
|
|
PostLinearize(depgraph_tree, post_linearization);
|
|
SanityCheck(depgraph_tree, post_linearization);
|
|
auto post_post_chunking = ChunkLinearization(depgraph_tree, post_post_linearization);
|
|
auto cmp_post = CompareChunks(post_post_chunking, post_chunking);
|
|
assert(cmp_post == 0);
|
|
|
|
// Try to find an even better linearization directly. This must not change the diagram for the
|
|
// same reason.
|
|
auto [opt_linearization, _optimal] = Linearize(depgraph_tree, 100000, rng_seed, post_linearization);
|
|
auto opt_chunking = ChunkLinearization(depgraph_tree, opt_linearization);
|
|
auto cmp_opt = CompareChunks(opt_chunking, post_chunking);
|
|
assert(cmp_opt == 0);
|
|
}
|
|
|
|
FUZZ_TARGET(clusterlin_postlinearize_moved_leaf)
|
|
{
|
|
// Verify that taking an existing linearization, and moving a leaf to the back, potentially
|
|
// increasing its fee, and then post-linearizing, results in something as good as the
|
|
// original. This guarantees that in an RBF that replaces a transaction with one of the same
|
|
// size but higher fee, applying the "remove conflicts, append new transaction, postlinearize"
|
|
// process will never worsen linearization quality.
|
|
|
|
// Construct an arbitrary graph and a fee from the fuzz input.
|
|
SpanReader reader(buffer);
|
|
DepGraph<TestBitSet> depgraph;
|
|
int32_t fee_inc{0};
|
|
try {
|
|
uint64_t fee_inc_code;
|
|
reader >> Using<DepGraphFormatter>(depgraph) >> VARINT(fee_inc_code);
|
|
fee_inc = fee_inc_code & 0x3ffff;
|
|
} catch (const std::ios_base::failure&) {}
|
|
if (depgraph.TxCount() == 0) return;
|
|
|
|
// Retrieve two linearizations from the fuzz input.
|
|
auto lin = ReadLinearization(depgraph, reader);
|
|
auto lin_leaf = ReadLinearization(depgraph, reader);
|
|
|
|
// Construct a linearization identical to lin, but with the tail end of lin_leaf moved to the
|
|
// back.
|
|
std::vector<ClusterIndex> lin_moved;
|
|
for (auto i : lin) {
|
|
if (i != lin_leaf.back()) lin_moved.push_back(i);
|
|
}
|
|
lin_moved.push_back(lin_leaf.back());
|
|
|
|
// Postlinearize lin_moved.
|
|
PostLinearize(depgraph, lin_moved);
|
|
SanityCheck(depgraph, lin_moved);
|
|
|
|
// Compare diagrams (applying the fee delta after computing the old one).
|
|
auto old_chunking = ChunkLinearization(depgraph, lin);
|
|
depgraph.FeeRate(lin_leaf.back()).fee += fee_inc;
|
|
auto new_chunking = ChunkLinearization(depgraph, lin_moved);
|
|
auto cmp = CompareChunks(new_chunking, old_chunking);
|
|
assert(cmp >= 0);
|
|
}
|
|
|
|
FUZZ_TARGET(clusterlin_merge)
|
|
{
|
|
// Construct an arbitrary graph from the fuzz input.
|
|
SpanReader reader(buffer);
|
|
DepGraph<TestBitSet> depgraph;
|
|
try {
|
|
reader >> Using<DepGraphFormatter>(depgraph);
|
|
} catch (const std::ios_base::failure&) {}
|
|
|
|
// Retrieve two linearizations from the fuzz input.
|
|
auto lin1 = ReadLinearization(depgraph, reader);
|
|
auto lin2 = ReadLinearization(depgraph, reader);
|
|
|
|
// Merge the two.
|
|
auto lin_merged = MergeLinearizations(depgraph, lin1, lin2);
|
|
|
|
// Compute chunkings and compare.
|
|
auto chunking1 = ChunkLinearization(depgraph, lin1);
|
|
auto chunking2 = ChunkLinearization(depgraph, lin2);
|
|
auto chunking_merged = ChunkLinearization(depgraph, lin_merged);
|
|
auto cmp1 = CompareChunks(chunking_merged, chunking1);
|
|
assert(cmp1 >= 0);
|
|
auto cmp2 = CompareChunks(chunking_merged, chunking2);
|
|
assert(cmp2 >= 0);
|
|
}
|