This class groups transactions that have been confirmed in blocks into buckets, based on either their fee or their priority. Then for each bucket, the class calculates what percentage of the transactions were confirmed within various numbers of blocks. It does this by keeping an exponentially decaying moving history for each bucket and confirm block count of the percentage of transactions in that bucket that were confirmed within that number of blocks.
-Eliminate txs which didn't have all inputs available at entry from fee/pri calcs
-Add dynamic breakpoints and tracking of confirmation delays in mempool transactions
-Remove old CMinerPolicyEstimator and CBlockAverage code
-New smartfees.py
-Pass a flag to the estimation code, using IsInitialBlockDownload as a proxy for when we are still catching up and we shouldn't be counting how many blocks it takes for transactions to be included.
-Add a policyestimator unit test
o Remove unused Leave and GetLock functions
o Make Enter and TryEnter private.
o Simplify Enter and TryEnter.
boost::unique_lock doesn't really know whether the
mutex it wraps is locked or not when the defer_lock
option is used.
The boost::recursive_mutex does not expose this
information, so unique_lock only infers this
knowledge. When taking the lock is defered, it
(randomly) assumes that the lock is not taken.
boost::unique_lock has the following definition:
unique_lock(Mutex& m_,defer_lock_t):
m(&m_),is_locked(false)
{}
bool owns_lock() const
{
return is_locked;
}
Thus it is a mistake to check owns_lock() in Enter
and TryEnter - they will always return false.
feature in clang. These macros should primarily be used to
document which locks protect a given piece of data. Secondary it
can be used to document the set of held and excluded locks when
entering a function.
Alex Morcos