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
Immature coinbase spends are allowed in the memory pool if they can be mined in the next block.
They are not allowed in the memory pool if they cannot be mined in the next block.
This regression test tests those edge cases.
The regtest framework is local, so often there is no need to
discover our external IP. Setting -discover=0 in util.py works
around shutdown hang caused by GetExternalIP waiting in recv().
This avoids a race condition in which the connection was
made but the version handshake is not completed yet. In that
case transactions won't be broadcasted to a peer yet, and
the nodes will wait forever for their mempools to sync.
New RPC methods: return an estimate of the fee (or priority) a
transaction needs to be likely to confirm in a given number of
blocks.
Mike Hearn created the first version of this method for estimating fees.
It works as follows:
For transactions that took 1 to N (I picked N=25) blocks to confirm,
keep N buckets with at most 100 entries in each recording the
fees-per-kilobyte paid by those transactions.
(separate buckets are kept for transactions that confirmed because
they are high-priority)
The buckets are filled as blocks are found, and are saved/restored
in a new fee_estiamtes.dat file in the data directory.
A few variations on Mike's initial scheme:
To estimate the fee needed for a transaction to confirm in X buckets,
all of the samples in all of the buckets are used and a median of
all of the data is used to make the estimate. For example, imagine
25 buckets each containing the full 100 entries. Those 2,500 samples
are sorted, and the estimate of the fee needed to confirm in the very
next block is the 50'th-highest-fee-entry in that sorted list; the
estimate of the fee needed to confirm in the next two blocks is the
150'th-highest-fee-entry, etc.
That algorithm has the nice property that estimates of how much fee
you need to pay to get confirmed in block N will always be greater
than or equal to the estimate for block N+1. It would clearly be wrong
to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay
12 uBTC and it will take LONGER".
A single block will not contribute more than 10 entries to any one
bucket, so a single miner and a large block cannot overwhelm
the estimates.
Taught bitcoind to close the HTTP connection after it gets a 'stop' command,
to make it easier for the regression tests to cleanly stop.
Move bitcoinrpc files to correct location.
Tidied up the python-based regression tests.
- Add license headers to source files (years based on commit dates)
in `src/test` as well as `qa`
- Add `README.md` to `src/test/data` specifying MIT license
Fixes#3848
