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shakmaty = "0.20.1"Please, use mobile in landscape.
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Previous review still applies for this new release.
Previous review still applies for this new release.
Implements chess and chess variant rules and operations.
This is a self-assessment. I am the author of this crate.
Soundness: I am highly confident in soundness. Unfortunately, I could not
avoid two kinds of unsafe blocks, without major performance impact.
Instead, all preconditions are explained thoroughly in comments and asserted
with debug assertions.
(1) The optimizer does not reliably elide bounds checks based on the
assumption that u64::trailing_zeros() will never be larger than 63.
This is important in many hot loops.
(2) The perfect hash function for attack lookups always stays within bounds.
This technique is called Magic Bitboards, widely used and very well
understood in the chess community. When selecting magic factors, exactly this
assumption is tested for all possible inputs.
Correctness: For move generation in standard chess, confidence is based on a
large test suite of randomly generated, as well as historical and tricky
positions, so called perft tests. The numbers are shared in the chess
community and compared across a wide array of implementations.
I am gradually less confident in other features, especially chess variants,
simply because they are less popular and played less often.
The library has been used to parse 1 billion recorded real world games
(https://database.lichess.org). Some bugs have been found, but in the source
of the data, not this library.
For handling of input formats (FEN, SAN, UCI) I reviewed the code thoroughly
and used fuzz testing to ensure absence of DOS/panics.
© bestia.dev 2023, MIT License, Version: 2023.608.1636
Open source repository for this web app: https://github.com/bestia-dev/cargo_crev_web/
This is a self-assessment. I am the author of this crate.
Soundness: I am highly confident in soundness. Unfortunately, I could not
avoid two kinds of unsafe blocks, without major performance impact.
Instead, all preconditions are explained thoroughly in comments and asserted
with debug assertions.
(1) The optimizer does not reliably elide bounds checks based on the
assumption that u64::trailing_zeros() will never be larger than 63.
This is important in many hot loops.
(2) The perfect hash function for attack lookups always stays within bounds.
This technique is called Magic Bitboards, widely used and very well
understood in the chess community. When selecting magic factors, exactly this
assumption is tested for all possible inputs.
Correctness: For move generation in standard chess, confidence is based
on a large test suite of randomly generated, as well as historical and tricky
positions, so called perft tests. The numbers are shared in the chess
community and compared across a wide array of implementations.
I am gradually less confident in other features, especially chess variants,
simply because they are less popular and played less often, and Zobrist
hashing, a recent feature addition.
The library has been used to parse 1 billion recorded real world games
(https://database.lichess.org). Some bugs have been found, but in the source
of the data, not this library.
For handling of input formats (FEN, SAN, UCI) I reviewed the code thoroughly
and used fuzz testing to ensure absence of DOS/panics.