Cases like `Either<@int,()>` have a null case with at most one value but
a nonzero number of fields; if we misreport this, then bad things can
happen inside of, for example, pattern matching.
Closes#6117.
The test is reduced from a doc test, but making it separate ensures that
(1) unrelated changes to the docs won't leave this case uncovered, and
(2) the nature of any future failures will be more obvious to whoever
sees the tree on fire as a result.
Cases like `Either<@int,()>` have a null case with at most one value but
a nonzero number of fields; if we misreport this, then bad things can
happen inside of, for example, pattern matching.
Closes#6117.
First, it refers to a feature (trait bounds on type parameters) that's
apparently no longer in the language. Second, if I understand the issue
correctly, it should never have been a "run-pass" test because it was
supposed to fail.
`std::bigint` contains the following code.
```rust
borrow = *elem << (uint::bits - n_bits);
```
The code above contains a bug that the value of the right operand of the shift operator exceeds the size of the left operand,
because sizeof(*elem) == 32, and 0 <= n_bits < 32 in 64bit architecture.
If `--opt-level` option is not given to rustc, the code above runs as if the right operand is `(uint::bits - n_bits) % 32`,
but if --opt-level is given, `borrow` is always zero.
I wonder why this bug is not catched in the libstd's testsuite (I try the `rustc --test --opt-level=2 bigint.rs` before fixing the bug,
but the unittest passes normally.)
This pull request also removes the implicit vector copies in `bigint.rs`.
This replaces the wrapper around the runtime RNG with a pure Rust implementation of the same algorithm. This is much faster (up to 5x), and is hopefully safer.
There is still (a little) room for optimisation: testing by summing 100,000,000 random `u32`s indicates this is about ~~40-50%~~ 10% slower than the pure C implementation (running as standalone executable, not in the runtime).
(Only 6d50d55 is part of this PR, the first two are from #6058, but are required for the rt rng to be correct to compare against in the tests.)
This replaces the wrapper around the runtime RNG with a pure Rust
implementation of the same algorithm. This is faster (up to 5x), and
is hopefully safer.
There is still much room for optimisation: testing by summing 100,000,000
random `u32`s indicates this is about 40-50% slower than the pure C
implementation (running as standalone executable, not in the runtime).
