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    //! A dynamically-sized view into a contiguous sequence, `[T]`.
    //!
    //! *[See also the slice primitive type](../../std/primitive.slice.html).*
    //!
    //! Slices are a view into a block of memory represented as a pointer and a
    //! length.
    //!
    //! ```
    //! // slicing a Vec
    //! let vec = vec![1, 2, 3];
    //! let int_slice = &vec[..];
    //! // coercing an array to a slice
    //! let str_slice: &[&str] = &["one", "two", "three"];
    //! ```
    //!
    //! Slices are either mutable or shared. The shared slice type is `&[T]`,
    //! while the mutable slice type is `&mut [T]`, where `T` represents the element
    //! type. For example, you can mutate the block of memory that a mutable slice
    //! points to:
    //!
    //! ```
    //! let x = &mut [1, 2, 3];
    //! x[1] = 7;
    //! assert_eq!(x, &[1, 7, 3]);
    //! ```
    //!
    //! Here are some of the things this module contains:
    //!
    //! ## Structs
    //!
    //! There are several structs that are useful for slices, such as [`Iter`], which
    //! represents iteration over a slice.
    //!
    //! ## Trait Implementations
    //!
    //! There are several implementations of common traits for slices. Some examples
    //! include:
    //!
    //! * [`Clone`]
    //! * [`Eq`], [`Ord`] - for slices whose element type are [`Eq`] or [`Ord`].
    //! * [`Hash`] - for slices whose element type is [`Hash`].
    //!
    //! ## Iteration
    //!
    //! The slices implement `IntoIterator`. The iterator yields references to the
    //! slice elements.
    //!
    //! ```
    //! let numbers = &[0, 1, 2];
    //! for n in numbers {
    //!     println!("{} is a number!", n);
    //! }
    //! ```
    //!
    //! The mutable slice yields mutable references to the elements:
    //!
    //! ```
    //! let mut scores = [7, 8, 9];
    //! for score in &mut scores[..] {
    //!     *score += 1;
    //! }
    //! ```
    //!
    //! This iterator yields mutable references to the slice's elements, so while
    //! the element type of the slice is `i32`, the element type of the iterator is
    //! `&mut i32`.
    //!
    //! * [`.iter`] and [`.iter_mut`] are the explicit methods to return the default
    //!   iterators.
    //! * Further methods that return iterators are [`.split`], [`.splitn`],
    //!   [`.chunks`], [`.windows`] and more.
    //!
    //! [`Clone`]: ../../std/clone/trait.Clone.html
    //! [`Eq`]: ../../std/cmp/trait.Eq.html
    //! [`Ord`]: ../../std/cmp/trait.Ord.html
    //! [`Iter`]: struct.Iter.html
    //! [`Hash`]: ../../std/hash/trait.Hash.html
    //! [`.iter`]: ../../std/primitive.slice.html#method.iter
    //! [`.iter_mut`]: ../../std/primitive.slice.html#method.iter_mut
    //! [`.split`]: ../../std/primitive.slice.html#method.split
    //! [`.splitn`]: ../../std/primitive.slice.html#method.splitn
    //! [`.chunks`]: ../../std/primitive.slice.html#method.chunks
    //! [`.windows`]: ../../std/primitive.slice.html#method.windows
    #![stable(feature = "rust1", since = "1.0.0")]

    // Many of the usings in this module are only used in the test configuration.
    // It's cleaner to just turn off the unused_imports warning than to fix them.
    #![cfg_attr(test, allow(unused_imports, dead_code))]

    use core::cmp::Ordering::{self, Less};
    use core::mem::size_of;
    use core::mem;
    use core::ptr;
    use core::{u8, u16, u32};

    use borrow::{Borrow, BorrowMut, ToOwned};
    use boxed::Box;
    use vec::Vec;

    #[stable(feature = "rust1", since = "1.0.0")]
    pub use core::slice::{Chunks, Windows};
    #[stable(feature = "rust1", since = "1.0.0")]
    pub use core::slice::{Iter, IterMut};
    #[stable(feature = "rust1", since = "1.0.0")]
    pub use core::slice::{SplitMut, ChunksMut, Split};
    #[stable(feature = "rust1", since = "1.0.0")]
    pub use core::slice::{SplitN, RSplitN, SplitNMut, RSplitNMut};
    #[stable(feature = "slice_rsplit", since = "1.27.0")]
    pub use core::slice::{RSplit, RSplitMut};
    #[stable(feature = "rust1", since = "1.0.0")]
    pub use core::slice::{from_raw_parts, from_raw_parts_mut};
    #[stable(feature = "from_ref", since = "1.28.0")]
    pub use core::slice::{from_ref, from_mut};
    #[stable(feature = "slice_get_slice", since = "1.28.0")]
    pub use core::slice::SliceIndex;
    #[stable(feature = "chunks_exact", since = "1.31.0")]
    pub use core::slice::{ChunksExact, ChunksExactMut};
    #[stable(feature = "rchunks", since = "1.31.0")]
    pub use core::slice::{RChunks, RChunksMut, RChunksExact, RChunksExactMut};

    ////////////////////////////////////////////////////////////////////////////////
    // Basic slice extension methods
    ////////////////////////////////////////////////////////////////////////////////

    // HACK(japaric) needed for the implementation of `vec!` macro during testing
    // NB see the hack module in this file for more details
    #[cfg(test)]
    pub use self::hack::into_vec;

    // HACK(japaric) needed for the implementation of `Vec::clone` during testing
    // NB see the hack module in this file for more details
    #[cfg(test)]
    pub use self::hack::to_vec;

    // HACK(japaric): With cfg(test) `impl [T]` is not available, these three
    // functions are actually methods that are in `impl [T]` but not in
    // `core::slice::SliceExt` - we need to supply these functions for the
    // `test_permutations` test
    mod hack {
        use boxed::Box;
        use core::mem;

        #[cfg(test)]
        use string::ToString;
        use vec::Vec;

        pub fn into_vec<T>(mut b: Box<[T]>) -> Vec<T> {
            unsafe {
                let xs = Vec::from_raw_parts(b.as_mut_ptr(), b.len(), b.len());
                mem::forget(b);
                xs
            }
        }

        #[inline]
        pub fn to_vec<T>(s: &[T]) -> Vec<T>
            where T: Clone
        {
            let mut vector = Vec::with_capacity(s.len());
            vector.extend_from_slice(s);
            vector
        }
    }

    #[lang = "slice_alloc"]
    #[cfg(not(test))]
    impl<T> [T] {
        /// Sorts the slice.
        ///
        /// This sort is stable (i.e., does not reorder equal elements) and `O(n log n)` worst-case.
        ///
        /// When applicable, unstable sorting is preferred because it is generally faster than stable
        /// sorting and it doesn't allocate auxiliary memory.
        /// See [`sort_unstable`](#method.sort_unstable).
        ///
        /// # Current implementation
        ///
        /// The current algorithm is an adaptive, iterative merge sort inspired by
        /// [timsort](https://en.wikipedia.org/wiki/Timsort).
        /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
        /// two or more sorted sequences concatenated one after another.
        ///
        /// Also, it allocates temporary storage half the size of `self`, but for short slices a
        /// non-allocating insertion sort is used instead.
        ///
        /// # Examples
        ///
        /// ```
        /// let mut v = [-5, 4, 1, -3, 2];
        ///
        /// v.sort();
        /// assert!(v == [-5, -3, 1, 2, 4]);
        /// ```
        #[stable(feature = "rust1", since = "1.0.0")]
        #[inline]
        pub fn sort(&mut self)
            where T: Ord
        {
            merge_sort(self, |a, b| a.lt(b));
        }

        /// Sorts the slice with a comparator function.
        ///
        /// This sort is stable (i.e., does not reorder equal elements) and `O(n log n)` worst-case.
        ///
        /// The comparator function must define a total ordering for the elements in the slice. If
        /// the ordering is not total, the order of the elements is unspecified. An order is a
        /// total order if it is (for all a, b and c):
        ///
        /// * total and antisymmetric: exactly one of a < b, a == b or a > b is true; and
        /// * transitive, a < b and b < c implies a < c. The same must hold for both == and >.
        ///
        /// For example, while [`f64`] doesn't implement [`Ord`] because `NaN != NaN`, we can use
        /// `partial_cmp` as our sort function when we know the slice doesn't contain a `NaN`.
        ///
        /// ```
        /// let mut floats = [5f64, 4.0, 1.0, 3.0, 2.0];
        /// floats.sort_by(|a, b| a.partial_cmp(b).unwrap());
        /// assert_eq!(floats, [1.0, 2.0, 3.0, 4.0, 5.0]);
        /// ```
        ///
        /// When applicable, unstable sorting is preferred because it is generally faster than stable
        /// sorting and it doesn't allocate auxiliary memory.
        /// See [`sort_unstable_by`](#method.sort_unstable_by).
        ///
        /// # Current implementation
        ///
        /// The current algorithm is an adaptive, iterative merge sort inspired by
        /// [timsort](https://en.wikipedia.org/wiki/Timsort).
        /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
        /// two or more sorted sequences concatenated one after another.
        ///
        /// Also, it allocates temporary storage half the size of `self`, but for short slices a
        /// non-allocating insertion sort is used instead.
        ///
        /// # Examples
        ///
        /// ```
        /// let mut v = [5, 4, 1, 3, 2];
        /// v.sort_by(|a, b| a.cmp(b));
        /// assert!(v == [1, 2, 3, 4, 5]);
        ///
        /// // reverse sorting
        /// v.sort_by(|a, b| b.cmp(a));
        /// assert!(v == [5, 4, 3, 2, 1]);
        /// ```
        #[stable(feature = "rust1", since = "1.0.0")]
        #[inline]
        pub fn sort_by<F>(&mut self, mut compare: F)
            where F: FnMut(&T, &T) -> Ordering
        {
            merge_sort(self, |a, b| compare(a, b) == Less);
        }

        /// Sorts the slice with a key extraction function.
        ///
        /// This sort is stable (i.e., does not reorder equal elements) and `O(m n log(m n))`
        /// worst-case, where the key function is `O(m)`.
        ///
        /// When applicable, unstable sorting is preferred because it is generally faster than stable
        /// sorting and it doesn't allocate auxiliary memory.
        /// See [`sort_unstable_by_key`](#method.sort_unstable_by_key).
        ///
        /// # Current implementation
        ///
        /// The current algorithm is an adaptive, iterative merge sort inspired by
        /// [timsort](https://en.wikipedia.org/wiki/Timsort).
        /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
        /// two or more sorted sequences concatenated one after another.
        ///
        /// Also, it allocates temporary storage half the size of `self`, but for short slices a
        /// non-allocating insertion sort is used instead.
        ///
        /// # Examples
        ///
        /// ```
        /// let mut v = [-5i32, 4, 1, -3, 2];
        ///
        /// v.sort_by_key(|k| k.abs());
        /// assert!(v == [1, 2, -3, 4, -5]);
        /// ```
        #[stable(feature = "slice_sort_by_key", since = "1.7.0")]
        #[inline]
        pub fn sort_by_key<K, F>(&mut self, mut f: F)
            where F: FnMut(&T) -> K, K: Ord
        {
            merge_sort(self, |a, b| f(a).lt(&f(b)));
        }

        /// Sorts the slice with a key extraction function.
        ///
        /// During sorting, the key function is called only once per element.
        ///
        /// This sort is stable (i.e., does not reorder equal elements) and `O(m n + n log n)`
        /// worst-case, where the key function is `O(m)`.
        ///
        /// For simple key functions (e.g., functions that are property accesses or
        /// basic operations), [`sort_by_key`](#method.sort_by_key) is likely to be
        /// faster.
        ///
        /// # Current implementation
        ///
        /// The current algorithm is based on [pattern-defeating quicksort][pdqsort] by Orson Peters,
        /// which combines the fast average case of randomized quicksort with the fast worst case of
        /// heapsort, while achieving linear time on slices with certain patterns. It uses some
        /// randomization to avoid degenerate cases, but with a fixed seed to always provide
        /// deterministic behavior.
        ///
        /// In the worst case, the algorithm allocates temporary storage in a `Vec<(K, usize)>` the
        /// length of the slice.
        ///
        /// # Examples
        ///
        /// ```
        /// #![feature(slice_sort_by_cached_key)]
        /// let mut v = [-5i32, 4, 32, -3, 2];
        ///
        /// v.sort_by_cached_key(|k| k.to_string());
        /// assert!(v == [-3, -5, 2, 32, 4]);
        /// ```
        ///
        /// [pdqsort]: https://github.com/orlp/pdqsort
        #[unstable(feature = "slice_sort_by_cached_key", issue = "34447")]
        #[inline]
        pub fn sort_by_cached_key<K, F>(&mut self, f: F)
            where F: FnMut(&T) -> K, K: Ord
        {
            // Helper macro for indexing our vector by the smallest possible type, to reduce allocation.
            macro_rules! sort_by_key {
                ($t:ty, $slice:ident, $f:ident) => ({
                    let mut indices: Vec<_> =
                        $slice.iter().map($f).enumerate().map(|(i, k)| (k, i as $t)).collect();
                    // The elements of `indices` are unique, as they are indexed, so any sort will be
                    // stable with respect to the original slice. We use `sort_unstable` here because
                    // it requires less memory allocation.
                    indices.sort_unstable();
                    for i in 0..$slice.len() {
                        let mut index = indices[i].1;
                        while (index as usize) < i {
                            index = indices[index as usize].1;
                        }
                        indices[i].1 = index;
                        $slice.swap(i, index as usize);
                    }
                })
            }

            let sz_u8    = mem::size_of::<(K, u8)>();
            let sz_u16   = mem::size_of::<(K, u16)>();
            let sz_u32   = mem::size_of::<(K, u32)>();
            let sz_usize = mem::size_of::<(K, usize)>();

            let len = self.len();
            if len < 2 { return }
            if sz_u8  < sz_u16   && len <= ( u8::MAX as usize) { return sort_by_key!( u8, self, f) }
            if sz_u16 < sz_u32   && len <= (u16::MAX as usize) { return sort_by_key!(u16, self, f) }
            if sz_u32 < sz_usize && len <= (u32::MAX as usize) { return sort_by_key!(u32, self, f) }
            sort_by_key!(usize, self, f)
        }

        /// Copies `self` into a new `Vec`.
        ///
        /// # Examples
        ///
        /// ```
        /// let s = [10, 40, 30];
        /// let x = s.to_vec();
        /// // Here, `s` and `x` can be modified independently.
        /// ```
        #[rustc_conversion_suggestion]
        #[stable(feature = "rust1", since = "1.0.0")]
        #[inline]
        pub fn to_vec(&self) -> Vec<T>
            where T: Clone
        {
            // NB see hack module in this file
            hack::to_vec(self)
        }

        /// Converts `self` into a vector without clones or allocation.
        ///
        /// The resulting vector can be converted back into a box via
        /// `Vec<T>`'s `into_boxed_slice` method.
        ///
        /// # Examples
        ///
        /// ```
        /// let s: Box<[i32]> = Box::new([10, 40, 30]);
        /// let x = s.into_vec();
        /// // `s` cannot be used anymore because it has been converted into `x`.
        ///
        /// assert_eq!(x, vec![10, 40, 30]);
        /// ```
        #[stable(feature = "rust1", since = "1.0.0")]
        #[inline]
        pub fn into_vec(self: Box<Self>) -> Vec<T> {
            // NB see hack module in this file
            hack::into_vec(self)
        }

        /// Creates a vector by repeating a slice `n` times.
        ///
        /// # Panics
        ///
        /// This function will panic if the capacity would overflow.
        ///
        /// # Examples
        ///
        /// Basic usage:
        ///
        /// ```
        /// #![feature(repeat_generic_slice)]
        ///
        /// fn main() {
        ///     assert_eq!([1, 2].repeat(3), vec![1, 2, 1, 2, 1, 2]);
        /// }
        /// ```
        ///
        /// A panic upon overflow:
        ///
        /// ```should_panic
        /// #![feature(repeat_generic_slice)]
        /// fn main() {
        ///     // this will panic at runtime
        ///     b"0123456789abcdef".repeat(usize::max_value());
        /// }
        /// ```
        #[unstable(feature = "repeat_generic_slice",
                   reason = "it's on str, why not on slice?",
                   issue = "48784")]
        pub fn repeat(&self, n: usize) -> Vec<T> where T: Copy {
            if n == 0 {
                return Vec::new();
            }

            // If `n` is larger than zero, it can be split as
            // `n = 2^expn + rem (2^expn > rem, expn >= 0, rem >= 0)`.
            // `2^expn` is the number represented by the leftmost '1' bit of `n`,
            // and `rem` is the remaining part of `n`.

            // Using `Vec` to access `set_len()`.
            let mut buf = Vec::with_capacity(self.len().checked_mul(n).expect("capacity overflow"));

            // `2^expn` repetition is done by doubling `buf` `expn`-times.
            buf.extend(self);
            {
                let mut m = n >> 1;
                // If `m > 0`, there are remaining bits up to the leftmost '1'.
                while m > 0 {
                    // `buf.extend(buf)`:
                    unsafe {
                        ptr::copy_nonoverlapping(
                            buf.as_ptr(),
                            (buf.as_mut_ptr() as *mut T).add(buf.len()),
                            buf.len(),
                        );
                        // `buf` has capacity of `self.len() * n`.
                        let buf_len = buf.len();
                        buf.set_len(buf_len * 2);
                    }

                    m >>= 1;
                }
            }

            // `rem` (`= n - 2^expn`) repetition is done by copying
            // first `rem` repetitions from `buf` itself.
            let rem_len = self.len() * n - buf.len(); // `self.len() * rem`
            if rem_len > 0 {
                // `buf.extend(buf[0 .. rem_len])`:
                unsafe {
                    // This is non-overlapping since `2^expn > rem`.
                    ptr::copy_nonoverlapping(
                        buf.as_ptr(),
                        (buf.as_mut_ptr() as *mut T).add(buf.len()),
                        rem_len,
                    );
                    // `buf.len() + rem_len` equals to `buf.capacity()` (`= self.len() * n`).
                    let buf_cap = buf.capacity();
                    buf.set_len(buf_cap);
                }
            }
            buf
        }
    }

    #[lang = "slice_u8_alloc"]
    #[cfg(not(test))]
    impl [u8] {
        /// Returns a vector containing a copy of this slice where each byte
        /// is mapped to its ASCII upper case equivalent.
        ///
        /// ASCII letters 'a' to 'z' are mapped to 'A' to 'Z',
        /// but non-ASCII letters are unchanged.
        ///
        /// To uppercase the value in-place, use [`make_ascii_uppercase`].
        ///
        /// [`make_ascii_uppercase`]: #method.make_ascii_uppercase
        #[stable(feature = "ascii_methods_on_intrinsics", since = "1.23.0")]
        #[inline]
        pub fn to_ascii_uppercase(&self) -> Vec<u8> {
            let mut me = self.to_vec();
            me.make_ascii_uppercase();
            me
        }

        /// Returns a vector containing a copy of this slice where each byte
        /// is mapped to its ASCII lower case equivalent.
        ///
        /// ASCII letters 'A' to 'Z' are mapped to 'a' to 'z',
        /// but non-ASCII letters are unchanged.
        ///
        /// To lowercase the value in-place, use [`make_ascii_lowercase`].
        ///
        /// [`make_ascii_lowercase`]: #method.make_ascii_lowercase
        #[stable(feature = "ascii_methods_on_intrinsics", since = "1.23.0")]
        #[inline]
        pub fn to_ascii_lowercase(&self) -> Vec<u8> {
            let mut me = self.to_vec();
            me.make_ascii_lowercase();
            me
        }
    }

    ////////////////////////////////////////////////////////////////////////////////
    // Extension traits for slices over specific kinds of data
    ////////////////////////////////////////////////////////////////////////////////
    #[unstable(feature = "slice_concat_ext",
               reason = "trait should not have to exist",
               issue = "27747")]
    /// An extension trait for concatenating slices
    ///
    /// While this trait is unstable, the methods are stable. `SliceConcatExt` is
    /// included in the [standard library prelude], so you can use [`join()`] and
    /// [`concat()`] as if they existed on `[T]` itself.
    ///
    /// [standard library prelude]: ../../std/prelude/index.html
    /// [`join()`]: #tymethod.join
    /// [`concat()`]: #tymethod.concat
    pub trait SliceConcatExt<T: ?Sized> {
        #[unstable(feature = "slice_concat_ext",
                   reason = "trait should not have to exist",
                   issue = "27747")]
        /// The resulting type after concatenation
        type Output;

        /// Flattens a slice of `T` into a single value `Self::Output`.
        ///
        /// # Examples
        ///
        /// ```
        /// assert_eq!(["hello", "world"].concat(), "helloworld");
        /// assert_eq!([[1, 2], [3, 4]].concat(), [1, 2, 3, 4]);
        /// ```
        #[stable(feature = "rust1", since = "1.0.0")]
        fn concat(&self) -> Self::Output;

        /// Flattens a slice of `T` into a single value `Self::Output`, placing a
        /// given separator between each.
        ///
        /// # Examples
        ///
        /// ```
        /// assert_eq!(["hello", "world"].join(" "), "hello world");
        /// assert_eq!([[1, 2], [3, 4]].join(&0), [1, 2, 0, 3, 4]);
        /// ```
        #[stable(feature = "rename_connect_to_join", since = "1.3.0")]
        fn join(&self, sep: &T) -> Self::Output;

        #[stable(feature = "rust1", since = "1.0.0")]
        #[rustc_deprecated(since = "1.3.0", reason = "renamed to join")]
        fn connect(&self, sep: &T) -> Self::Output;
    }

    #[unstable(feature = "slice_concat_ext",
               reason = "trait should not have to exist",
               issue = "27747")]
    impl<T: Clone, V: Borrow<[T]>> SliceConcatExt<T> for [V] {
        type Output = Vec<T>;

        fn concat(&self) -> Vec<T> {
            let size = self.iter().map(|slice| slice.borrow().len()).sum();
            let mut result = Vec::with_capacity(size);
            for v in self {
                result.extend_from_slice(v.borrow())
            }
            result
        }

        fn join(&self, sep: &T) -> Vec<T> {
            let mut iter = self.iter();
            let first = match iter.next() {
                Some(first) => first,
                None => return vec![],
            };
            let size = self.iter().map(|slice| slice.borrow().len()).sum::<usize>() + self.len() - 1;
            let mut result = Vec::with_capacity(size);
            result.extend_from_slice(first.borrow());

            for v in iter {
                result.push(sep.clone());
                result.extend_from_slice(v.borrow())
            }
            result
        }

        fn connect(&self, sep: &T) -> Vec<T> {
            self.join(sep)
        }
    }

    ////////////////////////////////////////////////////////////////////////////////
    // Standard trait implementations for slices
    ////////////////////////////////////////////////////////////////////////////////

    #[stable(feature = "rust1", since = "1.0.0")]
    impl<T> Borrow<[T]> for Vec<T> {
        fn borrow(&self) -> &[T] {
            &self[..]
        }
    }

    #[stable(feature = "rust1", since = "1.0.0")]
    impl<T> BorrowMut<[T]> for Vec<T> {
        fn borrow_mut(&mut self) -> &mut [T] {
            &mut self[..]
        }
    }

    #[stable(feature = "rust1", since = "1.0.0")]
    impl<T: Clone> ToOwned for [T] {
        type Owned = Vec<T>;
        #[cfg(not(test))]
        fn to_owned(&self) -> Vec<T> {
            self.to_vec()
        }

        #[cfg(test)]
        fn to_owned(&self) -> Vec<T> {
            hack::to_vec(self)
        }

        fn clone_into(&self, target: &mut Vec<T>) {
            // drop anything in target that will not be overwritten
            target.truncate(self.len());
            let len = target.len();

            // reuse the contained values' allocations/resources.
            target.clone_from_slice(&self[..len]);

            // target.len <= self.len due to the truncate above, so the
            // slice here is always in-bounds.
            target.extend_from_slice(&self[len..]);
        }
    }

    ////////////////////////////////////////////////////////////////////////////////
    // Sorting
    ////////////////////////////////////////////////////////////////////////////////

    /// Inserts `v[0]` into pre-sorted sequence `v[1..]` so that whole `v[..]` becomes sorted.
    ///
    /// This is the integral subroutine of insertion sort.
    fn insert_head<T, F>(v: &mut [T], is_less: &mut F)
        where F: FnMut(&T, &T) -> bool
    {
        if v.len() >= 2 && is_less(&v[1], &v[0]) {
            unsafe {
                // There are three ways to implement insertion here:
                //
                // 1. Swap adjacent elements until the first one gets to its final destination.
                //    However, this way we copy data around more than is necessary. If elements are big
                //    structures (costly to copy), this method will be slow.
                //
                // 2. Iterate until the right place for the first element is found. Then shift the
                //    elements succeeding it to make room for it and finally place it into the
                //    remaining hole. This is a good method.
                //
                // 3. Copy the first element into a temporary variable. Iterate until the right place
                //    for it is found. As we go along, copy every traversed element into the slot
                //    preceding it. Finally, copy data from the temporary variable into the remaining
                //    hole. This method is very good. Benchmarks demonstrated slightly better
                //    performance than with the 2nd method.
                //
                // All methods were benchmarked, and the 3rd showed best results. So we chose that one.
                let mut tmp = mem::ManuallyDrop::new(ptr::read(&v[0]));

                // Intermediate state of the insertion process is always tracked by `hole`, which
                // serves two purposes:
                // 1. Protects integrity of `v` from panics in `is_less`.
                // 2. Fills the remaining hole in `v` in the end.
                //
                // Panic safety:
                //
                // If `is_less` panics at any point during the process, `hole` will get dropped and
                // fill the hole in `v` with `tmp`, thus ensuring that `v` still holds every object it
                // initially held exactly once.
                let mut hole = InsertionHole {
                    src: &mut *tmp,
                    dest: &mut v[1],
                };
                ptr::copy_nonoverlapping(&v[1], &mut v[0], 1);

                for i in 2..v.len() {
                    if !is_less(&v[i], &*tmp) {
                        break;
                    }
                    ptr::copy_nonoverlapping(&v[i], &mut v[i - 1], 1);
                    hole.dest = &mut v[i];
                }
                // `hole` gets dropped and thus copies `tmp` into the remaining hole in `v`.
            }
        }

        // When dropped, copies from `src` into `dest`.
        struct InsertionHole<T> {
            src: *mut T,
            dest: *mut T,
        }

        impl<T> Drop for InsertionHole<T> {
            fn drop(&mut self) {
                unsafe { ptr::copy_nonoverlapping(self.src, self.dest, 1); }
            }
        }
    }

    /// Merges non-decreasing runs `v[..mid]` and `v[mid..]` using `buf` as temporary storage, and
    /// stores the result into `v[..]`.
    ///
    /// # Safety
    ///
    /// The two slices must be non-empty and `mid` must be in bounds. Buffer `buf` must be long enough
    /// to hold a copy of the shorter slice. Also, `T` must not be a zero-sized type.
    unsafe fn merge<T, F>(v: &mut [T], mid: usize, buf: *mut T, is_less: &mut F)
        where F: FnMut(&T, &T) -> bool
    {
        let len = v.len();
        let v = v.as_mut_ptr();
        let v_mid = v.add(mid);
        let v_end = v.add(len);

        // The merge process first copies the shorter run into `buf`. Then it traces the newly copied
        // run and the longer run forwards (or backwards), comparing their next unconsumed elements and
        // copying the lesser (or greater) one into `v`.
        //
        // As soon as the shorter run is fully consumed, the process is done. If the longer run gets
        // consumed first, then we must copy whatever is left of the shorter run into the remaining
        // hole in `v`.
        //
        // Intermediate state of the process is always tracked by `hole`, which serves two purposes:
        // 1. Protects integrity of `v` from panics in `is_less`.
        // 2. Fills the remaining hole in `v` if the longer run gets consumed first.
        //
        // Panic safety:
        //
        // If `is_less` panics at any point during the process, `hole` will get dropped and fill the
        // hole in `v` with the unconsumed range in `buf`, thus ensuring that `v` still holds every
        // object it initially held exactly once.
        let mut hole;

        if mid <= len - mid {
            // The left run is shorter.
            ptr::copy_nonoverlapping(v, buf, mid);
            hole = MergeHole {
                start: buf,
                end: buf.add(mid),
                dest: v,
            };

            // Initially, these pointers point to the beginnings of their arrays.
            let left = &mut hole.start;
            let mut right = v_mid;
            let out = &mut hole.dest;

            while *left < hole.end && right < v_end {
                // Consume the lesser side.
                // If equal, prefer the left run to maintain stability.
                let to_copy = if is_less(&*right, &**left) {
                    get_and_increment(&mut right)
                } else {
                    get_and_increment(left)
                };
                ptr::copy_nonoverlapping(to_copy, get_and_increment(out), 1);
            }
        } else {
            // The right run is shorter.
            ptr::copy_nonoverlapping(v_mid, buf, len - mid);
            hole = MergeHole {
                start: buf,
                end: buf.add(len - mid),
                dest: v_mid,
            };

            // Initially, these pointers point past the ends of their arrays.
            let left = &mut hole.dest;
            let right = &mut hole.end;
            let mut out = v_end;

            while v < *left && buf < *right {
                // Consume the greater side.
                // If equal, prefer the right run to maintain stability.
                let to_copy = if is_less(&*right.offset(-1), &*left.offset(-1)) {
                    decrement_and_get(left)
                } else {
                    decrement_and_get(right)
                };
                ptr::copy_nonoverlapping(to_copy, decrement_and_get(&mut out), 1);
            }
        }
        // Finally, `hole` gets dropped. If the shorter run was not fully consumed, whatever remains of
        // it will now be copied into the hole in `v`.

        unsafe fn get_and_increment<T>(ptr: &mut *mut T) -> *mut T {
            let old = *ptr;
            *ptr = ptr.offset(1);
            old
        }

        unsafe fn decrement_and_get<T>(ptr: &mut *mut T) -> *mut T {
            *ptr = ptr.offset(-1);
            *ptr
        }

        // When dropped, copies the range `start..end` into `dest..`.
        struct MergeHole<T> {
            start: *mut T,
            end: *mut T,
            dest: *mut T,
        }

        impl<T> Drop for MergeHole<T> {
            fn drop(&mut self) {
                // `T` is not a zero-sized type, so it's okay to divide by its size.
                let len = (self.end as usize - self.start as usize) / mem::size_of::<T>();
                unsafe { ptr::copy_nonoverlapping(self.start, self.dest, len); }
            }
        }
    }

    /// This merge sort borrows some (but not all) ideas from TimSort, which is described in detail
    /// [here](http://svn.python.org/projects/python/trunk/Objects/listsort.txt).
    ///
    /// The algorithm identifies strictly descending and non-descending subsequences, which are called
    /// natural runs. There is a stack of pending runs yet to be merged. Each newly found run is pushed
    /// onto the stack, and then some pairs of adjacent runs are merged until these two invariants are
    /// satisfied:
    ///
    /// 1. for every `i` in `1..runs.len()`: `runs[i - 1].len > runs[i].len`
    /// 2. for every `i` in `2..runs.len()`: `runs[i - 2].len > runs[i - 1].len + runs[i].len`
    ///
    /// The invariants ensure that the total running time is `O(n log n)` worst-case.
    fn merge_sort<T, F>(v: &mut [T], mut is_less: F)
        where F: FnMut(&T, &T) -> bool
    {
        // Slices of up to this length get sorted using insertion sort.
        const MAX_INSERTION: usize = 20;
        // Very short runs are extended using insertion sort to span at least this many elements.
        const MIN_RUN: usize = 10;

        // Sorting has no meaningful behavior on zero-sized types.
        if size_of::<T>() == 0 {
            return;
        }

        let len = v.len();

        // Short arrays get sorted in-place via insertion sort to avoid allocations.
        if len <= MAX_INSERTION {
            if len >= 2 {
                for i in (0..len-1).rev() {
                    insert_head(&mut v[i..], &mut is_less);
                }
            }
            return;
        }

        // Allocate a buffer to use as scratch memory. We keep the length 0 so we can keep in it
        // shallow copies of the contents of `v` without risking the dtors running on copies if
        // `is_less` panics. When merging two sorted runs, this buffer holds a copy of the shorter run,
        // which will always have length at most `len / 2`.
        let mut buf = Vec::with_capacity(len / 2);

        // In order to identify natural runs in `v`, we traverse it backwards. That might seem like a
        // strange decision, but consider the fact that merges more often go in the opposite direction
        // (forwards). According to benchmarks, merging forwards is slightly faster than merging
        // backwards. To conclude, identifying runs by traversing backwards improves performance.
        let mut runs = vec![];
        let mut end = len;
        while end > 0 {
            // Find the next natural run, and reverse it if it's strictly descending.
            let mut start = end - 1;
            if start > 0 {
                start -= 1;
                unsafe {
                    if is_less(v.get_unchecked(start + 1), v.get_unchecked(start)) {
                        while start > 0 && is_less(v.get_unchecked(start),
                                                   v.get_unchecked(start - 1)) {
                            start -= 1;
                        }
                        v[start..end].reverse();
                    } else {
                        while start > 0 && !is_less(v.get_unchecked(start),
                                                    v.get_unchecked(start - 1)) {
                            start -= 1;
                        }
                    }
                }
            }

            // Insert some more elements into the run if it's too short. Insertion sort is faster than
            // merge sort on short sequences, so this significantly improves performance.
            while start > 0 && end - start < MIN_RUN {
                start -= 1;
                insert_head(&mut v[start..end], &mut is_less);
            }

            // Push this run onto the stack.
            runs.push(Run {
                start,
                len: end - start,
            });
            end = start;

            // Merge some pairs of adjacent runs to satisfy the invariants.
            while let Some(r) = collapse(&runs) {
                let left = runs[r + 1];
                let right = runs[r];
                unsafe {
                    merge(&mut v[left.start .. right.start + right.len], left.len, buf.as_mut_ptr(),
                          &mut is_less);
                }
                runs[r] = Run {
                    start: left.start,
                    len: left.len + right.len,
                };
                runs.remove(r + 1);
            }
        }

        // Finally, exactly one run must remain in the stack.
        debug_assert!(runs.len() == 1 && runs[0].start == 0 && runs[0].len == len);

        // Examines the stack of runs and identifies the next pair of runs to merge. More specifically,
        // if `Some(r)` is returned, that means `runs[r]` and `runs[r + 1]` must be merged next. If the
        // algorithm should continue building a new run instead, `None` is returned.
        //
        // TimSort is infamous for its buggy implementations, as described here:
        // http://envisage-project.eu/timsort-specification-and-verification/
        //
        // The gist of the story is: we must enforce the invariants on the top four runs on the stack.
        // Enforcing them on just top three is not sufficient to ensure that the invariants will still
        // hold for *all* runs in the stack.
        //
        // This function correctly checks invariants for the top four runs. Additionally, if the top
        // run starts at index 0, it will always demand a merge operation until the stack is fully
        // collapsed, in order to complete the sort.
        #[inline]
        fn collapse(runs: &[Run]) -> Option<usize> {
            let n = runs.len();
            if n >= 2 && (runs[n - 1].start == 0 ||
                          runs[n - 2].len <= runs[n - 1].len ||
                          (n >= 3 && runs[n - 3].len <= runs[n - 2].len + runs[n - 1].len) ||
                          (n >= 4 && runs[n - 4].len <= runs[n - 3].len + runs[n - 2].len)) {
                if n >= 3 && runs[n - 3].len < runs[n - 1].len {
                    Some(n - 3)
                } else {
                    Some(n - 2)
                }
            } else {
                None
            }
        }

        #[derive(Clone, Copy)]
        struct Run {
            start: usize,
            len: usize,
        }
    }

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