Implement feature sort_unstable

src/libcollections/benches/lib.rs

@@ -11,6 +11,7 @@
 #![deny(warnings)]
 
 #![feature(rand)]
+#![feature(sort_unstable)]
 #![feature(test)]
 
 extern crate test;

src/libcollections/benches/slice.rs

@@ -169,6 +169,7 @@ fn random_inserts(b: &mut Bencher) {
         }
     })
 }
+
 #[bench]
 fn random_removes(b: &mut Bencher) {
     let mut rng = thread_rng();
@@ -216,65 +217,76 @@ fn gen_mostly_descending(len: usize) -> Vec<u64> {
     v
 }
 
+fn gen_strings(len: usize) -> Vec<String> {
+    let mut rng = thread_rng();
+    let mut v = vec![];
+    for _ in 0..len {
+        let n = rng.gen::<usize>() % 20 + 1;
+        v.push(rng.gen_ascii_chars().take(n).collect());
+    }
+    v
+}
+
 fn gen_big_random(len: usize) -> Vec<[u64; 16]> {
     let mut rng = thread_rng();
     rng.gen_iter().map(|x| [x; 16]).take(len).collect()
 }
 
-fn gen_big_ascending(len: usize) -> Vec<[u64; 16]> {
+macro_rules! sort {
-    (0..len as u64).map(|x| [x; 16]).take(len).collect()
+    ($f:ident, $name:ident, $gen:expr, $len:expr) => {
-}
-
-fn gen_big_descending(len: usize) -> Vec<[u64; 16]> {
-    (0..len as u64).rev().map(|x| [x; 16]).take(len).collect()
-}
-
-macro_rules! sort_bench {
-    ($name:ident, $gen:expr, $len:expr) => {
         #[bench]
         fn $name(b: &mut Bencher) {
-            b.iter(|| $gen($len).sort());
+            b.iter(|| $gen($len).$f());
             b.bytes = $len * mem::size_of_val(&$gen(1)[0]) as u64;
         }
     }
 }
 
-sort_bench!(sort_small_random, gen_random, 10);
+macro_rules! sort_expensive {
-sort_bench!(sort_small_ascending, gen_ascending, 10);
+    ($f:ident, $name:ident, $gen:expr, $len:expr) => {
-sort_bench!(sort_small_descending, gen_descending, 10);
+        #[bench]
+        fn $name(b: &mut Bencher) {
+            b.iter(|| {
+                let mut v = $gen($len);
+                let mut count = 0;
+                v.$f(|a: &u64, b: &u64| {
+                    count += 1;
+                    if count % 1_000_000_000 == 0 {
+                        panic!("should not happen");
+                    }
+                    (*a as f64).cos().partial_cmp(&(*b as f64).cos()).unwrap()
+                });
+                black_box(count);
+            });
+            b.bytes = $len as u64 * mem::size_of::<u64>() as u64;
+        }
+    }
+}
 
-sort_bench!(sort_small_big_random, gen_big_random, 10);
+sort!(sort, sort_small_ascending, gen_ascending, 10);
-sort_bench!(sort_small_big_ascending, gen_big_ascending, 10);
+sort!(sort, sort_small_descending, gen_descending, 10);
-sort_bench!(sort_small_big_descending, gen_big_descending, 10);
+sort!(sort, sort_small_random, gen_random, 10);
+sort!(sort, sort_small_big_random, gen_big_random, 10);
+sort!(sort, sort_medium_random, gen_random, 100);
+sort!(sort, sort_large_ascending, gen_ascending, 10000);
+sort!(sort, sort_large_descending, gen_descending, 10000);
+sort!(sort, sort_large_mostly_ascending, gen_mostly_ascending, 10000);
+sort!(sort, sort_large_mostly_descending, gen_mostly_descending, 10000);
+sort!(sort, sort_large_random, gen_random, 10000);
+sort!(sort, sort_large_big_random, gen_big_random, 10000);
+sort!(sort, sort_large_strings, gen_strings, 10000);
+sort_expensive!(sort_by, sort_large_random_expensive, gen_random, 10000);
 
-sort_bench!(sort_medium_random, gen_random, 100);
+sort!(sort_unstable, sort_unstable_small_ascending, gen_ascending, 10);
-sort_bench!(sort_medium_ascending, gen_ascending, 100);
+sort!(sort_unstable, sort_unstable_small_descending, gen_descending, 10);
-sort_bench!(sort_medium_descending, gen_descending, 100);
+sort!(sort_unstable, sort_unstable_small_random, gen_random, 10);
-
+sort!(sort_unstable, sort_unstable_small_big_random, gen_big_random, 10);
-sort_bench!(sort_large_random, gen_random, 10000);
+sort!(sort_unstable, sort_unstable_medium_random, gen_random, 100);
-sort_bench!(sort_large_ascending, gen_ascending, 10000);
+sort!(sort_unstable, sort_unstable_large_ascending, gen_ascending, 10000);
-sort_bench!(sort_large_descending, gen_descending, 10000);
+sort!(sort_unstable, sort_unstable_large_descending, gen_descending, 10000);
-sort_bench!(sort_large_mostly_ascending, gen_mostly_ascending, 10000);
+sort!(sort_unstable, sort_unstable_large_mostly_ascending, gen_mostly_ascending, 10000);
-sort_bench!(sort_large_mostly_descending, gen_mostly_descending, 10000);
+sort!(sort_unstable, sort_unstable_large_mostly_descending, gen_mostly_descending, 10000);
-
+sort!(sort_unstable, sort_unstable_large_random, gen_random, 10000);
-sort_bench!(sort_large_big_random, gen_big_random, 10000);
+sort!(sort_unstable, sort_unstable_large_big_random, gen_big_random, 10000);
-sort_bench!(sort_large_big_ascending, gen_big_ascending, 10000);
+sort!(sort_unstable, sort_unstable_large_strings, gen_strings, 10000);
-sort_bench!(sort_large_big_descending, gen_big_descending, 10000);
+sort_expensive!(sort_unstable_by, sort_unstable_large_random_expensive, gen_random, 10000);
-
-#[bench]
-fn sort_large_random_expensive(b: &mut Bencher) {
-    let len = 10000;
-    b.iter(|| {
-        let mut v = gen_random(len);
-        let mut count = 0;
-        v.sort_by(|a: &u64, b: &u64| {
-            count += 1;
-            if count % 1_000_000_000 == 0 {
-                panic!("should not happen");
-            }
-            (*a as f64).cos().partial_cmp(&(*b as f64).cos()).unwrap()
-        });
-        black_box(count);
-    });
-    b.bytes = len as u64 * mem::size_of::<u64>() as u64;
-}

src/libcollections/lib.rs

@@ -52,6 +52,7 @@
 #![feature(shared)]
 #![feature(slice_get_slice)]
 #![feature(slice_patterns)]
+#![feature(sort_unstable)]
 #![feature(specialization)]
 #![feature(staged_api)]
 #![feature(str_internals)]

src/libcollections/slice.rs

@@ -1092,36 +1092,6 @@ impl<T> [T] {
         merge_sort(self, |a, b| a.lt(b));
     }
 
-    /// Sorts the slice using `f` to extract a key to compare elements by.
-    ///
-    /// This sort is stable (i.e. does not reorder equal elements) and `O(n log n)` worst-case.
-    ///
-    /// # 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<B, F>(&mut self, mut f: F)
-        where F: FnMut(&T) -> B, B: Ord
-    {
-        merge_sort(self, |a, b| f(a).lt(&f(b)));
-    }
-
     /// Sorts the slice using `compare` to compare elements.
     ///
     /// This sort is stable (i.e. does not reorder equal elements) and `O(n log n)` worst-case.
@@ -1155,6 +1125,144 @@ impl<T> [T] {
         merge_sort(self, |a, b| compare(a, b) == Less);
     }
 
+    /// Sorts the slice using `f` to extract a key to compare elements by.
+    ///
+    /// This sort is stable (i.e. does not reorder equal elements) and `O(n log n)` worst-case.
+    ///
+    /// # 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<B, F>(&mut self, mut f: F)
+        where F: FnMut(&T) -> B, B: Ord
+    {
+        merge_sort(self, |a, b| f(a).lt(&f(b)));
+    }
+
+    /// Sorts the slice, but may not preserve the order of equal elements.
+    ///
+    /// This sort is unstable (i.e. may reorder equal elements), in-place (i.e. does not allocate),
+    /// and `O(n log n)` worst-case.
+    ///
+    /// # Current implementation
+    ///
+    /// The current algorithm is based on Orson Peters' [pdqsort][pattern-defeating quicksort],
+    /// which is a quicksort variant designed to be very fast on certain kinds of patterns,
+    /// sometimes achieving linear time. It is randomized but deterministic, and falls back to
+    /// heapsort on degenerate inputs.
+    ///
+    /// It is generally faster than stable sorting, except in a few special cases, e.g. when the
+    /// slice consists of several concatenated sorted sequences.
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// let mut v = [-5, 4, 1, -3, 2];
+    ///
+    /// v.sort_unstable();
+    /// assert!(v == [-5, -3, 1, 2, 4]);
+    /// ```
+    ///
+    /// [pdqsort]: https://github.com/orlp/pdqsort
+    // FIXME #40585: Mention `sort_unstable` in the documentation for `sort`.
+    #[unstable(feature = "sort_unstable", issue = "40585")]
+    #[inline]
+    pub fn sort_unstable(&mut self)
+        where T: Ord
+    {
+        core_slice::SliceExt::sort_unstable(self);
+    }
+
+    /// Sorts the slice using `compare` to compare elements, but may not preserve the order of
+    /// equal elements.
+    ///
+    /// This sort is unstable (i.e. may reorder equal elements), in-place (i.e. does not allocate),
+    /// and `O(n log n)` worst-case.
+    ///
+    /// # Current implementation
+    ///
+    /// The current algorithm is based on Orson Peters' [pdqsort][pattern-defeating quicksort],
+    /// which is a quicksort variant designed to be very fast on certain kinds of patterns,
+    /// sometimes achieving linear time. It is randomized but deterministic, and falls back to
+    /// heapsort on degenerate inputs.
+    ///
+    /// It is generally faster than stable sorting, except in a few special cases, e.g. when the
+    /// slice consists of several concatenated sorted sequences.
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// let mut v = [5, 4, 1, 3, 2];
+    /// v.sort_unstable_by(|a, b| a.cmp(b));
+    /// assert!(v == [1, 2, 3, 4, 5]);
+    ///
+    /// // reverse sorting
+    /// v.sort_unstable_by(|a, b| b.cmp(a));
+    /// assert!(v == [5, 4, 3, 2, 1]);
+    /// ```
+    ///
+    /// [pdqsort]: https://github.com/orlp/pdqsort
+    // FIXME #40585: Mention `sort_unstable_by` in the documentation for `sort_by`.
+    #[unstable(feature = "sort_unstable", issue = "40585")]
+    #[inline]
+    pub fn sort_unstable_by<F>(&mut self, compare: F)
+        where F: FnMut(&T, &T) -> Ordering
+    {
+        core_slice::SliceExt::sort_unstable_by(self, compare);
+    }
+
+    /// Sorts the slice using `f` to extract a key to compare elements by, but may not preserve the
+    /// order of equal elements.
+    ///
+    /// This sort is unstable (i.e. may reorder equal elements), in-place (i.e. does not allocate),
+    /// and `O(n log n)` worst-case.
+    ///
+    /// # Current implementation
+    ///
+    /// The current algorithm is based on Orson Peters' [pdqsort][pattern-defeating quicksort],
+    /// which is a quicksort variant designed to be very fast on certain kinds of patterns,
+    /// sometimes achieving linear time. It is randomized but deterministic, and falls back to
+    /// heapsort on degenerate inputs.
+    ///
+    /// It is generally faster than stable sorting, except in a few special cases, e.g. when the
+    /// slice consists of several concatenated sorted sequences.
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// let mut v = [-5i32, 4, 1, -3, 2];
+    ///
+    /// v.sort_unstable_by_key(|k| k.abs());
+    /// assert!(v == [1, 2, -3, 4, -5]);
+    ///
+    /// [pdqsort]: https://github.com/orlp/pdqsort
+    /// ```
+    // FIXME #40585: Mention `sort_unstable_by_key` in the documentation for `sort_by_key`.
+    #[unstable(feature = "sort_unstable", issue = "40585")]
+    #[inline]
+    pub fn sort_unstable_by_key<B, F>(&mut self, f: F)
+        where F: FnMut(&T) -> B,
+              B: Ord
+    {
+        core_slice::SliceExt::sort_unstable_by_key(self, f);
+    }
+
     /// Copies the elements from `src` into `self`.
     ///
     /// The length of `src` must be the same as `self`.
@@ -1553,28 +1661,20 @@ unsafe fn merge<T, F>(v: &mut [T], mid: usize, buf: *mut T, is_less: &mut F)
 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 = 16;
+    // Very short runs are extended using insertion sort to span at least this many elements.
+    const MIN_RUN: usize = 8;
+
     // Sorting has no meaningful behavior on zero-sized types.
     if size_of::<T>() == 0 {
         return;
     }
 
-    // FIXME #12092: These numbers are platform-specific and need more extensive testing/tuning.
-    //
-    // If `v` has length up to `max_insertion`, simply switch to insertion sort because it is going
-    // to perform better than merge sort. For bigger types `T`, the threshold is smaller.
-    //
-    // Short runs are extended using insertion sort to span at least `min_run` elements, in order
-    // to improve performance.
-    let (max_insertion, min_run) = if size_of::<T>() <= 2 * mem::size_of::<usize>() {
-        (64, 32)
-    } else {
-        (32, 16)
-    };
-
     let len = v.len();
 
     // Short arrays get sorted in-place via insertion sort to avoid allocations.
-    if len <= max_insertion {
+    if len <= MAX_INSERTION {
         if len >= 2 {
             for i in (0..len-1).rev() {
                 insert_head(&mut v[i..], &mut is_less);
@@ -1618,7 +1718,7 @@ fn merge_sort<T, F>(v: &mut [T], mut is_less: F)
 
         // 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 {
+        while start > 0 && end - start < MIN_RUN {
             start -= 1;
             insert_head(&mut v[start..end], &mut is_less);
         }

src/libcollectionstest/slice.rs

@@ -399,9 +399,10 @@ fn test_sort() {
         }
     }
 
-    // shouldn't panic
+    // Should not panic.
-    let mut v: [i32; 0] = [];
+    [0i32; 0].sort();
-    v.sort();
+    [(); 10].sort();
+    [(); 100].sort();
 
     let mut v = [0xDEADBEEFu64];
     v.sort();
@@ -441,13 +442,6 @@ fn test_sort_stability() {
     }
 }
 
-#[test]
-fn test_sort_zero_sized_type() {
-    // Should not panic.
-    [(); 10].sort();
-    [(); 100].sort();
-}
-
 #[test]
 fn test_concat() {
     let v: [Vec<i32>; 0] = [];

src/libcore/lib.rs

@@ -71,26 +71,27 @@
 #![feature(asm)]
 #![feature(associated_type_defaults)]
 #![feature(cfg_target_feature)]
+#![feature(cfg_target_has_atomic)]
 #![feature(concat_idents)]
 #![feature(const_fn)]
-#![feature(cfg_target_has_atomic)]
 #![feature(custom_attribute)]
 #![feature(fundamental)]
+#![feature(i128_type)]
 #![feature(inclusive_range_syntax)]
 #![feature(intrinsics)]
 #![feature(lang_items)]
+#![feature(never_type)]
 #![feature(no_core)]
 #![feature(on_unimplemented)]
 #![feature(optin_builtin_traits)]
-#![feature(unwind_attributes)]
+#![feature(prelude_import)]
 #![feature(repr_simd, platform_intrinsics)]
 #![feature(rustc_attrs)]
 #![feature(specialization)]
 #![feature(staged_api)]
 #![feature(unboxed_closures)]
-#![feature(never_type)]
+#![feature(untagged_unions)]
-#![feature(i128_type)]
+#![feature(unwind_attributes)]
-#![feature(prelude_import)]
 
 #[prelude_import]
 #[allow(unused)]

src/libcore/slice/mod.rs

@@ -1,4 +1,4 @@
-// Copyright 2012-2014 The Rust Project Developers. See the COPYRIGHT
+// Copyright 2012-2017 The Rust Project Developers. See the COPYRIGHT
 // file at the top-level directory of this distribution and at
 // http://rust-lang.org/COPYRIGHT.
 //
@@ -51,6 +51,8 @@ use mem;
 use marker::{Copy, Send, Sync, Sized, self};
 use iter_private::TrustedRandomAccess;
 
+mod sort;
+
 #[repr(C)]
 struct Repr<T> {
     pub data: *const T,
@@ -71,86 +73,119 @@ pub trait SliceExt {
 
     #[stable(feature = "core", since = "1.6.0")]
     fn split_at(&self, mid: usize) -> (&[Self::Item], &[Self::Item]);
+
     #[stable(feature = "core", since = "1.6.0")]
     fn iter(&self) -> Iter<Self::Item>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn split<P>(&self, pred: P) -> Split<Self::Item, P>
-                    where P: FnMut(&Self::Item) -> bool;
+        where P: FnMut(&Self::Item) -> bool;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn splitn<P>(&self, n: usize, pred: P) -> SplitN<Self::Item, P>
-                     where P: FnMut(&Self::Item) -> bool;
+        where P: FnMut(&Self::Item) -> bool;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn rsplitn<P>(&self,  n: usize, pred: P) -> RSplitN<Self::Item, P>
-                      where P: FnMut(&Self::Item) -> bool;
+        where P: FnMut(&Self::Item) -> bool;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn windows(&self, size: usize) -> Windows<Self::Item>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn chunks(&self, size: usize) -> Chunks<Self::Item>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn get<I>(&self, index: I) -> Option<&I::Output>
         where I: SliceIndex<Self::Item>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn first(&self) -> Option<&Self::Item>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn split_first(&self) -> Option<(&Self::Item, &[Self::Item])>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn split_last(&self) -> Option<(&Self::Item, &[Self::Item])>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn last(&self) -> Option<&Self::Item>;
+
     #[stable(feature = "core", since = "1.6.0")]
     unsafe fn get_unchecked<I>(&self, index: I) -> &I::Output
         where I: SliceIndex<Self::Item>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn as_ptr(&self) -> *const Self::Item;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn binary_search<Q: ?Sized>(&self, x: &Q) -> Result<usize, usize>
         where Self::Item: Borrow<Q>,
               Q: Ord;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn binary_search_by<'a, F>(&'a self, f: F) -> Result<usize, usize>
         where F: FnMut(&'a Self::Item) -> Ordering;
+
     #[stable(feature = "slice_binary_search_by_key", since = "1.10.0")]
     fn binary_search_by_key<'a, B, F, Q: ?Sized>(&'a self, b: &Q, f: F) -> Result<usize, usize>
         where F: FnMut(&'a Self::Item) -> B,
               B: Borrow<Q>,
               Q: Ord;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn len(&self) -> usize;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn is_empty(&self) -> bool { self.len() == 0 }
+
     #[stable(feature = "core", since = "1.6.0")]
     fn get_mut<I>(&mut self, index: I) -> Option<&mut I::Output>
         where I: SliceIndex<Self::Item>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn iter_mut(&mut self) -> IterMut<Self::Item>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn first_mut(&mut self) -> Option<&mut Self::Item>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn split_first_mut(&mut self) -> Option<(&mut Self::Item, &mut [Self::Item])>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn split_last_mut(&mut self) -> Option<(&mut Self::Item, &mut [Self::Item])>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn last_mut(&mut self) -> Option<&mut Self::Item>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn split_mut<P>(&mut self, pred: P) -> SplitMut<Self::Item, P>
-                        where P: FnMut(&Self::Item) -> bool;
+        where P: FnMut(&Self::Item) -> bool;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn splitn_mut<P>(&mut self, n: usize, pred: P) -> SplitNMut<Self::Item, P>
-                     where P: FnMut(&Self::Item) -> bool;
+        where P: FnMut(&Self::Item) -> bool;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn rsplitn_mut<P>(&mut self,  n: usize, pred: P) -> RSplitNMut<Self::Item, P>
-                      where P: FnMut(&Self::Item) -> bool;
+        where P: FnMut(&Self::Item) -> bool;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn chunks_mut(&mut self, chunk_size: usize) -> ChunksMut<Self::Item>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn swap(&mut self, a: usize, b: usize);
+
     #[stable(feature = "core", since = "1.6.0")]
     fn split_at_mut(&mut self, mid: usize) -> (&mut [Self::Item], &mut [Self::Item]);
+
     #[stable(feature = "core", since = "1.6.0")]
     fn reverse(&mut self);
+
     #[stable(feature = "core", since = "1.6.0")]
     unsafe fn get_unchecked_mut<I>(&mut self, index: I) -> &mut I::Output
         where I: SliceIndex<Self::Item>;
+
     #[stable(feature = "core", since = "1.6.0")]
     fn as_mut_ptr(&mut self) -> *mut Self::Item;
 
@@ -165,8 +200,22 @@ pub trait SliceExt {
 
     #[stable(feature = "clone_from_slice", since = "1.7.0")]
     fn clone_from_slice(&mut self, src: &[Self::Item]) where Self::Item: Clone;
+
     #[stable(feature = "copy_from_slice", since = "1.9.0")]
     fn copy_from_slice(&mut self, src: &[Self::Item]) where Self::Item: Copy;
+
+    #[unstable(feature = "sort_unstable", issue = "40585")]
+    fn sort_unstable(&mut self)
+        where Self::Item: Ord;
+
+    #[unstable(feature = "sort_unstable", issue = "40585")]
+    fn sort_unstable_by<F>(&mut self, compare: F)
+        where F: FnMut(&Self::Item, &Self::Item) -> Ordering;
+
+    #[unstable(feature = "sort_unstable", issue = "40585")]
+    fn sort_unstable_by_key<B, F>(&mut self, f: F)
+        where F: FnMut(&Self::Item) -> B,
+              B: Ord;
 }
 
 // Use macros to be generic over const/mut
@@ -238,7 +287,9 @@ impl<T> SliceExt for [T] {
     }
 
     #[inline]
-    fn split<P>(&self, pred: P) -> Split<T, P> where P: FnMut(&T) -> bool {
+    fn split<P>(&self, pred: P) -> Split<T, P>
+        where P: FnMut(&T) -> bool
+    {
         Split {
             v: self,
             pred: pred,
@@ -247,8 +298,8 @@ impl<T> SliceExt for [T] {
     }
 
     #[inline]
-    fn splitn<P>(&self, n: usize, pred: P) -> SplitN<T, P> where
+    fn splitn<P>(&self, n: usize, pred: P) -> SplitN<T, P>
-        P: FnMut(&T) -> bool,
+        where P: FnMut(&T) -> bool
     {
         SplitN {
             inner: GenericSplitN {
@@ -260,8 +311,8 @@ impl<T> SliceExt for [T] {
     }
 
     #[inline]
-    fn rsplitn<P>(&self, n: usize, pred: P) -> RSplitN<T, P> where
+    fn rsplitn<P>(&self, n: usize, pred: P) -> RSplitN<T, P>
-        P: FnMut(&T) -> bool,
+        where P: FnMut(&T) -> bool
     {
         RSplitN {
             inner: GenericSplitN {
@@ -422,13 +473,15 @@ impl<T> SliceExt for [T] {
     }
 
     #[inline]
-    fn split_mut<P>(&mut self, pred: P) -> SplitMut<T, P> where P: FnMut(&T) -> bool {
+    fn split_mut<P>(&mut self, pred: P) -> SplitMut<T, P>
+        where P: FnMut(&T) -> bool
+    {
         SplitMut { v: self, pred: pred, finished: false }
     }
 
     #[inline]
-    fn splitn_mut<P>(&mut self, n: usize, pred: P) -> SplitNMut<T, P> where
+    fn splitn_mut<P>(&mut self, n: usize, pred: P) -> SplitNMut<T, P>
-        P: FnMut(&T) -> bool
+        where P: FnMut(&T) -> bool
     {
         SplitNMut {
             inner: GenericSplitN {
@@ -450,7 +503,7 @@ impl<T> SliceExt for [T] {
                 invert: true
             }
         }
-   }
+    }
 
     #[inline]
     fn chunks_mut(&mut self, chunk_size: usize) -> ChunksMut<T> {
@@ -512,7 +565,10 @@ impl<T> SliceExt for [T] {
         m >= n && needle == &self[m-n..]
     }
 
-    fn binary_search<Q: ?Sized>(&self, x: &Q) -> Result<usize, usize> where T: Borrow<Q>, Q: Ord {
+    fn binary_search<Q: ?Sized>(&self, x: &Q) -> Result<usize, usize>
+        where T: Borrow<Q>,
+              Q: Ord
+    {
         self.binary_search_by(|p| p.borrow().cmp(x))
     }
 
@@ -548,6 +604,28 @@ impl<T> SliceExt for [T] {
     {
         self.binary_search_by(|k| f(k).borrow().cmp(b))
     }
+
+    #[inline]
+    fn sort_unstable(&mut self)
+        where Self::Item: Ord
+    {
+        sort::quicksort(self, |a, b| a.lt(b));
+    }
+
+    #[inline]
+    fn sort_unstable_by<F>(&mut self, mut compare: F)
+        where F: FnMut(&Self::Item, &Self::Item) -> Ordering
+    {
+        sort::quicksort(self, |a, b| compare(a, b) == Ordering::Less);
+    }
+
+    #[inline]
+    fn sort_unstable_by_key<B, F>(&mut self, mut f: F)
+        where F: FnMut(&Self::Item) -> B,
+              B: Ord
+    {
+        sort::quicksort(self, |a, b| f(a).lt(&f(b)));
+    }
 }
 
 #[stable(feature = "rust1", since = "1.0.0")]

src/libcore/slice/sort.rs

@@ -0,0 +1,628 @@
+// Copyright 2017 The Rust Project Developers. See the COPYRIGHT
+// file at the top-level directory of this distribution and at
+// http://rust-lang.org/COPYRIGHT.
+//
+// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
+// http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
+// <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your
+// option. This file may not be copied, modified, or distributed
+// except according to those terms.
+
+//! Slice sorting
+//!
+//! This module contains an sort algorithm based on Orson Peters' pattern-defeating quicksort,
+//! published at: https://github.com/orlp/pdqsort
+//!
+//! Unstable sorting is compatible with libcore because it doesn't allocate memory, unlike our
+//! stable sorting implementation.
+
+#![unstable(feature = "sort_unstable", issue = "40585")]
+
+use cmp;
+use mem;
+use ptr;
+
+/// Holds a value, but never drops it.
+#[allow(unions_with_drop_fields)]
+union NoDrop<T> {
+    value: T
+}
+
+/// When dropped, copies from `src` into `dest`.
+struct CopyOnDrop<T> {
+    src: *mut T,
+    dest: *mut T,
+}
+
+impl<T> Drop for CopyOnDrop<T> {
+    fn drop(&mut self) {
+        unsafe { ptr::copy_nonoverlapping(self.src, self.dest, 1); }
+    }
+}
+
+/// Sorts a slice using insertion sort, which is `O(n^2)` worst-case.
+fn insertion_sort<T, F>(v: &mut [T], is_less: &mut F)
+    where F: FnMut(&T, &T) -> bool
+{
+    let len = v.len();
+
+    for i in 1..len {
+        unsafe {
+            if is_less(v.get_unchecked(i), v.get_unchecked(i - 1)) {
+                // 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 = NoDrop { value: ptr::read(v.get_unchecked(i)) };
+
+                // 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 = CopyOnDrop {
+                    src: &mut tmp.value,
+                    dest: v.get_unchecked_mut(i - 1),
+                };
+                ptr::copy_nonoverlapping(v.get_unchecked(i - 1), v.get_unchecked_mut(i), 1);
+
+                for h in (0..i-1).rev() {
+                    if !is_less(&tmp.value, v.get_unchecked(h)) {
+                        break;
+                    }
+                    ptr::copy_nonoverlapping(v.get_unchecked(h), v.get_unchecked_mut(h + 1), 1);
+                    hole.dest = v.get_unchecked_mut(h);
+                }
+                // `hole` gets dropped and thus copies `tmp` into the remaining hole in `v`.
+            }
+        }
+    }
+}
+
+/// Sorts `v` using heapsort, which guarantees `O(n log n)` worst-case.
+#[cold]
+fn heapsort<T, F>(v: &mut [T], is_less: &mut F)
+    where F: FnMut(&T, &T) -> bool
+{
+    // This binary heap respects the invariant `parent >= child`.
+    let mut sift_down = |v: &mut [T], mut node| {
+        loop {
+            // Children of `node`:
+            let left = 2 * node + 1;
+            let right = 2 * node + 2;
+
+            // Choose the greater child.
+            let greater = if right < v.len() && is_less(&v[left], &v[right]) {
+                right
+            } else {
+                left
+            };
+
+            // Stop if the invariant holds at `node`.
+            if greater >= v.len() || !is_less(&v[node], &v[greater]) {
+                break;
+            }
+
+            // Swap `node` with the greater child, move one step down, and continue sifting.
+            v.swap(node, greater);
+            node = greater;
+        }
+    };
+
+    // Build the heap in linear time.
+    for i in (0 .. v.len() / 2).rev() {
+        sift_down(v, i);
+    }
+
+    // Pop maximal elements from the heap.
+    for i in (1 .. v.len()).rev() {
+        v.swap(0, i);
+        sift_down(&mut v[..i], 0);
+    }
+}
+
+/// Partitions `v` into elements smaller than `pivot`, followed by elements greater than or equal
+/// to `pivot`.
+///
+/// Returns the number of elements smaller than `pivot`.
+///
+/// Partitioning is performed block-by-block in order to minimize the cost of branching operations.
+/// This idea is presented in the [BlockQuicksort][pdf] paper.
+///
+/// [pdf]: http://drops.dagstuhl.de/opus/volltexte/2016/6389/pdf/LIPIcs-ESA-2016-38.pdf
+fn partition_in_blocks<T, F>(v: &mut [T], pivot: &T, is_less: &mut F) -> usize
+    where F: FnMut(&T, &T) -> bool
+{
+    // Number of elements in a typical block.
+    const BLOCK: usize = 128;
+
+    // The partitioning algorithm repeats the following steps until completion:
+    //
+    // 1. Trace a block from the left side to identify elements greater than or equal to the pivot.
+    // 2. Trace a block from the right side to identify elements less than the pivot.
+    // 3. Exchange the identified elements between the left and right side.
+    //
+    // We keep the following variables for a block of elements:
+    //
+    // 1. `block` - Number of elements in the block.
+    // 2. `start` - Start pointer into the `offsets` array.
+    // 3. `end` - End pointer into the `offsets` array.
+    // 4. `offsets - Indices of out-of-order elements within the block.
+
+    // The current block on the left side: `v[l .. l + block_l]`.
+    let mut l = v.as_mut_ptr();
+    let mut block_l = BLOCK;
+    let mut start_l = ptr::null_mut();
+    let mut end_l = ptr::null_mut();
+    let mut offsets_l: [u8; BLOCK] = unsafe { mem::uninitialized() };
+
+    // The current block on the right side: `v[r - block_r .. r]`.
+    let mut r = unsafe { l.offset(v.len() as isize) };
+    let mut block_r = BLOCK;
+    let mut start_r = ptr::null_mut();
+    let mut end_r = ptr::null_mut();
+    let mut offsets_r: [u8; BLOCK] = unsafe { mem::uninitialized() };
+
+    // Returns the number of elements between pointers `l` (inclusive) and `r` (exclusive).
+    fn width<T>(l: *mut T, r: *mut T) -> usize {
+        assert!(mem::size_of::<T>() > 0);
+        (r as usize - l as usize) / mem::size_of::<T>()
+    }
+
+    loop {
+        // We are done with partitioning block-by-block when `l` and `r` get very close. Then we do
+        // some patch-up work in order to partition the remaining elements in between.
+        let is_done = width(l, r) <= 2 * BLOCK;
+
+        if is_done {
+            // Number of remaining elements (still not compared to the pivot).
+            let mut rem = width(l, r);
+            if start_l < end_l || start_r < end_r {
+                rem -= BLOCK;
+            }
+
+            // Adjust block sizes so that the left and right block don't overlap, but get perfectly
+            // aligned to cover the whole remaining gap.
+            if start_l < end_l {
+                block_r = rem;
+            } else if start_r < end_r {
+                block_l = rem;
+            } else {
+                block_l = rem / 2;
+                block_r = rem - block_l;
+            }
+            debug_assert!(block_l <= BLOCK && block_r <= BLOCK);
+            debug_assert!(width(l, r) == block_l + block_r);
+        }
+
+        if start_l == end_l {
+            // Trace `block_l` elements from the left side.
+            start_l = offsets_l.as_mut_ptr();
+            end_l = offsets_l.as_mut_ptr();
+            let mut elem = l;
+
+            for i in 0..block_l {
+                unsafe {
+                    // Branchless comparison.
+                    *end_l = i as u8;
+                    end_l = end_l.offset(!is_less(&*elem, pivot) as isize);
+                    elem = elem.offset(1);
+                }
+            }
+        }
+
+        if start_r == end_r {
+            // Trace `block_r` elements from the right side.
+            start_r = offsets_r.as_mut_ptr();
+            end_r = offsets_r.as_mut_ptr();
+            let mut elem = r;
+
+            for i in 0..block_r {
+                unsafe {
+                    // Branchless comparison.
+                    elem = elem.offset(-1);
+                    *end_r = i as u8;
+                    end_r = end_r.offset(is_less(&*elem, pivot) as isize);
+                }
+            }
+        }
+
+        // Number of out-of-order elements to swap between the left and right side.
+        let count = cmp::min(width(start_l, end_l), width(start_r, end_r));
+
+        if count > 0 {
+            macro_rules! left { () => { l.offset(*start_l as isize) } }
+            macro_rules! right { () => { r.offset(-(*start_r as isize) - 1) } }
+
+            // Instead of swapping one pair at the time, it is more efficient to perform a cyclic
+            // permutation. This is not strictly equivalent to swapping, but produces a similar
+            // result using fewer memory operations.
+            unsafe {
+                let tmp = ptr::read(left!());
+                ptr::copy_nonoverlapping(right!(), left!(), 1);
+
+                for _ in 1..count {
+                    start_l = start_l.offset(1);
+                    ptr::copy_nonoverlapping(left!(), right!(), 1);
+                    start_r = start_r.offset(1);
+                    ptr::copy_nonoverlapping(right!(), left!(), 1);
+                }
+
+                ptr::copy_nonoverlapping(&tmp, right!(), 1);
+                mem::forget(tmp);
+                start_l = start_l.offset(1);
+                start_r = start_r.offset(1);
+            }
+        }
+
+        if start_l == end_l {
+            // All out-of-order elements in the left block were moved. Move to the next block.
+            l = unsafe { l.offset(block_l as isize) };
+        }
+
+        if start_r == end_r {
+            // All out-of-order elements in the right block were moved. Move to the previous block.
+            r = unsafe { r.offset(-(block_r as isize)) };
+        }
+
+        if is_done {
+            break;
+        }
+    }
+
+    // All that remains now is at most one block (either the left or the right) with out-of-order
+    // elements that need to be moved. Such remaining elements can be simply shifted to the end
+    // within their block.
+
+    if start_l < end_l {
+        // The left block remains.
+        // Move it's remaining out-of-order elements to the far right.
+        debug_assert_eq!(width(l, r), block_l);
+        while start_l < end_l {
+            unsafe {
+                end_l = end_l.offset(-1);
+                ptr::swap(l.offset(*end_l as isize), r.offset(-1));
+                r = r.offset(-1);
+            }
+        }
+        width(v.as_mut_ptr(), r)
+    } else if start_r < end_r {
+        // The right block remains.
+        // Move it's remaining out-of-order elements to the far left.
+        debug_assert_eq!(width(l, r), block_r);
+        while start_r < end_r {
+            unsafe {
+                end_r = end_r.offset(-1);
+                ptr::swap(l, r.offset(-(*end_r as isize) - 1));
+                l = l.offset(1);
+            }
+        }
+        width(v.as_mut_ptr(), l)
+    } else {
+        // Nothing else to do, we're done.
+        width(v.as_mut_ptr(), l)
+    }
+}
+
+/// Partitions `v` into elements smaller than `v[pivot]`, followed by elements greater than or
+/// equal to `v[pivot]`.
+///
+/// Returns a tuple of:
+///
+/// 1. Number of elements smaller than `v[pivot]`.
+/// 2. True if `v` was already partitioned.
+fn partition<T, F>(v: &mut [T], pivot: usize, is_less: &mut F) -> (usize, bool)
+    where F: FnMut(&T, &T) -> bool
+{
+    let (mid, was_partitioned) = {
+        // Place the pivot at the beginning of slice.
+        v.swap(0, pivot);
+        let (pivot, v) = v.split_at_mut(1);
+        let pivot = &mut pivot[0];
+
+        // Read the pivot into a stack-allocated variable for efficiency. If a following comparison
+        // operation panics, the pivot will be automatically written back into the slice.
+        let mut tmp = NoDrop { value: unsafe { ptr::read(pivot) } };
+        let _pivot_guard = CopyOnDrop {
+            src: unsafe { &mut tmp.value },
+            dest: pivot,
+        };
+        let pivot = unsafe { &tmp.value };
+
+        // Find the first pair of out-of-order elements.
+        let mut l = 0;
+        let mut r = v.len();
+        unsafe {
+            // Find the first element greater then or equal to the pivot.
+            while l < r && is_less(v.get_unchecked(l), pivot) {
+                l += 1;
+            }
+
+            // Find the last element lesser that the pivot.
+            while l < r && !is_less(v.get_unchecked(r - 1), pivot) {
+                r -= 1;
+            }
+        }
+
+        (l + partition_in_blocks(&mut v[l..r], pivot, is_less), l >= r)
+
+        // `_pivot_guard` goes out of scope and writes the pivot (which is a stack-allocated
+        // variable) back into the slice where it originally was. This step is critical in ensuring
+        // safety!
+    };
+
+    // Place the pivot between the two partitions.
+    v.swap(0, mid);
+
+    (mid, was_partitioned)
+}
+
+/// Partitions `v` into elements equal to `v[pivot]` followed by elements greater than `v[pivot]`.
+///
+/// Returns the number of elements equal to the pivot. It is assumed that `v` does not contain
+/// elements smaller than the pivot.
+fn partition_equal<T, F>(v: &mut [T], pivot: usize, is_less: &mut F) -> usize
+    where F: FnMut(&T, &T) -> bool
+{
+    // Place the pivot at the beginning of slice.
+    v.swap(0, pivot);
+    let (pivot, v) = v.split_at_mut(1);
+    let pivot = &mut pivot[0];
+
+    // Read the pivot into a stack-allocated variable for efficiency. If a following comparison
+    // operation panics, the pivot will be automatically written back into the slice.
+    let mut tmp = NoDrop { value: unsafe { ptr::read(pivot) } };
+    let _pivot_guard = CopyOnDrop {
+        src: unsafe { &mut tmp.value },
+        dest: pivot,
+    };
+    let pivot = unsafe { &tmp.value };
+
+    // Now partition the slice.
+    let mut l = 0;
+    let mut r = v.len();
+    loop {
+        unsafe {
+            // Find the first element greater that the pivot.
+            while l < r && !is_less(pivot, v.get_unchecked(l)) {
+                l += 1;
+            }
+
+            // Find the last element equal to the pivot.
+            while l < r && is_less(pivot, v.get_unchecked(r - 1)) {
+                r -= 1;
+            }
+
+            // Are we done?
+            if l >= r {
+                break;
+            }
+
+            // Swap the found pair of out-of-order elements.
+            r -= 1;
+            ptr::swap(v.get_unchecked_mut(l), v.get_unchecked_mut(r));
+            l += 1;
+        }
+    }
+
+    // We found `l` elements equal to the pivot. Add 1 to account for the pivot itself.
+    l + 1
+
+    // `_pivot_guard` goes out of scope and writes the pivot (which is a stack-allocated variable)
+    // back into the slice where it originally was. This step is critical in ensuring safety!
+}
+
+/// Scatters some elements around in an attempt to break patterns that might cause imbalanced
+/// partitions in quicksort.
+#[cold]
+fn break_patterns<T>(v: &mut [T]) {
+    let len = v.len();
+
+    if len >= 8 {
+        // A random number will be taken modulo this one. The modulus is a power of two so that we
+        // can simply take bitwise "and", thus avoiding costly CPU operations.
+        let modulus = (len / 4).next_power_of_two();
+        debug_assert!(modulus >= 1 && modulus <= len / 2);
+
+        // Pseudorandom number generation from the "Xorshift RNGs" paper by George Marsaglia.
+        let mut random = len;
+        random ^= random << 13;
+        random ^= random >> 17;
+        random ^= random << 5;
+        random &= modulus - 1;
+        debug_assert!(random < len / 2);
+
+        // The first index.
+        let a = len / 4 * 2;
+        debug_assert!(a >= 1 && a < len - 2);
+
+        // The second index.
+        let b = len / 4 + random;
+        debug_assert!(b >= 1 && b < len - 2);
+
+        // Swap neighbourhoods of `a` and `b`.
+        for i in 0..3 {
+            v.swap(a - 1 + i, b - 1 + i);
+        }
+    }
+}
+
+/// Chooses a pivot in `v` and returns it's index.
+///
+/// Elements in `v` might be reordered in the process.
+fn choose_pivot<T, F>(v: &mut [T], is_less: &mut F) -> usize
+    where F: FnMut(&T, &T) -> bool
+{
+    // Minimal length to choose the median-of-medians method.
+    // Shorter slices use the simple median-of-three method.
+    const SHORTEST_MEDIAN_OF_MEDIANS: usize = 90;
+    // Maximal number of swaps that can be performed in this function.
+    const MAX_SWAPS: usize = 4 * 3;
+
+    let len = v.len();
+
+    // Three indices near which we are going to choose a pivot.
+    let mut a = len / 4 * 1;
+    let mut b = len / 4 * 2;
+    let mut c = len / 4 * 3;
+
+    // Counts the total number of swaps we are about to perform while sorting indices.
+    let mut swaps = 0;
+
+    if len >= 8 {
+        // Swaps indices so that `v[a] <= v[b]`.
+        let mut sort2 = |a: &mut usize, b: &mut usize| unsafe {
+            if is_less(v.get_unchecked(*b), v.get_unchecked(*a)) {
+                ptr::swap(a, b);
+                swaps += 1;
+            }
+        };
+
+        // Swaps indices so that `v[a] <= v[b] <= v[c]`.
+        let mut sort3 = |a: &mut usize, b: &mut usize, c: &mut usize| {
+            sort2(a, b);
+            sort2(b, c);
+            sort2(a, b);
+        };
+
+        if len >= SHORTEST_MEDIAN_OF_MEDIANS {
+            // Finds the median of `v[a - 1], v[a], v[a + 1]` and stores the index into `a`.
+            let mut sort_adjacent = |a: &mut usize| {
+                let tmp = *a;
+                sort3(&mut (tmp - 1), a, &mut (tmp + 1));
+            };
+
+            // Find medians in the neighborhoods of `a`, `b`, and `c`.
+            sort_adjacent(&mut a);
+            sort_adjacent(&mut b);
+            sort_adjacent(&mut c);
+        }
+
+        // Find the median among `a`, `b`, and `c`.
+        sort3(&mut a, &mut b, &mut c);
+    }
+
+    if swaps < MAX_SWAPS {
+        b
+    } else {
+        // The maximal number of swaps was performed. Chances are the slice is descending or mostly
+        // descending, so reversing will probably help sort it faster.
+        v.reverse();
+        len - 1 - b
+    }
+}
+
+/// Sorts `v` recursively.
+///
+/// If the slice had a predecessor in the original array, it is specified as `pred`.
+///
+/// `limit` is the number of allowed imbalanced partitions before switching to `heapsort`. If zero,
+/// this function will immediately switch to heapsort.
+fn recurse<'a, T, F>(mut v: &'a mut [T], is_less: &mut F, mut pred: Option<&'a T>, mut limit: usize)
+    where F: FnMut(&T, &T) -> bool
+{
+    // Slices of up to this length get sorted using insertion sort.
+    const MAX_INSERTION: usize = 16;
+
+    // This is `true` if the last partitioning was balanced.
+    let mut was_balanced = true;
+
+    loop {
+        let len = v.len();
+
+        // Very short slices get sorted using insertion sort.
+        if len <= MAX_INSERTION {
+            insertion_sort(v, is_less);
+            return;
+        }
+
+        // If too many bad pivot choices were made, simply fall back to heapsort in order to
+        // guarantee `O(n log n)` worst-case.
+        if limit == 0 {
+            heapsort(v, is_less);
+            return;
+        }
+
+        // If the last partitioning was imbalanced, try breaking patterns in the slice by shuffling
+        // some elements around. Hopefully we'll choose a better pivot this time.
+        if !was_balanced {
+            break_patterns(v);
+            limit -= 1;
+        }
+
+        let pivot = choose_pivot(v, is_less);
+
+        // If the chosen pivot is equal to the predecessor, then it's the smallest element in the
+        // slice. Partition the slice into elements equal to and elements greater than the pivot.
+        // This case is usually hit when the slice contains many duplicate elements.
+        if let Some(p) = pred {
+            if !is_less(p, &v[pivot]) {
+                let mid = partition_equal(v, pivot, is_less);
+
+                // Continue sorting elements greater than the pivot.
+                v = &mut {v}[mid..];
+                continue;
+            }
+        }
+
+        let (mid, was_partitioned) = partition(v, pivot, is_less);
+        was_balanced = cmp::min(mid, len - mid) >= len / 8;
+
+        // If the partitioning is decently balanced and the slice was already partitioned, there
+        // are good chances it is also completely sorted. If so, we're done.
+        if was_balanced && was_partitioned && v.windows(2).all(|w| !is_less(&w[1], &w[0])) {
+            return;
+        }
+
+        // Split the slice into `left`, `pivot`, and `right`.
+        let (left, right) = {v}.split_at_mut(mid);
+        let (pivot, right) = right.split_at_mut(1);
+        let pivot = &pivot[0];
+
+        // Recurse into the shorter side only in order to minimize the total number of recursive
+        // calls and consume less stack space. Then just continue with the longer side (this is
+        // akin to tail recursion).
+        if left.len() < right.len() {
+            recurse(left, is_less, pred, limit);
+            v = right;
+            pred = Some(pivot);
+        } else {
+            recurse(right, is_less, Some(pivot), limit);
+            v = left;
+        }
+    }
+}
+
+/// Sorts `v` using pattern-defeating quicksort, which is `O(n log n)` worst-case.
+pub fn quicksort<T, F>(v: &mut [T], mut is_less: F)
+    where F: FnMut(&T, &T) -> bool
+{
+    // Sorting has no meaningful behavior on zero-sized types.
+    if mem::size_of::<T>() == 0 {
+        return;
+    }
+
+    // Limit the number of imbalanced partitions to `floor(log2(len)) + 2`.
+    let limit = mem::size_of::<usize>() * 8 - v.len().leading_zeros() as usize + 1;
+
+    recurse(v, &mut is_less, None, limit);
+}

src/libcoretest/lib.rs

@@ -19,18 +19,22 @@
 #![feature(decode_utf8)]
 #![feature(fixed_size_array)]
 #![feature(flt2dec)]
+#![feature(fmt_internals)]
 #![feature(libc)]
+#![feature(move_cell)]
 #![feature(nonzero)]
+#![feature(ordering_chaining)]
+#![feature(ptr_unaligned)]
 #![feature(rand)]
 #![feature(raw)]
 #![feature(sip_hash_13)]
 #![feature(slice_patterns)]
+#![feature(sort_unstable)]
 #![feature(step_by)]
 #![feature(test)]
 #![feature(try_from)]
 #![feature(unicode)]
 #![feature(unique)]
-#![feature(fmt_internals)]
 
 extern crate core;
 extern crate test;

src/libcoretest/slice.rs

@@ -9,6 +9,7 @@
 // except according to those terms.
 
 use core::result::Result::{Ok, Err};
+use rand::{Rng, XorShiftRng};
 
 #[test]
 fn test_binary_search() {
@@ -139,9 +140,6 @@ fn test_chunks_mut_last() {
     assert_eq!(c2.last().unwrap()[0], 4);
 }
 
-
-
-
 #[test]
 fn test_windows_count() {
     let v: &[i32] = &[0, 1, 2, 3, 4, 5];
@@ -224,3 +222,40 @@ fn get_unchecked_mut_range() {
         assert_eq!(v.get_unchecked_mut(1..4), &mut [1, 2, 3][..]);
     }
 }
+
+#[test]
+fn sort_unstable() {
+    let mut v = [0; 600];
+    let mut v1 = [0; 600];
+    let mut rng = XorShiftRng::new_unseeded();
+
+    for len in (2..25).chain(500..510) {
+        for &modulus in &[10, 1000] {
+            for _ in 0..100 {
+                for i in 0..len {
+                    let num = rng.gen::<i32>() % modulus;
+                    v[i] = num;
+                    v1[i] = num;
+                }
+
+                v.sort_unstable();
+                assert!(v.windows(2).all(|w| w[0] <= w[1]));
+
+                v1.sort_unstable_by(|a, b| a.cmp(b));
+                assert!(v1.windows(2).all(|w| w[0] <= w[1]));
+
+                v1.sort_unstable_by(|a, b| b.cmp(a));
+                assert!(v1.windows(2).all(|w| w[0] >= w[1]));
+            }
+        }
+    }
+
+    // Should not panic.
+    [0i32; 0].sort_unstable();
+    [(); 10].sort_unstable();
+    [(); 100].sort_unstable();
+
+    let mut v = [0xDEADBEEFu64];
+    v.sort_unstable();
+    assert!(v == [0xDEADBEEF]);
+}