big-O notation: parenthesis for function calls, explicit multiplication

src/liballoc/collections/binary_heap.rs

@@ -1,10 +1,10 @@
 //! A priority queue implemented with a binary heap.
 //!
-//! Insertion and popping the largest element have `O(log n)` time complexity.
+//! Insertion and popping the largest element have `O(log(n))` time complexity.
 //! Checking the largest element is `O(1)`. Converting a vector to a binary heap
 //! can be done in-place, and has `O(n)` complexity. A binary heap can also be
-//! converted to a sorted vector in-place, allowing it to be used for an `O(n
-//! log n)` in-place heapsort.
+//! converted to a sorted vector in-place, allowing it to be used for an `O(n * log(n))`
+//! in-place heapsort.
 //!
 //! # Examples
 //!
@@ -233,9 +233,9 @@ use super::SpecExtend;
 ///
 /// # Time complexity
 ///
-/// | [push] | [pop]    | [peek]/[peek\_mut] |
-/// |--------|----------|--------------------|
-/// | O(1)~  | O(log n) | O(1)               |
+/// | [push] | [pop]     | [peek]/[peek\_mut] |
+/// |--------|-----------|--------------------|
+/// | O(1)~  | O(log(n)) | O(1)               |
 ///
 /// The value for `push` is an expected cost; the method documentation gives a
 /// more detailed analysis.
@@ -398,7 +398,7 @@ impl<T: Ord> BinaryHeap<T> {
     ///
     /// # Time complexity
     ///
-    /// Cost is O(1) in the worst case.
+    /// Cost is `O(1)` in the worst case.
     #[stable(feature = "binary_heap_peek_mut", since = "1.12.0")]
     pub fn peek_mut(&mut self) -> Option<PeekMut<'_, T>> {
         if self.is_empty() { None } else { Some(PeekMut { heap: self, sift: true }) }
@@ -422,8 +422,7 @@ impl<T: Ord> BinaryHeap<T> {
     ///
     /// # Time complexity
     ///
-    /// The worst case cost of `pop` on a heap containing *n* elements is O(log
-    /// n).
+    /// The worst case cost of `pop` on a heap containing *n* elements is `O(log(n))`.
     #[stable(feature = "rust1", since = "1.0.0")]
     pub fn pop(&mut self) -> Option<T> {
         self.data.pop().map(|mut item| {
@@ -456,15 +455,15 @@ impl<T: Ord> BinaryHeap<T> {
     ///
     /// The expected cost of `push`, averaged over every possible ordering of
     /// the elements being pushed, and over a sufficiently large number of
-    /// pushes, is O(1). This is the most meaningful cost metric when pushing
+    /// pushes, is `O(1)`. This is the most meaningful cost metric when pushing
     /// elements that are *not* already in any sorted pattern.
     ///
     /// The time complexity degrades if elements are pushed in predominantly
     /// ascending order. In the worst case, elements are pushed in ascending
-    /// sorted order and the amortized cost per push is O(log n) against a heap
+    /// sorted order and the amortized cost per push is `O(log(n))` against a heap
     /// containing *n* elements.
     ///
-    /// The worst case cost of a *single* call to `push` is O(n). The worst case
+    /// The worst case cost of a *single* call to `push` is `O(n)`. The worst case
     /// occurs when capacity is exhausted and needs a resize. The resize cost
     /// has been amortized in the previous figures.
     #[stable(feature = "rust1", since = "1.0.0")]
@@ -644,7 +643,7 @@ impl<T: Ord> BinaryHeap<T> {
     /// The remaining elements will be removed on drop in heap order.
     ///
     /// Note:
-    /// * `.drain_sorted()` is O(n lg n); much slower than `.drain()`.
+    /// * `.drain_sorted()` is `O(n * lg(n))`; much slower than `.drain()`.
     ///   You should use the latter for most cases.
     ///
     /// # Examples
@@ -729,7 +728,7 @@ impl<T> BinaryHeap<T> {
     ///
     /// # Time complexity
     ///
-    /// Cost is O(1) in the worst case.
+    /// Cost is `O(1)` in the worst case.
     #[stable(feature = "rust1", since = "1.0.0")]
     pub fn peek(&self) -> Option<&T> {
         self.data.get(0)

src/liballoc/collections/btree/map.rs

@@ -40,7 +40,7 @@ use UnderflowResult::*;
 /// performance on *small* nodes of elements which are cheap to compare. However in the future we
 /// would like to further explore choosing the optimal search strategy based on the choice of B,
 /// and possibly other factors. Using linear search, searching for a random element is expected
-/// to take O(B log<sub>B</sub>n) comparisons, which is generally worse than a BST. In practice,
+/// to take O(B * log<sub>B</sub>(n)) comparisons, which is generally worse than a BST. In practice,
 /// however, performance is excellent.
 ///
 /// It is a logic error for a key to be modified in such a way that the key's ordering relative to

src/liballoc/collections/linked_list.rs

@@ -390,7 +390,7 @@ impl<T> LinkedList<T> {
     /// This reuses all the nodes from `other` and moves them into `self`. After
     /// this operation, `other` becomes empty.
     ///
-    /// This operation should compute in O(1) time and O(1) memory.
+    /// This operation should compute in `O(1)` time and `O(1)` memory.
     ///
     /// # Examples
     ///
@@ -547,7 +547,7 @@ impl<T> LinkedList<T> {
 
     /// Returns `true` if the `LinkedList` is empty.
     ///
-    /// This operation should compute in O(1) time.
+    /// This operation should compute in `O(1)` time.
     ///
     /// # Examples
     ///
@@ -568,7 +568,7 @@ impl<T> LinkedList<T> {
 
     /// Returns the length of the `LinkedList`.
     ///
-    /// This operation should compute in O(1) time.
+    /// This operation should compute in `O(1)` time.
     ///
     /// # Examples
     ///
@@ -594,7 +594,7 @@ impl<T> LinkedList<T> {
 
     /// Removes all elements from the `LinkedList`.
     ///
-    /// This operation should compute in O(n) time.
+    /// This operation should compute in `O(n)` time.
     ///
     /// # Examples
     ///
@@ -737,7 +737,7 @@ impl<T> LinkedList<T> {
 
     /// Adds an element first in the list.
     ///
-    /// This operation should compute in O(1) time.
+    /// This operation should compute in `O(1)` time.
     ///
     /// # Examples
     ///
@@ -760,7 +760,7 @@ impl<T> LinkedList<T> {
     /// Removes the first element and returns it, or `None` if the list is
     /// empty.
     ///
-    /// This operation should compute in O(1) time.
+    /// This operation should compute in `O(1)` time.
     ///
     /// # Examples
     ///
@@ -783,7 +783,7 @@ impl<T> LinkedList<T> {
 
     /// Appends an element to the back of a list.
     ///
-    /// This operation should compute in O(1) time.
+    /// This operation should compute in `O(1)` time.
     ///
     /// # Examples
     ///
@@ -803,7 +803,7 @@ impl<T> LinkedList<T> {
     /// Removes the last element from a list and returns it, or `None` if
     /// it is empty.
     ///
-    /// This operation should compute in O(1) time.
+    /// This operation should compute in `O(1)` time.
     ///
     /// # Examples
     ///
@@ -824,7 +824,7 @@ impl<T> LinkedList<T> {
     /// Splits the list into two at the given index. Returns everything after the given index,
     /// including the index.
     ///
-    /// This operation should compute in O(n) time.
+    /// This operation should compute in `O(n)` time.
     ///
     /// # Panics
     ///
@@ -880,7 +880,7 @@ impl<T> LinkedList<T> {
 
     /// Removes the element at the given index and returns it.
     ///
-    /// This operation should compute in O(n) time.
+    /// This operation should compute in `O(n)` time.
     ///
     /// # Panics
     /// Panics if at >= len

src/liballoc/collections/vec_deque.rs

@@ -1391,7 +1391,7 @@ impl<T> VecDeque<T> {
     /// Removes an element from anywhere in the `VecDeque` and returns it,
     /// replacing it with the first element.
     ///
-    /// This does not preserve ordering, but is O(1).
+    /// This does not preserve ordering, but is `O(1)`.
     ///
     /// Returns `None` if `index` is out of bounds.
     ///
@@ -1426,7 +1426,7 @@ impl<T> VecDeque<T> {
     /// Removes an element from anywhere in the `VecDeque` and returns it, replacing it with the
     /// last element.
     ///
-    /// This does not preserve ordering, but is O(1).
+    /// This does not preserve ordering, but is `O(1)`.
     ///
     /// Returns `None` if `index` is out of bounds.
     ///
@@ -2927,7 +2927,7 @@ impl<T> From<VecDeque<T>> for Vec<T> {
     /// [`Vec<T>`]: crate::vec::Vec
     /// [`VecDeque<T>`]: crate::collections::VecDeque
     ///
-    /// This never needs to re-allocate, but does need to do O(n) data movement if
+    /// This never needs to re-allocate, but does need to do `O(n)` data movement if
     /// the circular buffer doesn't happen to be at the beginning of the allocation.
     ///
     /// # Examples

src/liballoc/slice.rs

@@ -165,7 +165,7 @@ mod hack {
 impl<T> [T] {
     /// Sorts the slice.
     ///
-    /// This sort is stable (i.e., does not reorder equal elements) and `O(n log n)` worst-case.
+    /// 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.
@@ -200,7 +200,7 @@ impl<T> [T] {
 
     /// 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.
+    /// 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
@@ -254,7 +254,7 @@ impl<T> [T] {
 
     /// Sorts the slice with a key extraction function.
     ///
-    /// This sort is stable (i.e., does not reorder equal elements) and `O(m n log n)`
+    /// This sort is stable (i.e., does not reorder equal elements) and `O(m * n * log(n))`
     /// worst-case, where the key function is `O(m)`.
     ///
     /// For expensive key functions (e.g. functions that are not simple property accesses or
@@ -297,7 +297,7 @@ impl<T> [T] {
     ///
     /// 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)`
+    /// 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
@@ -935,7 +935,7 @@ where
 /// 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.
+/// 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,

src/libcore/slice/mod.rs

@@ -1606,7 +1606,7 @@ impl<T> [T] {
     /// 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.
+    /// (i.e., does not allocate), and `O(n * log(n))` worst-case.
     ///
     /// # Current implementation
     ///
@@ -1642,7 +1642,7 @@ impl<T> [T] {
     /// 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.
+    /// (i.e., does not allocate), 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
@@ -1697,7 +1697,7 @@ impl<T> [T] {
     /// elements.
     ///
     /// This sort is unstable (i.e., may reorder equal elements), in-place
-    /// (i.e., does not allocate), and `O(m n log n)` worst-case, where the key function is
+    /// (i.e., does not allocate), and `O(m * n * log(n))` worst-case, where the key function is
     /// `O(m)`.
     ///
     /// # Current implementation
@@ -1957,7 +1957,7 @@ impl<T> [T] {
         // over all the elements, swapping as we go so that at the end
         // the elements we wish to keep are in the front, and those we
         // wish to reject are at the back. We can then split the slice.
-        // This operation is still O(n).
+        // This operation is still `O(n)`.
         //
         // Example: We start in this state, where `r` represents "next
         // read" and `w` represents "next_write`.

src/libcore/slice/sort.rs

@@ -143,7 +143,7 @@ where
     }
 }
 
-/// Sorts `v` using heapsort, which guarantees `O(n log n)` worst-case.
+/// Sorts `v` using heapsort, which guarantees `O(n * log(n))` worst-case.
 #[cold]
 pub fn heapsort<T, F>(v: &mut [T], is_less: &mut F)
 where
@@ -621,7 +621,7 @@ where
         }
 
         // If too many bad pivot choices were made, simply fall back to heapsort in order to
-        // guarantee `O(n log n)` worst-case.
+        // guarantee `O(n * log(n))` worst-case.
         if limit == 0 {
             heapsort(v, is_less);
             return;
@@ -684,7 +684,7 @@ where
     }
 }
 
-/// Sorts `v` using pattern-defeating quicksort, which is `O(n log n)` worst-case.
+/// 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,

src/libstd/collections/mod.rs

@@ -110,10 +110,10 @@
 //!
 //! For Sets, all operations have the cost of the equivalent Map operation.
 //!
-//! |              | get       | insert   | remove   | predecessor | append |
-//! |--------------|-----------|----------|----------|-------------|--------|
-//! | [`HashMap`]  | O(1)~     | O(1)~*   | O(1)~    | N/A         | N/A    |
-//! | [`BTreeMap`] | O(log n)  | O(log n) | O(log n) | O(log n)    | O(n+m) |
+//! |              | get       | insert    | remove    | predecessor | append |
+//! |--------------|-----------|-----------|-----------|-------------|--------|
+//! | [`HashMap`]  | O(1)~     | O(1)~*    | O(1)~     | N/A         | N/A    |
+//! | [`BTreeMap`] | O(log(n)) | O(log(n)) | O(log(n)) | O(log(n))   | O(n+m) |
 //!
 //! # Correct and Efficient Usage of Collections
 //!

src/libstd/ffi/mod.rs

@@ -43,8 +43,8 @@
 //! terminator, so the buffer length is really `len+1` characters.
 //! Rust strings don't have a nul terminator; their length is always
 //! stored and does not need to be calculated. While in Rust
-//! accessing a string's length is a O(1) operation (because the
-//! length is stored); in C it is an O(length) operation because the
+//! accessing a string's length is a `O(1)` operation (because the
+//! length is stored); in C it is an `O(length)` operation because the
 //! length needs to be computed by scanning the string for the nul
 //! terminator.
 //!