Merge pull request kdn251#51 from yangshun/fix-heap

Fix Heap time complexities

Author: kdn251

README-zh-cn.md

@@ -118,11 +118,9 @@
 ### Heap
 * 堆是一种特殊的基于树的满足某些特性的数据结构，整个堆中的所有父子节点的键值都会满足相同的排序条件。堆更准确地可以分为最大堆与最小堆，在最大堆中，父节点的键值永远大于或者等于子节点的值，并且整个堆中的最大值存储于根节点；而最小堆中，父节点的键值永远小于或者等于其子节点的键值，并且整个堆中的最小值存储于根节点。
 * 时间复杂度:
-  * 访问: `O(log(n))`
-  * 搜索: `O(log(n))`
+  * 访问最大值 / 最小值: `O(1)`
   * 插入: `O(log(n))`
-  * 移除: `O(log(n))`
-  * 移除最大值 / 最小值: `O(1)`
+  * 移除最大值 / 最小值: `O(log(n))`
 
 <img src="/Images/heap.png?raw=true" alt="Max Heap" width="400" height="500">
 

README.md

@@ -136,11 +136,9 @@ A heap can be classified further as either a "max heap" or a "min heap". In a ma
 than or equal to those of the children and the highest key is in the root node. In a min heap, the keys of parent nodes are less than
 or equal to those of the children and the lowest key is in the root node
 * Time Complexity:
- * Access: `O(log(n))`
- * Search: `O(log(n))`
+ * Access Max / Min: `O(1)`
  * Insert: `O(log(n))`
- * Remove: `O(log(n))`
- * Remove Max / Min: `O(1)`
+ * Remove Max / Min: `O(log(n))`
 
 <img src="/Images/heap.png?raw=true" alt="Max Heap" width="400" height="500">