Update BST image.

Author: trekhleb

src/data-structures/tree/binary-search-tree/README.md

@@ -3,32 +3,34 @@
 _Read this in other languages:_
 [_Português_](README.pt-BR.md)
 
-In computer science, **binary search trees** (BST), sometimes called 
-ordered or sorted binary trees, are a particular type of container: 
-data structures that store "items" (such as numbers, names etc.) 
-in memory. They allow fast lookup, addition and removal of 
-items, and can be used to implement either dynamic sets of 
-items, or lookup tables that allow finding an item by its key 
+In computer science, **binary search trees** (BST), sometimes called
+ordered or sorted binary trees, are a particular type of container:
+data structures that store "items" (such as numbers, names etc.)
+in memory. They allow fast lookup, addition and removal of
+items, and can be used to implement either dynamic sets of
+items, or lookup tables that allow finding an item by its key
 (e.g., finding the phone number of a person by name).
 
-Binary search trees keep their keys in sorted order, so that lookup 
-and other operations can use the principle of binary search: 
-when looking for a key in a tree (or a place to insert a new key), 
-they traverse the tree from root to leaf, making comparisons to 
-keys stored in the nodes of the tree and deciding, on the basis 
-of the comparison, to continue searching in the left or right 
-subtrees. On average, this means that each comparison allows 
-the operations to skip about half of the tree, so that each 
-lookup, insertion or deletion takes time proportional to the 
-logarithm of the number of items stored in the tree. This is 
-much better than the linear time required to find items by key 
-in an (unsorted) array, but slower than the corresponding 
+Binary search trees keep their keys in sorted order, so that lookup
+and other operations can use the principle of binary search:
+when looking for a key in a tree (or a place to insert a new key),
+they traverse the tree from root to leaf, making comparisons to
+keys stored in the nodes of the tree and deciding, on the basis
+of the comparison, to continue searching in the left or right
+subtrees. On average, this means that each comparison allows
+the operations to skip about half of the tree, so that each
+lookup, insertion or deletion takes time proportional to the
+logarithm of the number of items stored in the tree. This is
+much better than the linear time required to find items by key
+in an (unsorted) array, but slower than the corresponding
 operations on hash tables.
 
 A binary search tree of size 9 and depth 3, with 8 at the root.
 The leaves are not drawn.
 
-![Binary Search Tree](https://upload.wikimedia.org/wikipedia/commons/d/da/Binary_search_tree.svg)
+![Trie](./images/binary-search-tree.jpg)
+
+*Made with [okso.app](https://okso.app)*
 
 ## Pseudocode for Basic Operations
 
@@ -45,7 +47,7 @@ insert(value)
   end if
 end insert
 ```
-    
+
 ```text
 insertNode(current, value)
   Pre: current is the node to start from
@@ -84,8 +86,8 @@ contains(root, value)
   end if
 end contains
 ```
-    
-     
+
+
 ### Deletion
 
 ```text
@@ -186,7 +188,7 @@ findNode(root, value)
   end if
 end findNode
 ```
-    
+
 ### Find Minimum
 
 ```text
@@ -200,7 +202,7 @@ findMin(root)
   findMin(root.left)
 end findMin
 ```
-    
+
 ### Find Maximum
 
 ```text
@@ -214,7 +216,7 @@ findMax(root)
   findMax(root.right)
 end findMax
 ```
-    
+
 ### Traversal
 
 #### InOrder Traversal
@@ -244,7 +246,7 @@ preorder(root)
   end if
 end preorder
 ```
-   
+
 #### PostOrder Traversal
 
 ```text
@@ -258,7 +260,7 @@ postorder(root)
   end if
 end postorder
 ```
-     
+
 ## Complexities
 
 ### Time Complexity

src/data-structures/tree/binary-search-tree/README.pt-BR.md

@@ -26,8 +26,9 @@ Uma pesquisa de árvore binária de tamanho 9 e profundidade 3, com valor 8
 na raíz.
 As folhas não foram desenhadas.
 
+![Trie](./images/binary-search-tree.jpg)
 
-![Binary Search Tree](https://upload.wikimedia.org/wikipedia/commons/d/da/Binary_search_tree.svg)
+*Made with [okso.app](https://okso.app)*
 
 ## Pseudocódigo para Operações Básicas
 
@@ -44,7 +45,7 @@ insert(value)
   end if
 end insert
 ```
-    
+
 ```text
 insertNode(current, value)
   Pre: current is the node to start from
@@ -83,8 +84,8 @@ contains(root, value)
   end if
 end contains
 ```
-    
-     
+
+
 ### Remoção
 
 ```text
@@ -185,7 +186,7 @@ findNode(root, value)
   end if
 end findNode
 ```
-    
+
 ### Encontrar Mínimo
 
 ```text
@@ -199,7 +200,7 @@ findMin(root)
   findMin(root.left)
 end findMin
 ```
-    
+
 ### Encontrar Máximo
 
 ```text
@@ -213,7 +214,7 @@ findMax(root)
   findMax(root.right)
 end findMax
 ```
-    
+
 ### Traversal
 
 #### Na Ordem Traversal (InOrder Traversal)
@@ -243,7 +244,7 @@ preorder(root)
   end if
 end preorder
 ```
-   
+
 #### Pós Ordem Traversal (PostOrder Traversal)
 
 ```text
@@ -257,7 +258,7 @@ postorder(root)
   end if
 end postorder
 ```
-     
+
 ## Complexidades
 
 ### Complexidade de Tempo