update 146

fishercoder1534 · fishercoder1534 · commit 592320c114ee · 2024-06-07T17:17:16.000-07:00
diff --git a/src/main/java/com/fishercoder/solutions/_146.java b/src/main/java/com/fishercoder/solutions/_146.java
@@ -4,33 +4,6 @@
 import java.util.LinkedHashMap;
 import java.util.Map;
 
-/**
- * 146. LRU Cache
- * <p>
- * Design and implement a data structure for Least Recently Used (LRU) cache. It should support the following operations: get and put.
- * <p>
- * get(key) - Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1.
- * put(key, value) - Set or insert the value if the key is not already present.
- * When the cache reached its capacity, it should invalidate the least recently used item before inserting a new item.
- * <p>
- * Follow up:
- * Could you do both operations in O(1) time complexity?
- * <p>
- * Example:
- * <p>
- * LRUCache cache = new LRUCache(2);//capacity
- * <p>
- * cache.put(1, 1);
- * cache.put(2, 2);
- * cache.get(1);       // returns 1
- * cache.put(3, 3);    // evicts key 2
- * cache.get(2);       // returns -1 (not found)
- * cache.put(4, 4);    // evicts key 1
- * cache.get(1);       // returns -1 (not found)
- * cache.get(3);       // returns 3
- * cache.get(4);       // returns 4
- */
-
 public class _146 {
 
     public class Solution1 {
@@ -71,6 +44,8 @@ public class Solution2 {
         public class LRUCache {
             /**
              * The more verbose solution is to implement a doubly linked list yourself plus a map, i.e. LinkedHashMap.
+             * It's very straightforward to implement this, key notes here: https://docs.google.com/spreadsheets/d/1anN6L5OLhUFd1ANtqDdYY6tz2Ao2H1GESfpDiCfeWyM/edit#gid=0
+             * (search for the URL of this problem to find it.)
              */
             private class Node {
                 int key;
@@ -110,11 +85,10 @@ public LRUCache(int capacity) {
 
             public int get(int key) {
                 LRUCache.Node node = map.get(key);
-                // HashMap allows value to be null, this is superior than HashTable!
+                // HashMap allows value to be null, this is superior to HashTable!
                 if (node == null) {
                     return -1;
                 } else {
-
                     /**Do two operations: this makes the process more clear:
                      * remove the old node first, and then
                      * just add the node again.
