Design and implement a data structure for Least Recently Used (LRU) cache. It should support the following operations: get and set.

get(key) - Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1. set(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.

Solution

public class LRUCache {

    public class Node {
        public int key;
        public int value; 
        public Node prev;
        public Node next;
    };

    Map<Integer, Node> map;
    int cap;
    Node head, tail;


    public LRUCache(int capacity) {
        map = new HashMap<Integer, Node>();

        cap = capacity;

        head = new Node();
        tail = new Node();

        head.prev = null;
        head.next = tail;
        tail.prev = head;
        tail.next = null;
    }

    public int get(int key) {
        if(map.containsKey(key)) {
            Node node = map.get(key);
            deleteNode(node);
            insertToHead(node);

            return map.get(key).value;
        }
        else return -1;
    }

    public void deleteNode(Node node) {
        node.prev.next = node.next;
        node.next.prev = node.prev;
    }

    public void insertToHead(Node node) {
        node.next = head.next;
        head.next.prev = node;

        head.next = node;
        node.prev = head;
    }

    public void set(int key, int value) {
        if(map.containsKey(key)) {
            Node node = map.get(key);
            node.value = value;
            deleteNode(node);
            insertToHead(node);
        } else {
            Node newNode = new Node();
            newNode.key = key;
            newNode.value = value;
            map.put(key, newNode);
            insertToHead(newNode);
            if(map.keySet().size() > cap) {
                map.remove(tail.prev.key);
                deleteNode(tail.prev);
            }
        }
    }
}