LRU Cache

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.

效率低了一点

import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;

public class LRUCache {
    List<Element> cache = new ArrayList<Element>();
    int capacity;
    HashMap<Integer, Boolean> isInCache = new HashMap<Integer, Boolean>();            //key是否in cache
    
    public LRUCache(int capacity) {
        this.capacity = capacity;
    }
    
    public int get(int key) {
        boolean isKeyInCache = false;
        int indexOfKey = -1;
        int value = -1;
        Element element = null;
        //查找cache中是否有key
        if(isInCache.get(key) != null)
            for(int i = 0; i < cache.size(); i++){
                element = cache.get(i);
                if(element.key == key){                                //cache中有key
                    value = element.value;
                    isKeyInCache = true;
                    indexOfKey = i;
                    break;
                }//if
            }//for
        
        if(isKeyInCache == true){                                //cache中有key
            cache.remove(indexOfKey);
            cache.add(0, element);                                //更新key在cache中的位置
        }//if
        
        return value;
    }
    
    public void set(int key, int value) {
        int valueOfCache = -1;
        if((valueOfCache = get(key)) == -1){                                        //在cache中不存在
            if(cache.size() < capacity)                                //cache没有满,在0号位置添加
                cache.add(0, new Element(key, value));
            else{    
                isInCache.remove(cache.get(capacity - 1).key);        //移除在hash表中的数据
                cache.remove(capacity - 1);                            //cache满了,移除最后一个,在0位置添加                
                cache.add(0, new Element(key, value));
            }
        }else{                                                    //如果在cache中存在
            if(valueOfCache != value){                            //更新cache的值
                cache.remove(0);
                cache.add(0, new Element(key, value));
            }
        }
        
        isInCache.put(key, true);
    }
}
/**
 * cache中的元素
 * @author Administrator
 *
 */
class Element{
    int key;
    int value;
    
    public Element(int key, int value){
        this.key = key;
        this.value = value;
    }
}