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Enhance docs, add more tests in LRUCache
(#5950)
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@ -4,15 +4,40 @@ import java.util.HashMap;
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import java.util.Map;
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/**
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* Least recently used (LRU)
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* <p>
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* Discards the least recently used items first. This algorithm requires keeping
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* track of what was used when, which is expensive if one wants to make sure the
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* algorithm always discards the least recently used item.
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* https://en.wikipedia.org/wiki/Cache_replacement_policies#Least_recently_used_(LRU)
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* A Least Recently Used (LRU) Cache implementation.
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*
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* @param <K> key type
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* @param <V> value type
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* <p>An LRU cache is a fixed-size cache that maintains items in order of use. When the cache reaches
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* its capacity and a new item needs to be added, it removes the least recently used item first.
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* This implementation provides O(1) time complexity for both get and put operations.</p>
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*
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* <p>Features:</p>
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* <ul>
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* <li>Fixed-size cache with configurable capacity</li>
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* <li>Constant time O(1) operations for get and put</li>
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* <li>Thread-unsafe - should be externally synchronized if used in concurrent environments</li>
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* <li>Supports null values but not null keys</li>
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* </ul>
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*
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* <p>Implementation Details:</p>
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* <ul>
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* <li>Uses a HashMap for O(1) key-value lookups</li>
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* <li>Maintains a doubly-linked list for tracking access order</li>
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* <li>The head of the list contains the least recently used item</li>
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* <li>The tail of the list contains the most recently used item</li>
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* </ul>
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*
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* <p>Example usage:</p>
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* <pre>
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* LRUCache<String, Integer> cache = new LRUCache<>(3); // Create cache with capacity 3
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* cache.put("A", 1); // Cache: A=1
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* cache.put("B", 2); // Cache: A=1, B=2
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* cache.put("C", 3); // Cache: A=1, B=2, C=3
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* cache.get("A"); // Cache: B=2, C=3, A=1 (A moved to end)
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* cache.put("D", 4); // Cache: C=3, A=1, D=4 (B evicted)
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* </pre>
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*
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* @param <K> the type of keys maintained by this cache
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* @param <V> the type of mapped values
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*/
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public class LRUCache<K, V> {
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@ -30,6 +55,11 @@ public class LRUCache<K, V> {
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setCapacity(cap);
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}
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/**
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* Returns the current capacity of the cache.
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*
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* @param newCapacity the new capacity of the cache
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*/
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private void setCapacity(int newCapacity) {
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checkCapacity(newCapacity);
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for (int i = data.size(); i > newCapacity; i--) {
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@ -39,6 +69,11 @@ public class LRUCache<K, V> {
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this.cap = newCapacity;
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}
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/**
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* Evicts the least recently used item from the cache.
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*
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* @return the evicted entry
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*/
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private Entry<K, V> evict() {
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if (head == null) {
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throw new RuntimeException("cache cannot be empty!");
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@ -50,12 +85,25 @@ public class LRUCache<K, V> {
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return evicted;
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}
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/**
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* Checks if the capacity is valid.
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*
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* @param capacity the capacity to check
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*/
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private void checkCapacity(int capacity) {
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if (capacity <= 0) {
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throw new RuntimeException("capacity must greater than 0!");
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}
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}
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/**
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* Returns the value to which the specified key is mapped, or null if this cache contains no
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* mapping for the key.
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*
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* @param key the key whose associated value is to be returned
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* @return the value to which the specified key is mapped, or null if this cache contains no
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* mapping for the key
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*/
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public V get(K key) {
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if (!data.containsKey(key)) {
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return null;
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@ -65,6 +113,11 @@ public class LRUCache<K, V> {
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return entry.getValue();
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}
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/**
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* Moves the specified entry to the end of the list.
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*
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* @param entry the entry to move
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*/
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private void moveNodeToLast(Entry<K, V> entry) {
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if (tail == entry) {
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return;
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@ -86,6 +139,12 @@ public class LRUCache<K, V> {
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tail = entry;
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}
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/**
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* Associates the specified value with the specified key in this cache.
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*
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* @param key the key with which the specified value is to be associated
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* @param value the value to be associated with the specified key
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*/
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public void put(K key, V value) {
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if (data.containsKey(key)) {
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final Entry<K, V> existingEntry = data.get(key);
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@ -107,6 +166,11 @@ public class LRUCache<K, V> {
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data.put(key, newEntry);
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}
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/**
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* Adds a new entry to the end of the list.
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*
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* @param newEntry the entry to add
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*/
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private void addNewEntry(Entry<K, V> newEntry) {
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if (data.isEmpty()) {
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head = newEntry;
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