This class is not a general-purpose Map implementation! While this class implements the Map interface, it intentionally violates Map's general contract, which mandates the use of the equals method when comparing objects. This class is designed for use only in the rare cases wherein reference-equality semantics are required.

A typical use of this class is topology-preserving object graph transformations, such as serialization or deep-copying. To perform such a transformation, a program must maintain a "node table" that keeps track of all the object references that have already been processed. The node table must not equate distinct objects even if they happen to be equal. Another typical use of this class is to maintain proxy objects. For example, a debugging facility might wish to maintain a proxy object for each object in the program being debugged.

This class provides all of the optional map operations, and permits null values and the null key. This class makes no guarantees as to the order of the map; in particular, it does not guarantee that the order will remain constant over time.

This class provides constant-time performance for the basic operations (get and put), assuming the system identity hash function (System.identityHashCode(Object)) disperses elements properly among the buckets.

This class has one tuning parameter (which affects performance but not semantics): expected maximum size. This parameter is the maximum number of key-value mappings that the map is expected to hold. Internally, this parameter is used to determine the number of buckets initially comprising the hash table. The precise relationship between the expected maximum size and the number of buckets is unspecified.

If the size of the map (the number of key-value mappings) sufficiently exceeds the expected maximum size, the number of buckets is increased Increasing the number of buckets ("rehashing") may be fairly expensive, so it pays to create identity hash maps with a sufficiently large expected maximum size. On the other hand, iteration over collection views requires time proportional to the number of buckets in the hash table, so it pays not to set the expected maximum size too high if you are especially concerned with iteration performance or memory usage.

Note that this implementation is not synchronized. If multiple threads access an identity hash map concurrently, and at least one of the threads modifies the map structurally, it must be synchronized externally. (A structural modification is any operation that adds or deletes one or more mappings; merely changing the value associated with a key that an instance already contains is not a structural modification.) This is typically accomplished by synchronizing on some object that naturally encapsulates the map. If no such object exists, the map should be "wrapped" using the Collections.synchronizedMap method. This is best done at creation time, to prevent accidental unsynchronized access to the map:

   Map m = Collections.synchronizedMap(new IdentityHashMap(...));

The iterators returned by the iterator method of the collections returned by all of this class's "collection view methods" are fail-fast: if the map is structurally modified at any time after the iterator is created, in any way except through the iterator's own remove method, the iterator will throw a ConcurrentModificationException. Thus, in the face of concurrent modification, the iterator fails quickly and cleanly, rather than risking arbitrary, non-deterministic behavior at an undetermined time in the future.

Note that the fail-fast behavior of an iterator cannot be guaranteed as it is, generally speaking, impossible to make any hard guarantees in the presence of unsynchronized concurrent modification. Fail-fast iterators throw ConcurrentModificationException on a best-effort basis. Therefore, it would be wrong to write a program that depended on this exception for its correctness: fail-fast iterators should be used only to detect bugs.

Implementation note: This is a simple linear-probe hash table, as described for example in texts by Sedgewick and Knuth. The array alternates holding keys and values. (This has better locality for large tables than does using separate arrays.) For many JRE implementations and operation mixes, this class will yield better performance than HashMap (which uses chaining rather than linear-probing).

This class is a member of the Java Collections Framework.