opcode directly as an index. For instructions where the individual operations are simple, such as "push" and "add", the overhead involved in deciding what to execute is larger than the cost of actually executing it, so such interpreters are often much slower than machine code. However, for more complex ("compound") instructions, the overhead percentage is proportionally less significant. There are times when token-threaded code can sometimes run faster than the equivalent machine code when that machine code ends up being too large to fit in the physical CPU's L1 instruction cache. The higher code density of threaded code, especially token-threaded code, can allow it to fit entirely in the L1 cache when it otherwise would not have, thereby avoiding cache thrashing. However, threaded code consumes both instruction cache (for the implementation of each operation) as well as data cache (for the bytecode and tables) unlike machine code which only consumes instruction cache; this means threaded code will eat into the budget for the amount of data that can be held for processing by the CPU at any given time. In any case, if the problem being computed involves applying a large number of operations to a small amount of data then using threaded code may be an ideal optimization. Huffman threading Huffman threaded code consists of lists of tokens stored as Huffman codes. A Huffman code is a variable-length string of bits that identifies a unique token. A Huffman-threaded interpreter locates subroutines using an index table or a tree of pointers that can be navigated by the Huffman code. Huffman-threaded code is one of the most compact representations known for a computer program. The index and codes are chosen by measuring the frequency of calls to each subroutine in the code. Frequent calls are given the shortest codes. Operations with approximately equal frequencies are given codes with nearly equal bit-lengths. Most Huffman-threaded systems have been implemented as direct-threaded Forth systems, and used to pack large amounts of slow-running code into small, cheap microcontrollers. Most published uses have been in smart cards, toys, calculators, and watches. The bit-oriented tokenized code used in PBASIC can be seen as a kind of Huffman-threaded code. Lesser-used threading An example is string threading, in which operations are identified by strings, usually looked up by a hash table. This was used in Charles H. Moore's earliest Forth implementations and in the University of Illinois's experimental hardware-interpreted