Update: I forgot that I did a brief analysis on this many years ago, using ROT13 as example.

Update: Noam Postavsky pointed out on #emacs that CCL is not turing-complete after all as a full simulation (as opposed to just interpreting a single line) requires an Emacs Lisp loop. This loop cannot be done in CCL itself as it doesn’t allow feeding its output back in as input. The I/O restrictions most likely put it into the weaker category of finite-state transducers.

Emacs is most famously, a re-imagination of a Lisp machine, with the Emacs Lisp byte-code interpreter being at its core. A lesser-known fact is that there’s two more byte-code interpreters in its C sources, one for compiled regular expressions and another designed for encoding and decoding text, known as Code Conversion Language (CCL). This blog post will focus on the latter as it’s largely gone unnoticed and hasn’t seen too much experimentation.

The CCL implementation is split into the byte-code interpreter ( ccl.c ) and compiler ( ccl.el ) parts. There is no official documentation other than comments and docstrings found in these files. From this I’ve learned that CCL programs are represented as integer vectors and that there’s a higher-level language compiling to them, described in the ccl-define-program docstring. By reading that information I’ve deduced the following:

The VM has eight integer-sized registers r0 to r7 and an instruction counter ic

to and an instruction counter Register r7 is used as a status register and may be clobbered at any time by an arithmetic operation

is used as a status register and may be clobbered at any time by an arithmetic operation A CCL program can either be run on a string and return a string, alternatively it can be run standalone for side effects

The former mode requires you to provide a nine-element status vector representing the registers and instruction counter, the latter an eight-element status vector representing the registers only

As a side-effect, the status vector contains the new state of the registers and instruction counter after executing the program

The VM supports the standard C arithmetic, comparison and assignment operators

The language translates several control flow statements to equivalent goto statements, such as if , branch (look-up table) and loop with repeat inside

statements, such as , (look-up table) and with inside Statements are grouped by surrounding them with parentheses

When operating on a string, they are read in and written out in a serial fashion, no random access whatsoever

It’s possible to do a look-up on an array, translation table or hash table

There is a call operator, but no stack to save/restore arguments to/from, so you’ll have to come up with a calling convention fitting the available registers

operator, but no stack to save/restore arguments to/from, so you’ll have to come up with a calling convention fitting the available registers Each CCL program specifies a magnification factor which determines the ratio between output and input string size

Armed with that knowledge I wrote some boiler plate code for experimentation:

;; -*- lexical-binding: t; -*- ( require 'ccl ) ( defvar ccl-status ( make-vector 8 0 )) ( defvar ccl-status+ic ( make-vector 9 0 )) ( defun ccl-init-status ( status args ) ( let (( i 0 )) ( fillarray status 0 ) ( dolist ( arg args ) ( aset status i arg ) ( setq i ( 1+ i ))))) ( defun ccl-run ( program string &rest args ) ( let (( status ccl-status+ic )) ( ccl-init-status status args ) ( ccl-execute-on-string program status string ))) ( defun ccl-run-pure ( program &rest args ) ( let (( status ccl-status )) ( ccl-init-status status args ) ( ccl-execute program status ) status ))

There will be some benchmark numbers, none of these are to be taken seriously. Do your own benchmarks before using mine for decisions.

Hello World! For starters I’ll focus on processing strings. The easiest possible program that still does something useful reads in output and writes it out as is: ( define-ccl-program ccl-identity ' ( 1 ( loop ( read r0 ) ( write r0 ) ( repeat )))) ( ccl-run 'ccl-identity "Hello World!" ) ;=> "Hello World!" Let’s go through that program carefully. The S-Expression starts with a magnification factor of 1, meaning that the output buffer should be as large as the input buffer. If it were zero, no I/O would be permitted in the first place, whereas a factor greater than one would allocate enough space to produce a string larger than the input. The magnification factor is followed by a s-expression that’s executed until it’s done or an error occurred, such as there being no more input. It may be followed by another s-expression that’s executed after the main one, no matter whether it failed with an error or not. ccl-identity uses a pattern that will come up a few more times in this blog post. It enters a loop, reads a character into the r0 register, writes out a character from the r0 register and jumps to the beginning of the loop. If there are no more characters left, the read operation fails and terminates the loop. Let’s spice things up by adding an extra processing step before writing out the character: ( define-ccl-program ccl-xor ' ( 1 ( loop ( read r1 ) ( r1 ^= r0 ) ( write r1 ) ( repeat )))) ( ccl-run 'ccl-xor "Secret" 42 ) ;=> "yOIXO^" ( ccl-run 'ccl-xor "yOIXO^" 42 ) ;=> "Secret" XOR is the bread and butter operator in modern cryptography. A text can be encrypted by replacing each character with the result of XORing it against a secret byte, similarly it can be decrypted by applying the same transformation again. To pass the secret byte as an argument, I’ve placed it in the r0 register and read the string into the r1 register instead. On each iteration of the loop r1 is set to r1 ^ r0 and written out again.

More on translation In the real world translating characters isn’t as simple as applying some arithmetic to them. Suppose I wanted to challenge the upcase built-in: ( define-ccl-program ccl-upcase ' ( 1 ( loop ( read r0 ) ( if ( r0 >= ?a ) ( if ( r0 <= ?z ) ( r0 -= 32 ))) ( write r0 ) ( repeat )))) The processing step is a bit more involved this time. If the read-in character appears to be between the a and z characters, transform it by subtracting 32. Why 32? Take a look at an ASCII table and you’ll see that this is the distance between uppercase and lowercase letters. Unfortunately this implementation cannot challenge upcase as it fails to translate non-ASCII characters correctly and is slower than the real deal: ( ccl-run 'ccl-upcase "Hello World!" ) ;=> "HELLO WORLD!" ( ccl-run 'ccl-upcase "Mötley Crüe" ) ;=> "MöTLEY CRüE" ( benchmark 100000 ' ( ccl-run 'ccl-upcase "Hello World!" )) ;; => "Elapsed time: 0.165250s (0.072059s in 1 GCs)" ( benchmark 100000 ' ( upcase "Hello World!" )) ;; => "Elapsed time: 0.119050s (0.072329s in 1 GCs)" Let’s try again with a different text transformation where I actually have a chance to win, ROT13: ( define-ccl-program ccl-rot13 ' ( 1 ( loop ( read r0 ) ( if ( r0 >= ?a ) ( if ( r0 <= ?z ) (( r0 -= ?a ) ( r0 += 13 ) ( r0 %= 26 ) ( r0 += ?a )))) ( if ( r0 >= ?A ) ( if ( r0 <= ?Z ) (( r0 -= ?A ) ( r0 += 13 ) ( r0 %= 26 ) ( r0 += ?A )))) ( write r0 ) ( repeat )))) This time the program needs to recognize two different character ranges to process, lowercase and uppercase ASCII characters. In either case they’re translated to their position in the alphabet, rotated by 13, then translated back to ASCII again. Surprisingly enough, this is enough to beat both rot13-string and rot13-region : ( ccl-run 'ccl-rot13 "Hello World!" ) ;=> "Uryyb Jbeyq!" ( ccl-run 'ccl-rot13 ( ccl-run 'ccl-rot13 "Hello World!" )) ;; => "Hello World!" ( benchmark 100000 ' ( ccl-run 'ccl-rot13 "Hello World!" )) ;; => "Elapsed time: 0.248791s (0.072622s in 1 GCs)" ( benchmark 100000 ' ( rot13-string "Hello World!" )) ;; => "Elapsed time: 6.108861s (2.360862s in 32 GCs)" ( with-temp-buffer ( insert "Hello World!" ) ( benchmark 100000 ' ( rot13-region ( point-min ) ( point-max )))) ;; => "Elapsed time: 1.489205s (1.017631s in 14 GCs)" I then tried to use translation tables for a final example of a “Vaporwave” converter, but failed. Funnily enough this mirrors my overall experience with Emacs, it’s easy to write fun things, but the moment one tries to write something useful, you discover it’s not fun and sometimes not even up to the task. At least it’s possible to salvage the translation tables and use them with translate-region instead, the built-in used by rot13-string and rot13-region : ( defvar ccl-vaporwave-table ( make-translation-table-from-alist ( cons ' ( ?\s . 12288 ) ( mapcar ( lambda ( i ) ( cons i ( + i 65248 ))) ( number-sequence 33 126 ))))) ( defun vaporwave-it ( string ) ( with-temp-buffer ( insert string ) ( translate-region ( point-min ) ( point-max ) ccl-vaporwave-table ) ( buffer-string ))) ( vaporwave-it ( upcase "aesthetic" )) ;=> "ＡＥＳＴＨＥＴＩＣ"

Edging towards general-purpose computing All examples so far have worked on text. If you limit yourself to numbers, you can solve some basic arithmetic problems. Here’s a classic, calculating the factorial of a number: ( define-ccl-program ccl-factorial ' ( 0 (( r1 = 1 ) ( loop ( if r0 (( r1 *= r0 ) ( r0 -= 1 ) ( repeat ))))))) ( defun factorial ( n ) ( let (( acc 1 )) ( while ( not ( zerop n )) ( setq acc ( * acc n )) ( setq n ( 1- n ))) acc )) While the regular version is more concise, the logic is nearly the same in both. Here’s some numbers: ( aref ( ccl-run-pure 'ccl-factorial 10 ) 1 ) ;=> 3628800 ( factorial 10 ) ;=> 3628800 ( benchmark 100000 ' ( ccl-run-pure 'ccl-factorial 10 )) ;; => "Elapsed time: 0.069063s" ( benchmark 100000 ' ( factorial 10 )) ;; => "Elapsed time: 0.080212s" This isn’t nearly as much of a speed-up as I’ve hoped for. Perhaps CCL pays off more when doing arithmetic than for looping? Another explanation is that the Emacs Lisp byte-code compiler has an edge over CCL’s rather simple one. Here’s a more entertaining example, printing out the lyrics of 99 Bottles of Beer on the Wall: ( define-ccl-program ccl-print-bottle-count ' ( 1 ( if ( r0 < 10 ) ( write ( r0 + ?0 )) (( write (( r0 / 10 ) + ?0 )) ( write (( r0 % 10 ) + ?0 )))))) ( define-ccl-program ccl-99-bottles ' ( 1 ( loop ( if ( r0 > 2 ) (( call ccl-print-bottle-count ) ( write " bottles of beer on the wall, " ) ( call ccl-print-bottle-count ) ( write " bottles of beer.

" ) ( write "Take one down and pass it around, " ) ( r0 -= 1 ) ( call ccl-print-bottle-count ) ( write " bottles of beer on the wall.



" ) ( repeat )) (( write "2 bottles of beer on the wall, 2 bottles of beer.

" ) ( write "Take one down and pass it around, 1 bottle of beer on the wall.



" ) ( write "1 bottle of beer on the wall, 1 bottle of beer.

" ) ( write "Take one down and pass it around, no more bottles of beer on the wall.



" ) ( write "No more bottles of beer on the wall, no more bottles of beer.

" ) ( write "Go to the store and buy some more, 99 bottles of beer on the wall.

" )))))) ( defun 99-bottles () ( with-output-to-string ( let (( i 99 )) ( while ( > i 2 ) ( princ ( format "%d bottles of beer on the wall, %d bottles of beer.

" i i )) ( princ ( format "Take one down and pass it around, %d bottles of beer on the wall.



" ( 1- i ))) ( setq i ( - i 1 )))) ( princ "2 bottles of beer on the wall, 2 bottles of beer.

" ) ( princ "Take one down and pass it around, 1 bottle of beer on the wall.



" ) ( princ "1 bottle of beer on the wall, 1 bottle of beer.

" ) ( princ "Take one down and pass it around, no more bottles of beer.



" ) ( princ "No more bottles of beer on the wall, no more bottles of beer.

" ) ( princ "Go to the store and buy some more, 99 bottles of beer on the wall.

" ))) This example shows a few more interesting things, generating text of unknown length is rather hard, so I’m using the standard magnification factor of 1 and estimate how big the buffer will be to create an appropriately sized input string. call is useful to not repeat yourself, at the cost of having to carefully plan register usage. Printing out the bottle count can be done if you’re limiting yourself to whole numbers up to 100, a generic solution is going to be hard without random access to the output string. The performance numbers for this one are somewhat surprising: ( let (( input ( make-string 15000 ?\s ))) ( benchmark 1000 ' ( ccl-run 'ccl-99-bottles input 99 ))) ;; => "Elapsed time: 0.301170s (0.217804s in 3 GCs)" ( benchmark 1000 ' ( my-99-bottles )) ;; => "Elapsed time: 1.735386s (0.507231s in 7 GCs)" This doesn’t make much sense. Is using format that expensive? It’s hard to tell in advance whether CCL will make a noticable difference or not.

But is it Turing-complete? My experimentation so far left me wondering, is this language turing-complete? You can perform arithmetics, there’s goto , but the I/O facilities, amount of registers and memory access are limited. The easiest way of proving this property is by implementing another known turing-complete system on top of your current one. I researched a bit and found the following candidates: Brainfuck: A classic, however it requires writable memory. Registers could be used for this, but you don’t have many to play with. You’d need the branch instruction to simulate the data pointer.

instruction to simulate the data pointer. subleq: Implementing subleq looks easy, but suffers from the same problem as Brainfuck, it requires you to modify an arbitrary memory location. I’ve found a compiler from a C subset to subleq that generates code operating beyond the handful of registers, so that’s not an option either.

looks easy, but suffers from the same problem as Brainfuck, it requires you to modify an arbitrary memory location. I’ve found a compiler from a C subset to that generates code operating beyond the handful of registers, so that’s not an option either. Rule 110: It’s basically Game of Life, but one-dimensional and can be implemented in a serial fashion. With some tricks it doesn’t require random access either. The proof of it being turing-complete looks painful, but whatever, I don’t care. It’s perfect. There are more elementary cellular automata, so I’ll try to implement it in a generic fashion and demonstrate it on Rule 90 which produces the Sierpinski triangle. ( defmacro define-ccl-automaton ( n ) ( let (( print-sym ( intern ( format "ccl-rule%d-print" n ))) ( rule-sym ( intern ( format "ccl-rule%d" n )))) ` ( progn ( define-ccl-program , print-sym ' ( 1 (( r4 = 0 ) ( if ( r0 == ?1 ) ( r4 += 4 )) ( if ( r1 == ?1 ) ( r4 += 2 )) ( if ( r2 == ?1 ) ( r4 += 1 )) ( branch r4 ( write , ( if ( zerop ( logand n 1 )) ?0 ?1 )) ( write , ( if ( zerop ( logand n 2 )) ?0 ?1 )) ( write , ( if ( zerop ( logand n 4 )) ?0 ?1 )) ( write , ( if ( zerop ( logand n 8 )) ?0 ?1 )) ( write , ( if ( zerop ( logand n 16 )) ?0 ?1 )) ( write , ( if ( zerop ( logand n 32 )) ?0 ?1 )) ( write , ( if ( zerop ( logand n 64 )) ?0 ?1 )) ( write , ( if ( zerop ( logand n 128 )) ?0 ?1 )))))) ( define-ccl-program , rule-sym ' ( 1 (( r6 = , n ) ( r0 = 0 ) ( read r1 ) ( read r2 ) ( loop ( call , print-sym ) ( read r3 ) ( r0 = r1 ) ( r1 = r2 ) ( r2 = r3 ) ( repeat ))) (( r0 = r1 ) ( r1 = r2 ) ( r2 = r5 ) ( call , print-sym ))))))) ( define-ccl-automaton 30 ) ( define-ccl-automaton 90 ) ( define-ccl-automaton 110 ) ( defun ccl-sierpinski () ( with-output-to-string ( let (( line "0000000001000000000" )) ( dotimes ( _ 20 ) ( princ line ) ( terpri ) ( setq line ( ccl-run 'ccl-rule90 line )))))) The macro may look scary, but all it does is defining two CCL programs. What an elementary cellular automaton does is looking at the two cells around the current cell, map them to a cell depending to a rule and emit it. There are two edge cases with this for the first and last cell, in my implementation the first cell assumes the previous one was a zero and the last cell uses the first cell. Since there’s no random access, it’s stored into a spare register at the beginning and accessed in a S-Expression after the main loop terminated due to no more input. The surrounding and current cell are stored in three registers and rotated every time a new cell is read in. The mapping is done in the print program by summing up the ones and zeroes, then using the branch instruction to apply the rule to it. If you find this hard to follow, here’s an Emacs Lisp version of it using random access and less limited arithmetic to do the job: ( defun rule--evolve ( prev cur next n ) ( let (( acc ( + ( if ( = prev ?1 ) 4 0 ) ( if ( = cur ?1 ) 2 0 ) ( if ( = next ?1 ) 1 0 )))) ( if ( zerop ( logand n ( ash 1 acc ))) ?0 ?1 ))) ( defun rule-evolve ( line n ) ( let (( out ( make-string ( length line ) ?0 ))) ( dotimes ( i ( length line )) ( cond (( zerop i ) ( aset out i ( rule--evolve ?0 ( aref line i ) ( aref line ( 1+ i )) n ))) (( = i ( 1- ( length line ))) ( aset out i ( rule--evolve ( aref line ( 1- i )) ( aref line i ) ( aref line 0 ) n ))) ( t ( aset out i ( rule--evolve ( aref line ( 1- i )) ( aref line i ) ( aref line ( 1+ i )) n ))))) out )) ( defun sierpinski () ( with-output-to-string ( let (( line "0000000001000000000" )) ( dotimes ( _ 20 ) ( princ line ) ( terpri ) ( setq line ( rule-evolve line 90 )))))) One more benchmark run, this time with less surprising performance numbers: ( benchmark 1000 ' ( ccl-sierpinski )) ;; => "Elapsed time: 0.365031s (0.071827s in 1 GCs)" ( benchmark 1000 ' ( sierpinski )) ;; => "Elapsed time: 0.545512s (0.071829s in 1 GCs)" If you want to see it in action, try evaluating (progn (princ (sierpinski)) nil) in M-x ielm . Now for a big letdown, despite everything what I’ve demonstrated, this system is not turing-complete after all. While it’s capable of processing a single line of input, the proof of Rule 110 being turing-complete relies on feeding its output in as input over and over again, however that part has been done in Emacs Lisp as it’s impossible to do in CCL. I’m not 100% sure what CCL’s computing power is, Noam Postavsky suggested on #emacs that it’s most likely a finite-state transducer.