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The foma FST compiler

The foma compiler is essentially a tool for converting regular expressions to finite automata and transducers. It supports a variety of operations (many more than are found in search-regex formalisms such as the Python re module). The interface also includes tools for performing various tests on automata and transducers, passing words through transducers (doing translations), and importing and exporting transducers in various formats.

The foma program runs with a read-eval-print loop (REPL), like IPython/Jupyter. That means that each command given is executed and the output is printed, and a new prompt is displayed. You can run scripts of commands by either launching foma with the foma -l flag, or by typing source filename inside foma.

Foma basics

When you start foma, it should respond with a title page, something like:

Foma, version 0.9.18alpha
Type "help" to list all commands available.
Type "help <topic>" or help "<operator>" for further help.

If you type help at the prompt, you'll be given a long terse list of help topics. This tutorial is intended to alleviate the learning curve with foma.

Compiling regular expressions

There are two commands def and regex that invoke the regular expression compiler. Saying


simply compiles the regular expression into an automaton/transducer and gives you the result. For example

regex a|b|c|d ;

would compile the regular expression in question and return the following:

371 bytes. 2 states, 4 arcs, 4 paths.

The result says that the (minimal) finite-state machine that corresponds to the regex has 2 states, 4 arcs, and that there are 4 valid paths through it. This result gets stored on an internal stack, which is what the number inside the prompt foma[1]: refers to: you now have one finite-state machine stored on the internal stack.

The def or define command has the following schema:


For example, to define a regular language that contains the words cat and dog and give that language a name Animals, we could issue:

def Animals c a t | d o g ;

Note the spaces between the symbols. Those are necessary, and will be explained below. When doing a def you can subsequently use the defined label in other regular expressions, for example:

regex Animals+ ;

would now re-use your earlier definition of Animals and this regular expression is equivalent to saying:

regex [c a t | d o g]+ ;

To get an overview of what regular expressions you have defined (so called language constants), you can saying

print defined

in the foma interface.

Viewing automata/transducers: view

If you have the GraphViz tool installed, you should be able to view the result of the last issued regex by typing view. (Note that this only works on UNIXes such as Linux or OSX, not Windows). It is often very helpful to view the result of your regular expressions graphically and reason about them in two modalities.

For a simpler view of any transducer, you can type net, which gives an ASCII listing of the transitions and basic information about the last issued regex.

You can also get information about the alphabet of a transducer by the command sigma.

Basic FST testing


If you issue the command words you'll get a list of all the words accepted by an automaton. For example:

foma[0]: regex c a t | d o g ;
455 bytes. 6 states, 6 arcs, 2 paths.
foma[1]: words


With transducers, the pairs command is often useful. It prints all the input/output pairs from a transducer.

foma[0]: regex c:d a:o t:g;
407 bytes. 4 states, 3 arcs, 1 path.
foma[1]: pairs
cat	dog

upper-words and lower-words

These commands print out only the input-side or output-side sets from a transducer. Of course, since automata are treated like repeating transducers, there is no difference in behavior for automata.

foma[0]: regex c:d a:o t:g;
407 bytes. 4 states, 3 arcs, 1 path.
foma[1]: upper-words
foma[1]: lower-words

Testing automata/transducers

The down command will enter a special prompt (which you can exit with CTRL-D) and allows you to give a transducer an input, yielding the translation output:

foma[0]: regex c:d a:o t:g;
407 bytes. 4 states, 3 arcs, 1 path.
foma[1]: down
apply down> cat
apply down> dog

If the transducer doesn't accept the input, then ??? is printed.

There is a equivalent up command, which works the same way, but in the inverse direction.

Regex basics

The regular expression formalism in foma differs somewhat from standard formalisms. It inherits a regular expression syntax called Xerox regular expressions. The main differences between standard regular expressions and this formalism is given below.

Main differences

The main differences and things to look out for can be summarized as follows:

  • All regular expressions need to end in ;
  • Brackets [ and ] are used for grouping. That means that a standard regular expression (a|b)* should be written [a|b]*. There are no "character classes", so something like [a-d] must be explicitly listed in a union in foma: [a|b|c|d]
  • Parentheses, in turn, denote "optionality". So an expression such as c a t (s) would denote the two words cat and cats since whatever is inside the parentheses is "optional". This comes from linguistic usage of parentheses.
  • Multi-character symbols are used: these are strings that are themselves single symbols (see below).
  • The wildcard symbol is ?, not .. For example, the set of words that end in a can be described as ?* a
  • Apart from union |, other logical operators are allowed, such as intersection & and complement ~. Since regular languages really denote sets of strings, we can perform set operations on them. For example, the set of words that begin and end with a could be describes as a ?* & ?* a.
  • Special symbols are escaped either by placing them in quotes, e.g. "_" to talk about an underscore symbol, or by prepending with a parenthesis symbol %, for example %_
  • Transducer operations are included: the cross-product :, composition .o. and different string rewriting operators -> are commonly used.
  • 0 represents the epsilon (ε) -symbol. This is mostly used in creating transducers. For example, a transducer that accepts a as input and outputs nothing would be denoted by the regex regex a:0 ;

Multi-character symbols

Foma allows entire strings to be single atomic symbols. This means that the two regular expressions below will give a different result:

regex cat ;
regex c a t ;

Here, the first one contains the single-symbol word cat whereas the second one contains a word made out of three symbols, c, a, and t. Compile the two regular expressions, and then issue the command view to see the difference when you view it as an automaton/transducer.

Multi-character symbols are almost never used except for grammatical tags such as [Noun] or [Sg] or [Pl]. The logic is that such tags really aren't strings, but denote atomic ideas and so should be treated as single symbols. Morphological FSTs also become smaller if atomic symbols are used for tags.

Exercise 1:

Create a regular expression denoting the set that contains the words cat, dog, horse, cats, dogs, horses (i.e. six words in total). Try to not repeat the s-part in your regular expression. Use the view command to examine the resulting automaton/transducer.

Commonly used notation:

Expression Meaning
[ ] Grouping
? Wildcard
?* Zero or more of anything
a single symbol
\a any symbol except a
\C any symbol except on in the language C
.#. word edge (in rewrite rules)
[a|b] a or b
[C|.#.] C or word boundary
a* zero or more as
A .o. B compose A and B

Transducers: the cross-product

The cross-product operator : is the simplest way to create a transducer from a regular expression. For example:

foma[0]: regex a:b;
228 bytes. 2 states, 1 arc, 1 path.

compiles a transducer that accepts a as its input, and outputs b. (View this transducer graphically).

Note that the : binds tighter than any other operator. This means that if you want to pair up strings, you'll need to indicate grouping by parentheses. For example, to define a transducer that maps cat to dog, you should do

foma[0]: regex [c a t]:[d o g];

And not regex c a t:d o g ; , since in this case, you get a transducer that maps catog to cadog (why?).

Another example, here's a transducer that deletes the first and last letters of every input word:

foma[0]: regex ?:0 ?* ?:0;
338 bytes. 3 states, 3 arcs, Cyclic.
foma[1]: down
apply down> cats

Another example: here's a transducer that maps cat[Sg] to cat (foreshadowing some kind of crude morphological analysis). Note the escaping of the "[Sg]", which is now a single symbol.

foma[0]: regex  c a t "[Sg]":0 ;
374 bytes. 5 states, 4 arcs, 1 path.
foma[1]: up
apply up> cat

Note also that in the example, we ask (by applying up) what the input-side equivalent of output-side cat is.

Exercise 2:

Use the cross-product operation to create a transducer that maps c a t [Sg] to c a t and c a t [Pl] to c a t s and d o g [Sg] to d o g and d o g [Pl] to d o g s. Note that spaces are given here deliberately only to show that [Sg] and [Pl] should be multi-character symbols, whereas the rest should be single symbols.

Rewrite rule basics

Rewrite rules are often used when modeling morphophonology. These have the following basic format.

LHS -> RHS || LC _ RC ;

where LHS is left-hand-side, RHS is right-hand-side, LC is left-context, and RC is right-context.

A regular expression such as:

regex a -> b || c _ d ;

would create a transducer that converts all instances of a to b, but only if that a occurs between c and d.

The LC and RC are optional, so you could say:

regex a -> 0 || _ b ;

creating a transducer that deletes a-symbols when they occur before a b.

You can also drop the context altogether, and say:

regex x -> y ;

Which creates a transducer that maps all x-symbols to y, always, passing everything else through untouched.

Word boundaries in rewrite rules

The special symbol .#. is used to refer to edges of words. For example, the following transducer deletes all x-symbols, but only at the beginning of a word. Everything else is passed through as-is.

regex x -> 0 || .#. _ ;

Epenthesis (insertion) rules

There is a special type of rule, called epenthesis rules is used whenever you want to insert something (from nothing) in a special position. This is denoted by [..] as the LHS. For example:

regex [..] -> x || y _ z ;

would result in a transducer that inserts x between y and z, as seen below:

foma[1]: down
apply down> yzyz

Composition: .o.

If you have two (or more) transducers, they can be joined by composition. For example:

foma[0]: regex a -> b .o. b -> c ;
416 bytes. 1 state, 4 arcs, Cyclic.

Creates the composition of the two above transducers, mapping a directly to c. Question: what does c map to in the inverse direction (do up and then c)? Why?

Normally, individual transducers are given names with def, and then composed. For example:

foma[0]: def RuleA a -> b || c _ d;
defined RuleA: 634 bytes. 4 states, 16 arcs, Cyclic.
foma[0]: def RuleB b -> x || c _ ;
defined RuleB: 480 bytes. 2 states, 8 arcs, Cyclic.
foma[0]: regex RuleA .o. RuleB;
708 bytes. 4 states, 19 arcs, Cyclic.

Exercise 3:

First create a transducer Lexicon that does the following: maps c a t [Sg] to c a t and c a t [Pl] to c a t + s and b u s [Sg] to b u s and b u s [Pl] to b u s + s. Now that you have this, create a rewrite rule that translates all instances of + to e whenever it's surrounded by s on both sides. Def this rule to have the name EInsert. Now compose Lexicon and EInsert by issuing

regex Lexicon .o. EInsert ;

You should get a resulting transducer that maps b u s [Pl] to b u s e s and c a t [Pl] to c a t s. Now, you can create a third transducer Cleanup that always deletes all +-symbols and compose that in last.

regex Lexicon .o. EInsert .o. Cleanup ;

You should now have your first complete morphological toy grammar. Test it with up and the word buses and cats.

Common mistakes

  • Not separating symbols by spaces; writing regex cat|dog; instead of regex c a t | d o g;.
  • Forgetting the semicolon at the end of a regular expressions.
  • Not keeping track of binding: see help precedence in foma to see which operators bind in what order.