Will vs Technology

Where I, William Rudenmalm, document my quixotic struggle against technology.

Push-down automatons in Rust

Push-down automatons are a formal model for representing limited computation. They are similar to finite state machines, but add a stack which is manipulated by the machine. In a traditional finite state machine the current state, and the input signal decide the next state that the machine advances to.

In a push down automaton things get more complicated, our transitions include can either push, pop or do nothing with the stack, and when considering wheter to apply a transition, in addition to the current state, and input signal we may also take into account the value at the top of the stack.

Limited models of computation are interesting not only because it allows us to better manage state complexity than full-blown turing-complete languages, they also have parallels in the world of parsing. In fact a regular expression has, atleast in theory, a matching finite state machine. What regular expressions famously cannot do is parse HTML. In a strict regular expression environment we cannot express with any sort of nesting. When we add a stack, as is the case with push-down automatons, we suddenly can.

At this point regular expressions and finite state machines are nearly ubiquitous in modern programming languages. So in order to experiment with them we need either a library or to do it ourselves. Unfortunately doing in many languages, the type system is too limited to support a general type safe implementation, and in the languages that do support it generalizing then leads to poor performance. There is one mainstream language that is an exception to this and that is Rust. So lets try building it in Rust and if we can manage to properly model everything with its type system.

From the mathematical definition of a push-down automaton we know that there are three different alphabets (essentially enums) involved, one for the values on the stack, one for the state of the machine itself and for the inputs. Of these, the stack seems the easiest to lets define what we can do with it.

enum StackOp<StackAlphabet> {

Recall, that we could do two things with the stack, popping (removing the top element) and pushing (adding a new top element). These fit neatly into a rust enum with the Push type, taking a value from the stack alphabet.

Rust doesn't have a dedicated Stack data type because vecs (implemented as a continous, resizable array list) already implement push and pop. For our purposes it would be helpful to encapsulate the logic of the stack somehow, so that we can work more easily with our StackOp type.

#[derive(Clone, Debug)]
struct PDAStack<StackAlphabet: Clone> {
    vec: Vec<StackAlphabet>,
impl <StackAlphabet: Clone> Default for PDAStack<StackAlphabet> {
    fn default() -> PDAStack<StackAlphabet>{
       PDAStack { vec: vec![] }
impl <StackAlphabet: Clone> PDAStack<StackAlphabet> {
    pub fn apply(&mut self, s: Option<StackOp<StackAlphabet>>) {
      match s {
           None => {},
           Some(StackOp::Pop) => { self.vec.pop(); },
           Some(StackOp::Push(x)) => { self.vec.push(x) }
    pub fn peek(&self) -> Option<StackAlphabet> {
       self.vec.last().map(|x| x.clone())

In the above code we implement a new struct PDAStack short for push down automaton stack, which implements the logic for handling our stack ops as well as a peek operation, getting the value at the top of the stack. It is interesting to note the repr(transparent) attributes which ask the compiler to guarantee that the struct is optimized away. Rust usually optimizes the memory layout for single-member structs into that of it's member, essentially making the struct disappear. This means our stack abstraction is zero-cost, it doesn't affect CPU or memory use at all.

Now with the stack operations defined we can try to define a type to represent the destination side of a transition. When a push-down automaton receives input it both change the internal state (like an FSM) and manipulate the stack. Lets represent this a rust struct

struct Dest<State, StackAlphabet>(Option<State>, Option<StackOp<StackAlphabet>>);

We don't need to define a StateOp because the state is either unchaned or it is changed to a particular value, in Rust we can simply model this using the Option type. Likewise, if we don't want to touch the stack we also model that as an option.

Now with the destination out of the way we need to come up with the source side of the rule. The source side is what is used to come up with the destination side of a transition, in a push-down automaton it is defined as the current state, the value at the top of the stack and the input received. In our version of the push down automaton the stack may be empty so we model the stack value using an option.

struct Source<State, StackAlphabet, InputAlphabet>(State, Option<StackAlphabet>, InputAlphabet);

Now with all the types defined we can finally define a trait (think interface but better), to represent Push-down automatons.

trait PDA {
    type State: Default + Clone;
    type InputAlphabet: Clone;
    type StackAlphabet: Clone;
    fn advance(source: Source<Self::State, Self::StackAlphabet, Self::InputAlphabet>) -> Dest<Self::State, Self::StackAlphabet>;

First we define, three assoicated types one for the stack alphabet, one for the input alphabet and one for the state alphabet. We then ask that these associated types all implment Default and Clone, that is to say we want them have a default value (e.g. 0 for numbers and false for booleans) and we want them to be clone-able, that is we to be able to copy their memory to create a new instance of them.

One thing that is important to note here is that we don't actually define any operations for instances of PDAs just a function that should be defined for the structure.

Having now defined the interface contracts for push-down automatons time has come to actually implement logic for running a push-down automaton.

struct PDARunner<T: PDA> {
    state: T::State,
    stack: Vec<T::StackAlphabet>,
impl <T: PDA> Default for PDARunner<T> {
    fn default() -> PDARunner<T> {
      PDARunner {
           state: Default::default(),
           stack: Default::default(),

We don't need anything other than a state containing members of the stack alphabet. Usually in Rust you use derive to automatically implment default, but in this case because we don't demand that the type parameter T also implmeents default, derive fails, even though a trivial implementation of Default exists.

The structure of the PDARunner wasn't all that hard but the implemation of the PDA itself is however a bit more involved.

impl <T:PDA> PDARunner<T> {
    fn update_state(&mut self, state: Option<T::State>) {
       if let Some(state) = state {
           self.state = state
    fn advance(&mut self, inp: T::InputAlphabet) {
       let source = Source::<T::State, T::StackAlphabet, T::InputAlphabet>(self.state.clone(), self.stack.peek(), inp);
       let Dest(state, stack) = T::advance(source);
    pub fn run<X: IntoIterator<Item=V>, V: Into<T::InputAlphabet>>(input: X) -> Self {
       let mut s = Self::new();
       for i in input.into_iter() {

That's a bit more code than we're used of seeing but lets go through it step by step. First we have a helper method update_state which updates the state using the passed in option, if it exists.

Then we have advance which is the core of what the push-down automaton needs to do. First it creates the source value from the top value of the stack, the input signal and the current state. Then it calls the advance function of the particular PDA that is associated with this runner. We get the result of the advance function and change the state if it needs changing, using our helper. The stack operation received is simply passed in to our stack implementation. With that the core logic for the push-down automaton is done.

Finally, on to our last function, the run function. It simply takes an iterable of things that can be turned into members of our input alphabet and advances the machine based on those.

Now to make the API more convienent we can add an alias within the PDA trait itself so we don't need to know that the PDARunner actually exists, to do this we can add the following function to the PDA trait.

trait PDA
    fn run<T: IntoIterator<Item=V>, V: Into<Self::InputAlphabet>>(input: T) -> PDARunner<Self> where Self: Sized {

Again this is mostly a repeat of the run function defined in the PDARunner, but we need to add a sized type constraint to keep the rust compiler happy.

And that's it. We can now use our code to solve a problem with a push down automaton. The problem that I'd like to solve is determining wheter or not a string containing gparenthesises is balanced or not. For instance, the string (hello (world)) is balanced while, (hello (world) is not.

To solve this problem we need a push down automaton where the inputs are left parens, right parens and other characters. The category other characters eists simply to allow us to ignore irrelevant characters. When we find a left parenthesises we push to the stack and when we find a right parenthesises we pop from the stack. Because we are only considering one type of parenthesises we only need a single type of data on the stack. Finally to keep track of when errors occur we need an OK state and a an error state.

The transitions will then look like this:

  • If we are in the error state, we ignore all everything and stay in the error state. This is what is said to be a terminal state.
  • If we receive an other character input we ignore it nothing changes. It is as if the input was never received at all, we might call it a no-op.
  • If we are stil in the OK state, receiving a left parenthesises, we push a parenthesis marker to the stack.
  • If we are in the OK state, have a parenthesis marker on the top of the stack, and receive a right parenthes, we pop a value from the stack.
  • If we are in the OK state, the stack is empty and we receive a right parenthesises, we should go to the error state.

Now when if we pass in a string of characters to our push-down automaton, we know that it's parenthesises are balanced if and only if the stack is empty and the state is OK.

To not pollute the rest of our file we can do it in its own module, using the mod syntax. In a production environment it is usually use another file, but inner modules makes it easy for us to do it all in one go.

mod balanced_parens {
    use super::{Source, Dest, PDA, StackOp};

    #[derive(Debug, Clone)]
    pub enum Stack {
    #[derive(Clone, Debug)]
    pub enum State {
    impl Default for State {
       fn default() -> State {
    #[derive(Clone, Debug)]
    pub enum Input {
    impl From<char> for Input {
       fn from(c: char) -> Input {
            match c {
               '(' => Self::LeftParens,
               ')' => Self::RightParens,
               _ => Self::Other,
    pub struct BalancedParensPDA;
    impl PDA for BalancedParensPDA {
       type State = State;
       type InputAlphabet = Input;
       type StackAlphabet = Stack;
       fn advance(src: Source<Self::State, Self::StackAlphabet, Self::InputAlphabet>) -> Dest<Self::State, Self::StackAlphabet> {
            match src {
               Source(State::Error, _, _) => Dest(None, None),
               Source(_, _, Input::Other) => Dest(None, None),
               Source(State::Ok, _, Input::LeftParens) => Dest(None, Some(StackOp::Push(Stack::Parens))),
               Source(State::Ok, Some(Stack::Parens), Input::RightParens) => Dest(None, Some(StackOp::Pop)),
               Source(State::Ok, _, Input::RightParens) => Dest(Some(State::Error), None),


First we declare the enums Stack, State and Input according to the specifications above, making sure to make the default state OK. Then we declare conversion from chracters into our input value type, making ( and ) to their corresponding input values, while all other values are mapped to Other. Then we declare our push down automaton itself with an empty struct and a implementation of the PDA trait. In the trait we set our associated types to the enums declared just before and then declare the advance method based on the rules from earlier.

We can now declare a main function outside them like this:

fn main() {
    let machine = BalancedParensPDA::run("()".chars());
    println!("{:?}", machine);

This results in the following output:

PDARunner { state: Ok, stack: PDAStack { vec: [] } }

The state is OK and the stack is empty, which means the parenthesis are balanced and our push down automaton works as intended.

Now the question remains, this was a lot of code and a ton of types is this a good way of determining if a string has its parenthesies balanced? Probably not, Rust as a language is not Haskell or even Scala - while Rust is certainly is able to express things with it's type system that Java developers can only dream about, abstractions in Rust sometimes results in code that is difficult to understand and this is natural because not only does it have to deal with what different generics but also the Rust memory model, which itself is encoded into the typesystem. With that said of course, there are abstractions which make sense, especially when you are smaller in scope, a function with one our two type parameters is so problem, a couple of traits, or a struct with two or three paramters are also fine. When going beyond that consider doing things at runtime, Rust is already plenty fast and that often leaves rooms to do things at runtime. In fact, by not abstracting over the problem we can implement balancing parenthesis like this.

fn balanced(data: &str) -> bool {
    data.chars().map(|x| match x {
		'(' => 1,
		')' => -1,
		_ => 0
    }).fold(0, |acc, x| {
		if acc < 0 {
		} else {
			acc + x
    }) == 0

And this is where I will leave you today, we have built a useful abstraction in Rust, shown how it works with a toy example, and shown how the example might just be easier with no abstraction at all. Hopefully you have learned something about useful abstractions in Rust and perhaps even given some thought to when and when not to use them.

A picture of William Rudenmalm

William Rudenmalm

Technologist at Sobel Software Research

William Rudenmalm is a european technologist passionate about the next big thing and the people building it. William is particularly interested in scaling engineering organizations and navigating trade offs of architecture and velocity. In the field of computer science, his expertise lies in distributed systems, scalability and machine learning. Among the technologies William is particularly excited about are Kubernetes, Rust, nats, Kafka and neo4j.