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Railway

Railway is my amateur attempt at a reversible imperative programming language. Its unique features (compared to reversible languages I have read about) include communicating multi-threading, mono-directional 'rvalue' variables, and the try-catch construct. In the interest of unrestricted experimentation some of the language's features are slightly at odds with one another, however they are disjoint enough that there are very cohesive subsets.

This repository contains a simple tree-walking proof-of-concept Railway interpreter, placing a high emphasis on ensuring program correctness at run-time and completely disregarding performance (speed). A possible future project is to write a proper byte-code compiler, or devise an alternative dialect suitable for machine-code compilation.

Usage

Requires Python3.8. Install using the provided setup script, either with pip or by running

> python setup.py install

This will put the interpreter railway somewhere accessible in your path, which you can use to run Railway files (those with the .rail extension)

> cd examples
> railway cellular_automaton.rail

> cd NeuralNetwork
> railway predict.rail \
      -f32 W1.float32  \
      -f32 W2.float32  \
      -f32 images/6_four.float32

Reversible Computation?

Railway is a reversible language in the sense that any sequence of statements can be run both forwards and backwards deterministically, and hence so can any Railway program. This might evoke for you the image of a train on a fixed set of tracks, along which it can move freely in either direction. There are two reasons we might be interested in reversibility:

  • In theory: A language in which every operation is invertible must necessarily be information-constant, that is it can not be possible to create or destroy information in any way. As silicon manufacturing processes get smaller and smaller, we become more and more concerned with the absolute physical limits of the technology. A process that destroys information is increasing entropy and so is guaranteed to produce some quantity of heat, limiting the density of transistors that can be accommodated on the CPU due to cooling restraints. A process that uses a completely reversible model of computation need not increase entropy and so (in theory) has no guaranteed lower limit on heat production. Of course nothing like that could be achieved by a reversible language such as Railway being emulated by a non-reversible process on any current CPU, but studying reversible models of computation would be the first step on a path to understanding how to build such a system.

    Also, people who talk about reversible programming languages sometimes talk about quantum computers, and I don't really know why.

  • In Practice: A language in which any set of instructions can be run backwards provides great opportunity for experimenting with novel control structures and techniques. For example, if you have written a (lossless) compression function in Railway you get the corresponding decompression function for free because said function can be run backwards.

    (data) => call compress() => (compressed_data)
    (compressed_data) => uncall compress() => (data)
    

    As another example, the try-catch construct makes several attempts to run a block of code with different initial conditions provided by an iterator. Any time a catch happens, the interpreter reverts the state of the program back to the beginning of the try block by running the relevant lines backwards, then reattempts the try with the next initial condition.

    try (step_size in [10 to 1 by -1])
        call step_simuation(state, step_size) => (error)
        catch (error > epsilon)
    yrt
    

    More examples can be found in the full "documentation".

Influences

Reversible languages mainly exist as academic papers and proof-of-concept interpreters/compilers (like this one). Before writing Railway I read some parts of some of these papers.

There are some very interesting reversible functional languages (CoreFun, rFun) but I came to reversible computation via an interest in turning back time, and functional languages don't care much for time so Railway is imperative. Equally there are excellent explorations of reversible computation using OOP (ROOPL, Joule), but I felt that the need to track each object's history so explicitly works against the goals of traditional OOP, so Railway is not Object Oriented. Therefore, the two main influences for Railway are Janus (the original reversible language) and Arrow. The former of course provides a skeleton of basic ideas for the language, the latter provides inspiration for things like the do-yield-undo construct. Though you may see many arrow symbols (=>) in Railway programs, this is actually part of the ownership system and bears no relation to the arrows in Arrow.

Docs

Documentation is a pretty strong word for what's written in the following pages, but it does go into detail about most of the components of Railway the language, how they are generally composed into Railway programs, and a little bit of design narrative. They were written in a specific order, so unfortunately some of the more interesting later topics might not make complete sense before reading the more basic ones. Even the basic elements of the language need careful consideration to ensure reversibility.

  1. Variables, Data and Scope
  2. Control Structures
  3. Functions
  4. Mono Variables
  5. Parallelism

Examples

The examples directory contains some Railway programs (files with the .rail extension) and a few comments on why they do what they do. There are things in there like a reversible cellular automaton (think Conway's Game of Life) and a simple neural network which does handwriting recognition on digits from the MNIST dataset. One day I'll get around to writing the reversible Turing machine to show Railway is rTuring-complete.

Writing the examples was the main way I learnt what is viable in a reversible program and where I decided on the course of further development. They are a good way to see how the elements of the language interact, and how reversible programs behave differently to conventional ones.