Reversible Computation: (Possibly) the Next-Generation Theory of Software Construction

Hi everyone,

I’m from China, and recently I came across an interesting idea called Reversible Computation.

I’d like to share it with the community and see what you think.

I did a quick search on Hacker News and found that this term has been discussed before, but mostly in the context of physics.

The reversible computation I’m talking about here does originate from physics as well,

but it applies the idea to a very different domain: software engineering.

Let’s start with something familiar.

We all know that the best programmers (a.k.a. hackers) can design a clean, minimal abstraction. Let’s call that system P.

Then, less capable programmers (like me) come along and extend it with additional features. Let’s call my contribution Code.

So the result looks like this:

    App = P + Code

This process feels completely natural, doesn’t it?

Now, if we accept this forward process as natural, isn’t it also natural to imagine that a reverse process might exist?

Suppose we are faced with a huge, ugly, monolithic system W.

Shouldn’t there exist some form of inverse transformation that can refine it into a cleaner, simpler system L?

Something like:

    W + inverse Δ = L

You may not have seen something like this in everyday programming practice,

but mathematically, this kind of formulation is perfectly valid.

Let me switch perspectives and explain the idea in a more practical setting.

Imagine your company has developed a large, useful system.

One day, a customer comes along who wants something very similar—but not exactly the same.

Naturally, your company’s requirements and the customer’s requirements won’t line up perfectly.

What’s the traditional approach?

You extract the common parts into a smaller core system, and then maintain two diverging codebases derived from that core.

Under reversible computation, however, this step is not necessary.

Instead, you can focus entirely on maintaining your primary system, and write delta code that compensates for incompatibilities.

Let:

    X be your system
    Y be the system required by the customer
    Δ be the difference between them

Note that Δ includes both:

    features the customer wants to *add*, and
    features the customer implicitly wants to *remove* (i.e. things they simply don’t need).

This can be expressed as:

    Y = X + Δ

The key points are:

    1. X is never broken apart or refactored into pieces
    2. Differences are “attached”, not “torn out”

Here’s an example from the official documentation that contrasts different paradigms:

    Object-Oriented:        The inequality    A > B
    Component-Based:        Addition          A = B + C
    Reversible Computation: Delta composition Y = X + ΔY

What’s interesting here is that reversible computation can be seen as an extension of the compositional paradigm.

It introduces a surprisingly powerful subtractive primitive.

Traditional component reuse is based on the idea that only identical things can be reused.

Reversible Computation flips that idea into: “related things can be reused.”

As long as two systems can be expressed as X and X + Δ, they can share X with zero modification.

Interestingly enough, I think we’ve already encountered this idea before—in JavaScript’s prototype-based inheritance.

Reversible Computation simply pushes this intuition further, extending it from object models to entire software projects.

At the moment, I can’t yet see a clear practical revolution coming directly from this theory.

But the way it reframes how we think about software evolution is genuinely thought-provoking.

After all, the idea that you might write code specifically to remove behavior is kind of fascinating.

    App = Delta x-extends Generator<DSL>

    Gitee:  https://gitee.com/canonical-entropy/nop-entropy
    GitHub: https://github.com/entropy-cloud/nop-entropy