I don't think it's a universal property of functional languages. Haskell is also strongly (excessively) typed, down to the level of modeling computation itself, and it's lazy.

See, when you are defining a Haskell program, you are conceptually creating a tree of thunks that eventually get executed by the GHC runtime. Those thunks are typed, meaning they have typed inputs and outputs, and are either side-effect-free or are defined in a context that controls their side effects (e.g. the IO monad).

So you can change the definition of types willy-nilly and either get a working compiled program or some error output that tells you exactly what is broken or doesn't make sense to GHC's model of your proposed computation. Because computation itself is typed, you have a stronger guarantee that it will work as expected when executed by the GHC runtime. Because side effects are controlled, you are forced by the type checker to handle runtime errors (or crash).

At least that's how I understand it as someone who works with gifted Haskell engineers, but exists very much on the periphery of understanding.

A functional language is fundamentally one where the same inputs always produce the same outputs. So you can e.g. change the order of two function calls and be confident that that's not going to change the behaviour, without even running it. In a language with pervasive state mutation, essentially any change you make to the code might change what the program does, so you have to test every little thing. https://www.lihaoyi.com/post/WhatsFunctionalProgrammingAllAb...

Type systems of functional languages are generally capable of representing more. You can have the type system validate application state at compile time for you, for example.

If it compiled before and worked and your refactored version also compiles, chances are you didn't break anything.

One practical example: if you have a union of A|B, and you decide to add a third shape C to it, your program won't compile until logic for C is written in all the places where A and B are already being matched against. Refactoring often means changing data models, then letting the errors walk you through the actual implementation details.

With mutable state every function has an implicit dependency on other stuff. Without mutable state your function depends on its arguments, and produces only a return value. No moving parts or implicit dependencies = you can cut and paste stuff around the code base like there is no tomorrow.

Because it is more difficult to make a change that affects other code without a change in types occurring, which will make compilation fail until all affected code is updated.

In addition to the type system, I'd also add purity. If you have a function f :: a -> b, there is literally no way for f to read anything besides a, or affect anything besides returning b (aside from unsafePerformIO, which you can ban from your code.) so if you want to refactor f, you know exactly from the call site everything that needs to be updated.

all state is factored, so it can easily be refactored.

It’s mostly the type system. Ocaml is the same. Static typing, type inference and the easiness of introducing complex types really help when it comes to fitting the code together. Beginners tend to think that "if it compiles it works" and it feels that way sometimes but you lose the hubris once you are bitten by a bug complicated enough to pass though.

Perhaps it is easier because Peyton Jones is a world class expert in Haskell and have 30 years experience refactoring it?

In my experience the ease of refactoring is more depending on the quality of the code you are refactoring than the language. That said, a strong type system helps avoiding stupid mistakes and Haskell have a very strong type system.

almost no, if at all, state

you can unplug, replug stuff at will