Optimizing Away the Need To Perform Expensive Deep Copies
It can be very useful for multithreading but not in the type of example you provided. For small strings, it would be so much more efficient to avoid any ref counting/GC and just deep copy and ideally with a small buffer optimization as I'm sure you realize.
But consider a game example where you have systems that want to operate in a parallel pipeline like a physics system, AI system, rendering system, etc, all inputting a game scene and producing a modified output so that the physics system can be working on frame 2 while the rendering system is still rendering frame 1. Very few game engines avoid a serial pattern here across systems (they might multithread the work done within a system like with parallel loops, but not achieve a parallel pipeline across systems)[*].
- Most gamedevs I've talked to on the game exchange section of stack exchange, including very high-profile ones, consider it too much trouble than it's worth to even double-buffer game state to allow even two system to run in parallel, not to mention triple-buffering to allow three, and quadruple-buffering for four, and so forth. But they might not have considered copy-on-write data structures which can trivialize the effort.
Massive, Shared, Mutable Data
Allowing these systems to operate in parallel means that they cannot share mutable data without locks. They can have their own thread-local copy of unshared mutable data, or shared immutable data, but they cannot share mutable data without locking and bottlenecking other threads on access. Avoiding either the sharing or the mutability (we only need one to avoid bottlenecking threads) may or may not be tricky depending on the game engine.
With basic game engines that deal mostly with unchanging scene data, we can probably easily and cleanly separate the immutable scene data that can be freely shared without locking from the small subset that is mutable which can be locally deep copied for each thread to avoid the sharing (and as John Carmack pointed out, this may only have to be some megabytes for many games, not hundreds of megabytes or gigabytes). The design constraints allow that for most orthodox game engines which don't even have the possibility of mutating much scene data per frame.
For example, most game engines don't even offer the ability to freely mutate hefty character models for bone deformations or facial animations in any arbitrary frame while the game is running (only their animation parameters, like bone matrices). Instead they generate the deformed version on the fly in a vertex shader and so the bulk of the hefty game data is immutable and easy to separate from the mutable given the heavy engine-imposed restrictions on what's allowed to change per frame.
Designs That Cannot Anticipate What Will Mutate
Yet consider a very innovative game doing things so differently from orthodox AAA engines that uses a freely-destructible voxel environment with voxels much smaller than Minecraft, maybe even close to pixel resolution or less at normal viewing distances. But the sheer amount of environment destructibility means that almost all the hefty data of the scene is mutable and can be changed by user input at any given time. Here even generating the results in a shader would still require treating enormous amounts of data as mutable per frame, as the input parameters are no longer simple matrices or vectors or scalars affecting things at a whole model level, but would be parameters affecting things at the individual voxel level with billions of voxels.
That's going to involve a scene that might easily require hundreds of megabytes to gigabytes of data that could be mutated at any given time (we cannot possibly anticipate what might change in a frame given such user freedom) per deep copy of the scene, even with a very efficient sparse voxel octree that can compress voxels down to less than a byte in size. What would normally have to be treated as inevitably shared and mutable data in this case is enormous, and eliminating the sharing of the mutable data via thread-local deep copies might require deep copying this enormous amount of data in close to its entirety per thread per frame (which might easily require more time just spent copying than the thread requires to do its thing with it not to mention the explosive memory use).
Automating Away the Sharing of Mutable Data With COW
Copy-on-write in this case comes to the rescue where we cannot possibly anticipate what will be mutated of this enormous scene in advance as it automatically avoids modifying the shared, immutable shallow copy of the parts of the scene which have not been modified. If one thread -- like the physics thread working on frame 4 while the AI system is working on frame 3 while the rendering system is working on frame 2 -- wants to modify a small section of the scene, only that small section of the scene that is requested to be modified is deep-copied on write keeping the other threads able to churn away and do their thing while keeping regular copying relatively dirt cheap and shallow (at least for data that spans hundreds of megabytes or more).
Writing/mutation becomes a bit more expensive as a result of the atomic ref counting or GC but very often at least in the types of scenarios I deal with, a thread might only need to modify 1 megabyte worth of data while the scene spans an entire gigabyte. It's more than a worthwhile exchange and instead a fantastic bargain to avoid having to deep copy the entirety of that scene data at the relatively trivial expense of some atomic operations and small, partial deep copies of the smallest subset of the scene to avoid what would otherwise be hundreds of megabytes to gigabytes of data deep copied per-frame per-thread.
Conclusion
So apologies for the long-windedness, but this is at least one use case where I think copy-on-write has to be both the most efficient and elegant solution: in cases where the shared mutable data is too massive to be deep copied left and right for each thread for every single frame but only a subset of it is actually modified per thread per frame (but in ways that are impossible for designers to anticipate in advance).
A Note
It's also worth noting that all persistent data structures in functional languages use copy-on-write behind the scenes. That's how a PDS is implemented. They may not expose the mutable interface to the users in ways we might want to do in an imperative language like C++, but under the hood it's always COW. So fans of languages like Haskell or Clojure are at least using COW all over the place under the hood at the implementation level, even if they're not exposed to it and only dealing with conceptually read-only interfaces to immutable data structures.