In the talk I gave at Rust LATAM, I said that the Rust project has always emphasized finding the best solution, rather than winning the argument. I think this is one of our deepest values. It’s also one of the hardest for us to uphold.

Let’s face it – when you’re having a conversation, it’s easy to get attached to specific proposals. It’s easy to have those proposals change from “Option A” vs “Option B” to “my option” and “their option”. Once this happens, it can be very hard to let them “win” – even if you know that both options are quite reasonable.

This is a problem I’ve been thinking a lot about lately. So I wanted to start an irregular series of blog posts entitled “Adventures in consensus”, or AiC for short. These posts are my way of exploring the topic, and hopefully getting some feedback from all of you while I’m at it.

This first post dives into what a phrase like “finding the best solution” even means (is there a best?) as well as the mechanics of how one might go about deciding if you really have the “best” solution. Along the way, we’ll see a few places where I think our current process could do better.

Beyond tradeoffs

Part of the challenge here, of course, is that often there is no “best” solution. Different solutions are better for different things.

This is the point where we often talk about tradeoffs – and tradeoffs are part of it. But I’m also wary of the term. It often brings to mind a simplistic, zero-sum approach to the problem, where we can all too easily decide that we have to pick A or B and leave it at that.

But often when we are faced with two irreconcilable options, A or B, there is a third one waiting in the wings. This third option often turns on some hidden assumption that – once lifted – allows us to find a better overall approach; one that satisfies both A and B.

Example: the ? operator

I think a good example is the ? operator. When thinking about error handling, we seem at first two face two irreconcilable options:

Explicit error codes , like in C, make it easy to see where errors can occur, but they require tedious code at the call site of each function to check for errors, when most of the time you just want to propagate the error anyway. This seems to favor explicit reasoning at the expense of the happy path . (In C specifically, there is also the problem of it being easy to forget to check for errors in the first place, but let’s leave that for now.)

, like in C, make it easy to see where errors can occur, but they require tedious code at the call site of each function to check for errors, when most of the time you just want to propagate the error anyway. This seems to favor at the expense of . Exceptions propagate the error implicitly, making the happy path clean, but making it very hard to see where an error occurs.

By now, a number of languages have seen that there is a third way – a kind of “explicit exception”, where you make it very easy and lightweight to propagate errors In Rust, we do this via the ? operator (which desugars to a match). In Swift (if I understand correctly) invoking a method that throws an exception is done by adding a prefix, like try foo() . Joe Duffy describes a similar mechanism in the midori language in his epic article dissecting Midori error handling.

Having used ? for a long time now, I can definitely attest that (a) it is very nice to be able to propagate errors in a light-weight fasion and (b) having the explicit marker is very useful. Many times I’ve found bugs by scrutinizing the code for ? , uncovering surprising control flow I wasn’t considering.

There is no free lunch

Of course, I’d be remiss if I didn’t point out that the discussion over ? was a really difficult one for our community. It was one of the longest RFC threads in history, and one in which the same arguments seemed to rise up again and again in a kind of cycle. Moreover, we’re still wrestling with what extensions (if any) we might want to consider to the basic mechanism (e.g., try blocks, perhaps try fns, etc).

I think part of the reason for this is that “the third option ain’t free”. In other words, the ? operator did a nice job of sidestepping the dichotomy that seemed to be presented by previous options (clear but tedious vs elegant but hidden), but it did so by coming into contact with other principles. In this case, the primary debate was over whether to consider some mechanism like Haskell’s do syntax for working with monads.

I think this is generally true. All the examples that I can come up with where we’ve found a third option generally come at some sort of price – but often it’s a price we’re content to pay. In the case of ? , this means that we have some syntax in the language that is dedicated to errors, when perhaps it could have been more general (but that might itself have come with limitations, or meant more complexity elsewhere).

Rust’s origin story

Overcoming tradeoffs is, in my view, the core purpose of Rust. After all, the ur-tradeoff of them all is control vs safety:

Control – let the programmer decide about memory layout, threads, runtime.

Safety – avoid crashes.

This choice used to be embodied by having to decide between using C++ (and gaining the control, and thus often performance) or a garbage-collected language like Java (and sacrifice control, often at the cost of performance). Deciding whether or not to use threads was a similar choice between peril and performance.

Ownership and borrowing eliminated that tradeoff – but not for free! They come with a steep learning curve, after all, and they impose some limitations of their own. (Flattening the slope of that learning curve – and extending the range of patterns that we accept – was of course a major goal of the non-lexical lifetimes effort, and I think will continue to be an area of focus for us going forward.)

Tradeoffs after all – but the right ones

So, even though I maligned tradeoffs earlier as simplistic thinking, perhaps in the end it does all come down to tradeoffs. Rust is definitely a language for people who prefer to measure twice and cut once, and – for such folks – learning ownership and borrowing has proven to be worth the effort (and then some!). But this clearly isn’t the right choice for all people and all situations.

I guess then that the trick is being sure that you’re trading the right things. You will probably have to trade something, but it may not be the things you’re discussing right now.

Mapping the solution space

When we talk about the RFC process, we always emphasize that the point of RFC discussion is not to select the best answer; rather, the point is to map the solution space. That is, to explore what the possible tradeoffs are and to really look for alternatives. This mapping process also means exploring the ups and downs of the current solutions on the table.

What does mapping the solution space really mean?

When you look at it, “mapping the solution space” is actually a really complex task. There are a lot of pieces to it:

Identifying stakeholders: figuring out who are the people affected by this change, for good or ill.

figuring out who are the people affected by this change, for good or ill. Clarifying motivations: what exactly are we aiming to solve with a given proposal? It’s interesting how often this is left unstated (and, I suspect, not fully understood). Often we have a general idea of the problem, but we could sharpen it quite a bit. It’s also very useful to figure out which parts of the problem are most important.

what exactly are we aiming to solve with a given proposal? It’s interesting how often this is left unstated (and, I suspect, not fully understood). Often we have a general idea of the problem, but we could sharpen it quite a bit. It’s also very useful to figure out which parts of the problem are most important. Finding the pros and cons of the current proposals: what works well with each solution and what are its costs.

what works well with each solution and what are its costs. Identifying new possibilities: finding new ways to solve the motivations. Sometimes this may not solve the complete problem we set out to attack, but only the most important part – and that can be a good thing, if it avoids some of the downsides.

finding new ways to solve the motivations. Sometimes this may not solve the complete problem we set out to attack, but only the most important part – and that can be a good thing, if it avoids some of the downsides. Finding the hidden assumption(s): This is in some way the same as identifying new possibilities, but I thought it was worth pulling out separately. There often comes a point in the design where you feel like you are faced with two bad options – and then you realize that one of the design constraints you took as inviolate isn’t, really, all that essential. Once you weaken that constraint, or drop it entirely, suddenly the whole design falls into place.

Our current process mixes all of these goals

Looking at that list of tasks, is it any wonder that some RFC threads go wrong? The current process doesn’t really try to separate out these various tasks in any way or even to really highlight them. We sort of expect people to “figure it out” on their own.

Worse, I think the current process often starts with a particular solution. This encourages people to react to that solution. The RFC author, then, is naturally prone to be defensive and to defend their proposal. We are right away kicking things off with an “A or B” mindset, where ideas belong to people, rather than the process. I think ‘disarming’ the attachment of people to specific ideas, and instead trying to focus everyone’s attention on the problem space as a whole, is crucial.

Now, I am not advocating for some kind of “waterfall” process here. I don’t think it’s possible to cleanly separate each of the goals above and handle them one at a time. It’s always a bit messy – you start with a fuzzy idea of the problem (and some stakeholders) and you try to refine it. Then you take a stab at what a solution might look like, which helps you to understand better the problem itself, but which also starts to bring in more stakeholders. Figuring out the pros and cons may spark new ideas. And so forth.

But just because we can’t use waterfall doesn’t mean we can’t give more structure. Exploring what that might mean is one of the things I hope to do in subsequent blog posts.

Conclusion

Ultimately, this post is about the importance of being thorough and deliberate in our design efforts. If we truly want to find the best design – well, I shouldn’t say the best design. If we want to find the right design for Rust, it’s often going to take time. This is because we need to take the time to elaborate on the implications of the decisions we are making, and to give time for a “third way” to be found.

But – lo – even here there is a tradeoff. We are trading away time, it seems, for optimality. And this clearly isn’t always the right choice. After all, “real artists ship”. Often, there comes a point where further exploration yields increasingly small improvements (“diminishing returns”).

As we explore ways to improve the design process, then, we should try to ensure we are covering the whole design space, but we also have to think about knowing when to stop and move on to the next thing.

Oh, one last thing…

Also, by the by, if you’ve not already read aturon’s 3-part series on “listening and trust”, you should do so.

Feedback

I’ve created a discussion thread on the internals forum where you can leave questions or comments. I’ll definitely read them and I will try to respond, though I often get overwhelmed, so don’t feel offended if I fail to do so.