gdp-paper

oom here, but the paper is an incredibly cool read and very approachable: https://arxiv.org/abs/1712.01208 Another really cool family of algorithms and associated structures in distributed systems is CRDTs. They're poorly understood, but in research they have largely superseded operational transforms. The Wikipedia page branches off into lots of good research: https://en.wikipedia.org/wiki/Conflict-free_replicated_data_... If we slightly broadened the lens of what is an algorithm, my favoriate category-theoretic approaches to solving problems include Recursion Schemes which are a technique to totally separate the specification of recursive algorithms over data structures from both the structures and the code that the algorithm runs to compute a result (Patrick from Github has a great series on them here: https://blog.sumtypeofway.com/). I also love the modern and rapidly growing "Ghosts of Forgotten Proofs" as a way to let the compiler assert you've properly built and/or terminated values: https://github.com/matt-noonan/gdp-paper/releases/download/j...

xceptional cases like network faults. F# is incredibly good at this kind of flow. > ADTs and FP techniques provide only syntactic sugar to avoid this spaghetti in the source code. But due to that they just encourage having the worst mess of control actually happen on the machine. You've said this multiple times, but it's just not true. The F# code is just a function that calls functions. F#, ML and Haskell compilers all aggressively inline these calls. You pay the exact same costs for validating an error exists in the Golang style, in practice. Indeed, lots of people generate Go from liskov-style templates JUST to get ADTs to make error handling less painful. It's gaining popularity in Swift and Rust as well. Folks there aren't trying to impress people with their FP knowledge, they're cribbing a technique that works and scales well. > My example does not have a single if statement (yes, you might argue there are if statements hidden in the for loops). I clearly stated that it's often possible to choose this approach. Your example, by your own admission, doesn't address error handling flows. You need conditional logic to work with operations that don't always succeed. You say, "Structure it so you never have them." I think a lot of FP people would agree with this (in fact, there is a really cool functional pearl about doing exactly this at scale: https://github.com/matt-noonan/gdp-paper/releases/download/j...) but they'd think about it less as a function of assurances and "thinking very hard" and more about using methods to make inconsistent code provably false at compile time. Very few languages can actually encode formal notions of correctness, right now. Recently languages like Idris, Agda, Coq, and TLA come up as tools for formal correctness, where you can actually have your compiler prove your invariants and their implications.