One option is dependent pairs, where one value of the pair (in this example) would be the length of the array and the other value is a type which depends on that same value (such as Vector n T instead of List T).
Type-Driven Development with Idris[1] is a great introduction for dependently typed languages and covers methods such as these if you're interested (and Edwin Brady is a great teacher).
We're not done building the boring stuff or solving the hard problems either. One is, well, boring and the other is...hard. Easy enough to proxy out prompts to OpenAI for your next funding round, though.
Other languages that make heavy usage of non-ASCII Unicode characters (such as Lean) often have tooling support such that one can type '\' along with some combination of ASCII characters to generate characters like '≈', '≠' and 'ƒ'. Along with searchable documentation for the whole mapping of shorthand codes to the mapped Unicode values, of course.
Code is read more than written, so I have grown to appreciate programming languages that lean into non-ASCII characters for semantic clarity :)
In event sourced systems, you project the event stream into read models, of which there can be many (relational, time series, etc.) If you're familiar with functional programming, it is essentially a fold operation over the stream of events into a single state.
Having worked with event sourced systems in the past, there are benefits in having a persisted explicit event history, but there is much added complexity (how do those read models actually get generated? how do you version the model? do you have snapshots of your read models?). In my experience, the additional complexity was not worth it for most contexts in which the pattern was applied...
I would recommend two. F# in Action [1] by Isaac Abraham is a great (and recent) introduction to the F# language. For a more philosophical, domain-oriented book, you can't go wrong with Scott Wlaschin's Domain Modeling Made Functional book[2]. Scott's blog[3] is also must-read material.
It may be sacrilege to say this, but I have adopted Retool in my organization for the purposes of quick-and-dirty internal apps that are essentially thin GUIs around internal data stores. It has worked out well for us and even stodgy backend engineers like myself can be productive with it.
Congratulations on the publication! As a dabbler in strictly typed functional programming languages like Scala and F#, I have always been curious about proof-oriented languages such as Coq or Agda, but found it difficult to justify the time investment. Lean seems to position itself as a theorem proving language that also supports general-purpose programs. Looking forward to digging into your book!
My understanding is that the 'linear' terminology derives from the field of Linear Logic[1]. But, I am by no means an expert on theoretical computer science etymology!
In my perusals into the Haskell ecosystem, discovering Hoogle[1] was definitely a revelation on the power of a strongly-typed language. Sometimes, you know the _shape_ of the thing you are looking for, but not the name. The ability to search a repository of packages for all functions conforming to a certain type signature (e.g., (a -> Bool) -> [a] -> [a]) is a superpower.
Unit of measures are a great example of what a type system can do, and something not enough languages support. F#[1] and Scala[2] are two that I know of that do support UOMs. Like you, I haven't had the need to use them in the domains I work in, but I imagine that they would be invaluable in certain contexts.
The short answer is that a category also satisfies two rules: every object has an arrow to itself (identity) and if there are two arrows (a->b) and (b->c) there is an arrow (a->c) (associativity).
Other abstractions such as functors (mappings between categories) are built upon this relatively simple foundation. You can also think about categories of categories (they can be considered an object, after all!), and so on and so forth.
Some complain about the generality of Category Theory ('It is a theory about everything and nothing!'), but its generality makes it compelling for some for study.
Not the OP, but I have had success with CDK. The main advantages for me have been discoverability with respect to resource properties, along with proper, higher-level abstractions pertaining to AWS infrastructure. https://aws.amazon.com/blogs/devops/leverage-l2-constructs-t...
F# 6.0 added the 'task' computation expression, which is much more performant than the F# 'async' methods. It also makes interop with C# projects and libraries simpler, as is uses the same mechanism that C#'s async/await does. I have used it in production workflows without major performance issues FWIW.
Type-Driven Development with Idris[1] is a great introduction for dependently typed languages and covers methods such as these if you're interested (and Edwin Brady is a great teacher).
[1] https://www.manning.com/books/type-driven-development-with-i...