Essays
This is a review of all the resources I found and learned about persistent data structures in the course of looking for a solution for maintaining state. Complexity from maintaining state One of the hard things about programming is how to maintain and manage state [https://interjectedfuture.com/the-broken-half-of-interactive-programs/], especially
lab notes
This week was a little different. The implementation work was supposed to be fairly trivial, but in practice, it took a lot of time. The implementation was for an iterator that iterates over all the values in the RRBT in order. In theory, it's pretty trivial. The core
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Most of this week has been spent rewriting `append()`. This stemmed from mostly following the pseudocode from the L'Orange paper [https://hypirion.com/thesis.pdf] too closely. Excited about ChatGPT, I used it to convert the pseudocode to Rust code and tried to go from there. However, in
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Took a bit of a break, but have been back at it. The most involved part of implementing the relaxed radix balance trie is the concatenation. I had to consult three [https://hypirion.com/thesis.pdf] different [https://raw.githubusercontent.com/nicolasstucki/scala-rrb-vector/master/documents/Master%20Thesis%20-%20Nicolas%20Stucki%
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I'm usually not hung up about the programming language I use, but given Jamie's take [https://www.scattered-thoughts.net/writing/assorted-thoughts-on-zig-and-rust/], I did some deliberation about whether to use Zig or Rust. I ended up going with Rust, because I'm not a seasoned systems
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While moving forward through the implementation, it wasn't clear how the indexing worked in detail. How do you determine what segments were different between the live and storage-backed indices? By definition, aren't all segments in the live index novel? But more worryingly, what is the key
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A good part of the week was spent reading and watching talks on "The simple essence of automatic differentiation". I got the gist the first go around but much of the details were opaque to me. Reading it this second time around and actually working through the examples
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Reading more papers, mostly focused on Relaxed Radix Balanced Trees, since other trees, such as B-trees, Finger Trees, and HAMT trees seem to predate the research on this one. The premise is generally pretty simple, but the devil is in the details. The papers on it are fairly clear. I
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Watched lectures and read papers on persistent trees, and come away feeling like it's a rabbit hole. I initially found it difficult to implement a B+-tree in Rust, due to ownership rules, so I stopped. As much of an advantage it would be to have these things implemented, it's a commodity.
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I spent a bunch of time mapping out the architecture of Datomic in detail. Diving into all the details revealed all the different places my knowledge was spotty, or where Rich Hickey glossed over the details. * Are the internal nodes of the storage-backed index only in memory, or are they
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For the programming environment, I wanted a database embedded in it. I had stuided the architecture of Datomic, and it seems a convincing architecture to solve the problem of creating offline apps distributed online. However, Datomic is proprietary, and there isn't an official corresponding client side database either.
programming
What if the changes to the input result in state changes that can't be computed fast enough to keep the user interface snappy for an interactive program? Reactivity to the rescue. It's a way to drastically reduce the amount of computation required to compute an output given a change to the input.