DataStructure

March 5, 2023
in Ordinal, DataStructure
6 min read

Transfinite Zippers

In my previous post, I described an approach for extending multi-stage programming (MSP) to infinity and beyond. We start with a simple computing “machine” M[0] such as the lambda calculus. Each machine M[a] has a successor machine M[a+1] which is capable of building and reasoning about programs from M[a], yielding towers of nested machines. From there, we note that MSP itself can’t be implemented in any such finite M[n], but must exist in some limit machine M[ω], yielding transfinite towers of machines M[a] for each ordinal a.

May 30, 2022
in DataStructure, Ordinal
7 min read

Efficient Transfinite Lists

My last two posts were about ordinals and pure lists, and they got a combined whopping 11 claps, so I’m selling out and writing a post about both. In particular, this post is about a data structure I discovered for lists of transfinite length. A repo is linked at the bottom.

October 21, 2020
in DataStructure
7 min read

Pure Lists with O(log(i)) Indexing

Linked lists are simple and ubiquitous. When used as a stack, they allow for constant time pushing and popping. Furthermore, they are purely functional: multiple processes can branch off of a linked list and push their own items without stepping on eachothers’ toes, so long as they avoid mutating the list. However, indexing into a list is slow: retrieving the i’th element of a list requires i “hops” along the items. While indexing isn’t technically required of a stack, it is often desired. (For example, when implementing an interpreter with De Bruijn indices, variable lookup requires indexing into the stack representing the environment.) As the title suggests, it turns out that we can improve upon lists to achieve O(log(i)) indexing without forfeiting purity and O(1) push/pop. I call them rainbow lists.