Mathematics and Computation

In various mathematical forums, mostly those of a logical flavor, I regularly see people asking basic questions about constructive mathematics. I also see misconceptions about constructive mathematics. I shall make a series of posts, _Constructive Gems and Stone_s, which will answer basic questions about constructive mathematics, and will hopefully help fix wrong ideas about constructive mathematics.

A constructive gem is something nice about constructive mathematics that makes you want to know more about it. In contrast, a constructive stone is a complication in constructive mathematics which does not exist in the classical counterpart.

Here we go! The first one is about finite sets.

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These are the slides and the extended abstract from my MSFP 2008 talk. Apparently, I forgot to publish them online. There is a discussion on the Agda mailing list to which the talk is somewhat relevant, so I am publishing now.

Abstract: Realizability is an interpretation of intuitionistic logic which subsumes the Curry-Howard interpretation of propositions as types, because it allows the realizers to use computational effects such as non-termination, store and exceptions. Therefore, we can use realizability as a framework for program development and extraction which allows any style of programming, not just the purely functional one that is supported by the Curry-Howard correspondence. In joint work with Christopher A. Stone we developed RZ, a tool which uses realizability to translate specifications written in constructive logic into interface code annotated with logical assertions. RZ does not extract code from proofs, but allows any implementation method, from handwritten code to code extracted from proofs by other tools. In our experience, RZ is useful for specification of non-trivial theories. While the use of computational effects does improve efficiency it also makes it difficult to reason about programs and prove their correctness. We demonstrate this fact by considering non-purely functional realizers for a Brouwerian continuity principle.

Download: msfp2008-slides.pdf, msfp2008-abstract.pdf

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In a recent post I claimed that Python's lambda construct is broken. This attracted some angry responses by people who thought I was confused about how Python works. Luckily there were also many useful responses from which I learnt. This post is a response to comment 27, which asks me to say more about my calling certain design decisions in Python crazy.

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I quite like Python for teaching. And people praise it for the lambda construct which is a bit like $\lambda$-abstraction in functional languages. However, it is broken!

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I have been writing lecture notes on computable mathematics. One of the questions that came up was whether it is possible to simulate the booleans in the simply-typed $\lambda$-calculus. This is a nice puzzle in functional programming. If you solve it, definitely let me know, although I suspect logicians did it a long time ago.

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Abstract: In the effective topos there exists a chain-complete distributive lattice with a monotone and progressive endomap which does not have a fixed point. Consequently, the Bourbaki-Witt theorem and Tarski’s fixed-point theorem for chain-complete lattices do not have constructive (topos-valid) proofs.

Download: fixed-points.pdf

Published in: Theoretical Computer Science Volume 430, 27 April 2012, Pages 43–50. Mathematical Foundations of Programming Semantics (MFPS XXV)

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I have aded to the PL Zoo a mini prolog interpreter. It really is minimalistic, as it only handles pure Horn clauses. There is no arithmetic, lists, cuts, or disjunctions. Nevertheless, it ought to be possible to write a miniml interpreter in it... If anyone does it, please send me the code!

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This is a short note pointing out that the recent paper on“Mathematical undecidability and quantum randomness” by Tomasz Paterek et al. is no black magic, and that the authors are well aware of it. Unfortunately the paper appeared on Slashdot and has since generated an infinite amount of quasi-mathematical discussions.

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I have added two new languages to the PL Zoo. The minor addition is miniml+error, which is just MiniML with an error exception (raised by division by 0) that cannot be caught. The purpose is to demonstrate handling of fatal errors during runtime. The more interesting new animal is levy (written by Matija Pretnar and myself), an implementation of Paul Levy's call-by-push-value language. If you only know about Haskell's call-by-name and ML's call-by-value, I invite you to learn about call-by-push-value. Start by reading Paul's FAQ.

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I show how monads in Haskell can be used to structure infinite search algorithms, and indeed get them for free. This is a follow-up to my blog post Seemingly impossible functional programs. In the two papers Infinite sets that admit fast exhaustive search (LICS07) and Exhaustible sets in higher-type computation (LMCS08), I discussed what kinds of infinite sets admit exhaustive search in finite time, and how to systematically build such sets. Here I build them using monads, which makes the algorithms more transparent (and economic).

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