\documentclass[report]{article} \usepackage{etex} %% Narrow margins % \usepackage{fullpage} %% Bibtex \usepackage{natbib} %% Links \usepackage{hyperref} %% Frames \usepackage{framed} %% Symbols \usepackage[fleqn]{amsmath} \usepackage{stmaryrd} %llbracket %% Proof trees \usepackage{bussproofs} %% Diagrams \usepackage[all]{xy} %% Quotations \usepackage{epigraph} %% Images \usepackage{graphicx} %% Subfigure \usepackage{subcaption} %% diagrams \usepackage{tikz} \usetikzlibrary{shapes,arrows,positioning} % \usepackage{tikz-cd} % \usepackage{pgfplots} %% ----------------------------------------------------------------------------- %% Commands for Agda \usepackage[english]{babel} \usepackage[conor]{agda} \renewcommand{\AgdaKeywordFontStyle}[1]{\ensuremath{\mathrm{\underline{#1}}}} \renewcommand{\AgdaFunction}[1]{\textbf{\textcolor{AgdaFunction}{#1}}} \renewcommand{\AgdaField}{\AgdaFunction} % \definecolor{AgdaBound} {HTML}{000000} \definecolor{AgdaHole} {HTML} {FFFF33} \DeclareUnicodeCharacter{9665}{\ensuremath{\lhd}} \DeclareUnicodeCharacter{964}{\ensuremath{\tau}} \DeclareUnicodeCharacter{963}{\ensuremath{\sigma}} \DeclareUnicodeCharacter{915}{\ensuremath{\Gamma}} \DeclareUnicodeCharacter{8799}{\ensuremath{\stackrel{?}{=}}} \DeclareUnicodeCharacter{9655}{\ensuremath{\rhd}} %% ----------------------------------------------------------------------------- %% Commands \newcommand{\mysyn}{\AgdaKeyword} \newcommand{\mytyc}{\AgdaDatatype} % TODO have this with math mode so I can have subscripts \newcommand{\mydc}{\AgdaInductiveConstructor} \newcommand{\myfld}{\AgdaField} \newcommand{\myfun}{\AgdaFunction} \newcommand{\myb}[1]{\AgdaBound{$#1$}} \newcommand{\myfield}{\AgdaField} \newcommand{\myind}{\AgdaIndent} \newcommand{\mykant}{\textsc{Kant}} \newcommand{\mysynel}[1]{#1} \newcommand{\myse}{\mysynel} \newcommand{\mytmsyn}{\mysynel{term}} \newcommand{\mysp}{\ } \newcommand{\myabs}[2]{\mydc{$\lambda$} #1 \mathrel{\mydc{$\mapsto$}} #2} \newcommand{\myappsp}{\hspace{0.07cm}} \newcommand{\myapp}[2]{#1 \myappsp #2} \newcommand{\mysynsep}{\ \ |\ \ } \FrameSep0.2cm \newcommand{\mydesc}[3]{ \noindent \mbox{ \parbox{\textwidth}{ {\small \vspace{0.3cm} \hfill \textbf{#1} $#2$ \framebox[\textwidth]{ \parbox{\textwidth}{ \vspace{0.1cm} \centering{ #3 } \vspace{0.1cm} } } } } } } % TODO is \mathbin the correct thing for arrow and times? \newcommand{\mytmt}{\mysynel{t}} \newcommand{\mytmm}{\mysynel{m}} \newcommand{\mytmn}{\mysynel{n}} \newcommand{\myred}{\leadsto} \newcommand{\mysub}[3]{#1[#2 / #3]} \newcommand{\mytysyn}{\mysynel{type}} \newcommand{\mybasetys}{K} % TODO change this name \newcommand{\mybasety}[1]{B_{#1}} \newcommand{\mytya}{\myse{A}} \newcommand{\mytyb}{\myse{B}} \newcommand{\mytycc}{\myse{C}} \newcommand{\myarr}{\mathrel{\textcolor{AgdaDatatype}{\to}}} \newcommand{\myprod}{\mathrel{\textcolor{AgdaDatatype}{\times}}} \newcommand{\myctx}{\Gamma} \newcommand{\myvalid}[1]{#1 \vdash \underline{\mathrm{valid}}} \newcommand{\myjudd}[3]{#1 \vdash #2 : #3} \newcommand{\myjud}[2]{\myjudd{\myctx}{#1}{#2}} % TODO \mathbin or \mathrel here? \newcommand{\myabss}[3]{\mydc{$\lambda$} #1 {:} #2 \mathrel{\mydc{$\mapsto$}} #3} \newcommand{\mytt}{\mydc{$\langle\rangle$}} \newcommand{\myunit}{\mytyc{Unit}} \newcommand{\mypair}[2]{\mathopen{\mydc{$\langle$}}#1\mathpunct{\mydc{,}} #2\mathclose{\mydc{$\rangle$}}} \newcommand{\myfst}{\myfld{fst}} \newcommand{\mysnd}{\myfld{snd}} \newcommand{\myconst}{\myse{c}} \newcommand{\myemptyctx}{\cdot} \newcommand{\myhole}{\AgdaHole} \newcommand{\myfix}[3]{\mysyn{fix} \myappsp #1 {:} #2 \mapsto #3} \newcommand{\mysum}{\mathbin{\textcolor{AgdaDatatype}{+}}} \newcommand{\myleft}[1]{\mydc{left}_{#1}} \newcommand{\myright}[1]{\mydc{right}_{#1}} \newcommand{\myempty}{\mytyc{Empty}} \newcommand{\mycase}[2]{\mathopen{\myfun{[}}#1\mathpunct{\myfun{,}} #2 \mathclose{\myfun{]}}} \newcommand{\myabsurd}[1]{\myfun{absurd}_{#1}} \newcommand{\myarg}{-} \newcommand{\myderivsp}{\vspace{0.3cm}} \newcommand{\mytyp}{\mytyc{Type}} \newcommand{\myneg}{\myfun{$\neg$}} \newcommand{\myar}{\,} \newcommand{\mybool}{\mytyc{Bool}} \newcommand{\mytrue}{\mydc{true}} \newcommand{\myfalse}{\mydc{false}} \newcommand{\myitee}[5]{\myfun{if}\,#1 / {#2.#3}\,\myfun{then}\,#4\,\myfun{else}\,#5} \newcommand{\mynat}{\mytyc{$\mathbb{N}$}} \newcommand{\myrat}{\mytyc{$\mathbb{R}$}} \newcommand{\myite}[3]{\myfun{if}\,#1\,\myfun{then}\,#2\,\myfun{else}\,#3} \newcommand{\myfora}[3]{(#1 {:} #2) \myarr #3} \newcommand{\myexi}[3]{(#1 {:} #2) \myprod #3} \newcommand{\mypairr}[4]{\mathopen{\mydc{$\langle$}}#1\mathpunct{\mydc{,}} #4\mathclose{\mydc{$\rangle$}}_{#2{.}#3}} \newcommand{\mylist}{\mytyc{List}} \newcommand{\mynil}[1]{\mydc{[]}_{#1}} \newcommand{\mycons}{\mathbin{\mydc{∷}}} \newcommand{\myfoldr}{\myfun{foldr}} \newcommand{\myw}[3]{\myapp{\myapp{\mytyc{W}}{(#1 {:} #2)}}{#3}} \newcommand{\mynode}[2]{\mathbin{\mydc{$\lhd$}_{#1.#2}}} \newcommand{\myrec}[4]{\myfun{rec}\,#1 / {#2.#3}\,\myfun{with}\,#4} \newcommand{\mylub}{\sqcup} \newcommand{\mydefeq}{\cong} \newcommand{\myrefl}{\mydc{refl}} \newcommand{\mypeq}[1]{\mathrel{\mytyc{=}_{#1}}} \newcommand{\myjeqq}{\myfun{=-elim}} \newcommand{\myjeq}[3]{\myapp{\myapp{\myapp{\myjeqq}{#1}}{#2}}{#3}} \newcommand{\mysubst}{\myfun{subst}} \newcommand{\myprsyn}{\myse{prop}} \newcommand{\myprdec}[1]{\mathopen{\mytyc{$\llbracket$}} #1 \mathopen{\mytyc{$\rrbracket$}}} \newcommand{\myand}{\mathrel{\mytyc{$\wedge$}}} \newcommand{\myprfora}[3]{\forall #1 {:} #2. #3} \newcommand{\myimpl}{\mathrel{\mytyc{$\Rightarrow$}}} \newcommand{\mybot}{\mytyc{$\bot$}} \newcommand{\mytop}{\mytyc{$\top$}} \newcommand{\mycoe}{\myfun{coe}} \newcommand{\mycoee}[4]{\myapp{\myapp{\myapp{\myapp{\mycoe}{#1}}{#2}}{#3}}{#4}} \newcommand{\mycoh}{\myfun{coh}} \newcommand{\mycohh}[4]{\myapp{\myapp{\myapp{\myapp{\mycoh}{#1}}{#2}}{#3}}{#4}} \newcommand{\myjm}[4]{(#1 {:} #2) \mathrel{\mytyc{=}} (#3 {:} #4)} \newcommand{\myeq}{\mathrel{\mytyc{=}}} \newcommand{\myprop}{\mytyc{Prop}} \newcommand{\mytmup}{\mytmsyn\uparrow} \newcommand{\mydefs}{\Delta} \newcommand{\mynf}{\Downarrow} \newcommand{\myinff}[3]{#1 \vdash #2 \Rightarrow #3} \newcommand{\myinf}[2]{\myinff{\myctx}{#1}{#2}} \newcommand{\mychkk}[3]{#1 \vdash #2 \Leftarrow #3} \newcommand{\mychk}[2]{\mychkk{\myctx}{#1}{#2}} \newcommand{\myann}[2]{#1 : #2} \newcommand{\mydeclsyn}{\myse{decl}} \newcommand{\myval}[3]{#1 : #2 \mapsto #3} \newcommand{\mypost}[2]{\mysyn{postulate}\ #1 : #2} \newcommand{\myadt}[4]{\mysyn{data}\ #1 : #2\ \mysyn{where}\ #3\{ #4 \}} \newcommand{\myreco}[4]{\mysyn{record}\ #1 : #2\ \mysyn{where}\ #3\ \{ #4 \}} % TODO change vdash \newcommand{\myelabt}{\vdash} \newcommand{\myelabf}{\rhd} \newcommand{\myelab}[2]{\myctx \myelabt #1 \myelabf #2} \newcommand{\mytele}{\Delta} \newcommand{\mytelee}{\delta} \newcommand{\mydcctx}{\Gamma} \newcommand{\mynamesyn}{\myse{name}} \newcommand{\myvec}{\overrightarrow} \newcommand{\mymeta}{\textsc} \newcommand{\myhyps}{\mymeta{hyps}} \newcommand{\mycc}{;} \newcommand{\myemptytele}{\cdot} \newcommand{\mymetagoes}{\Longrightarrow} % \newcommand{\mytesctx}{\ \newcommand{\mytelesyn}{\myse{telescope}} \newcommand{\myrecs}{\mymeta{recs}} \newcommand{\myle}{\mathrel{\lcfun{$\le$}}} %% ----------------------------------------------------------------------------- \title{\mykant: Implementing Observational Equality} \author{Francesco Mazzoli \href{mailto:fm2209@ic.ac.uk}{\nolinkurl{}}} \date{June 2013} \begin{document} \iffalse \begin{code} module thesis where \end{code} \fi \maketitle \begin{abstract} The marriage between programming and logic has been a very fertile one. In particular, since the simply typed lambda calculus (STLC), a number of type systems have been devised with increasing expressive power. Section \ref{sec:types} will give a very brief overview of STLC, and then illustrate how it can be interpreted as a natural deduction system. Section \ref{sec:itt} will introduce Inutitionistic Type Theory (ITT), which expands on this concept, employing a more expressive logic. The exposition is quite dense since there is a lot of material to cover; for a more complete treatment of the material the reader can refer to \citep{Thompson1991, Pierce2002}. Section \ref{sec:equality} will explain why equality has always been a tricky business in these theories, and talk about the various attempts that have been made to make the situation better. One interesting development has recently emerged: Observational Type theory. Section \ref{sec:practical} will describe common extensions found in the systems currently in use. Finally, section \ref{sec:kant} will describe a system developed by the author that implements a core calculus based on the principles described. \end{abstract} \clearpage \tableofcontents \clearpage \section{Simple and not-so-simple types} \label{sec:types} \subsection{The untyped $\lambda$-calculus} Along with Turing's machines, the earliest attempts to formalise computation lead to the $\lambda$-calculus \citep{Church1936}. This early programming language encodes computation with a minimal syntax and no `data' in the traditional sense, but just functions. Here we give a brief overview of the language, which will give the chance to introduce concepts central to the analysis of all the following calculi. The exposition follows the one found in chapter 5 of \cite{Queinnec2003}. The syntax of $\lambda$-terms consists of three things: variables, abstractions, and applications: \mydesc{syntax}{ }{ $ \begin{array}{r@{\ }c@{\ }l} \mytmsyn & ::= & \myb{x} \mysynsep \myabs{\myb{x}}{\mytmsyn} \mysynsep (\myapp{\mytmsyn}{\mytmsyn}) \\ x & \in & \text{Some enumerable set of symbols} \end{array} $ } Parenthesis will be omitted in the usual way: $\myapp{\myapp{\mytmt}{\mytmm}}{\mytmn} = \myapp{(\myapp{\mytmt}{\mytmm})}{\mytmn}$. Abstractions roughly corresponds to functions, and their semantics is more formally explained by the $\beta$-reduction rule: \mydesc{reduction:}{\mytmsyn \myred \mytmsyn}{ $ \begin{array}{l} \myapp{(\myabs{\myb{x}}{\mytmm})}{\mytmn} \myred \mysub{\mytmm}{\myb{x}}{\mytmn}\text{, where} \\ \myind{1} \begin{array}{l@{\ }c@{\ }l} \mysub{\myb{x}}{\myb{x}}{\mytmn} & = & \mytmn \\ \mysub{\myb{y}}{\myb{x}}{\mytmn} & = & y\text{, with } \myb{x} \neq y \\ \mysub{(\myapp{\mytmt}{\mytmm})}{\myb{x}}{\mytmn} & = & (\myapp{\mysub{\mytmt}{\myb{x}}{\mytmn}}{\mysub{\mytmm}{\myb{x}}{\mytmn}}) \\ \mysub{(\myabs{\myb{x}}{\mytmm})}{\myb{x}}{\mytmn} & = & \myabs{\myb{x}}{\mytmm} \\ \mysub{(\myabs{\myb{y}}{\mytmm})}{\myb{x}}{\mytmn} & = & \myabs{\myb{z}}{\mysub{\mysub{\mytmm}{\myb{y}}{\myb{z}}}{\myb{x}}{\mytmn}}, \\ \multicolumn{3}{l}{\myind{1} \text{with $\myb{x} \neq \myb{y}$ and $\myb{z}$ not free in $\myapp{\mytmm}{\mytmn}$}} \end{array} \end{array} $ } The care required during substituting variables for terms is required to avoid name capturing. We will use substitution in the future for other name-binding constructs assuming similar precautions. These few elements are of remarkable expressiveness, and in fact Turing complete. As a corollary, we must be able to devise a term that reduces forever (`loops' in imperative terms): \[ (\myapp{\omega}{\omega}) \myred (\myapp{\omega}{\omega}) \myred \cdots \text{, with $\omega = \myabs{x}{\myapp{x}{x}}$} \] A \emph{redex} is a term that can be reduced. In the untyped $\lambda$-calculus this will be the case for an application in which the first term is an abstraction, but in general we call aterm reducible if it appears to the left of a reduction rule. When a term contains no redexes it's said to be in \emph{normal form}. Given the observation above, not all terms reduce to a normal forms: we call the ones that do \emph{normalising}, and the ones that don't \emph{non-normalising}. The reduction rule presented is not syntax directed, but \emph{evaluation strategies} can be employed to reduce term systematically. Common evaluation strategies include \emph{call by value} (or \emph{strict}), where arguments of abstractions are reduced before being applied to the abstraction; and conversely \emph{call by name} (or \emph{lazy}), where we reduce only when we need to do so to proceed---in other words when we have an application where the function is still not a $\lambda$. In both these reduction strategies we never reduce under an abstraction: for this reason a weaker form of normalisation is used, where both abstractions and normal forms are said to be in \emph{weak head normal form}. \subsection{The simply typed $\lambda$-calculus} A convenient way to `discipline' and reason about $\lambda$-terms is to assign \emph{types} to them, and then check that the terms that we are forming make sense given our typing rules \citep{Curry1934}. The first most basic instance of this idea takes the name of \emph{simply typed $\lambda$ calculus}, whose rules are shown in figure \ref{fig:stlc}. Our types contain a set of \emph{type variables} $\Phi$, which might correspond to some `primitive' types; and $\myarr$, the type former for `arrow' types, the types of functions. The language is explicitly typed: when we bring a variable into scope with an abstraction, we explicitly declare its type. Reduction is unchanged from the untyped $\lambda$-calculus. \begin{figure}[t] \mydesc{syntax}{ }{ $ \begin{array}{r@{\ }c@{\ }l} \mytmsyn & ::= & \myb{x} \mysynsep \myabss{\myb{x}}{\mytysyn}{\mytmsyn} \mysynsep (\myapp{\mytmsyn}{\mytmsyn}) \\ \mytysyn & ::= & \myse{\phi} \mysynsep \mytysyn \myarr \mytysyn \mysynsep \\ \myb{x} & \in & \text{Some enumerable set of symbols} \\ \myse{\phi} & \in & \Phi \end{array} $ } \mydesc{typing:}{\myjud{\mytmsyn}{\mytysyn}}{ \begin{tabular}{ccc} \AxiomC{$\myctx(x) = A$} \UnaryInfC{$\myjud{\myb{x}}{A}$} \DisplayProof & \AxiomC{$\myjudd{\myctx;\myb{x} : A}{\mytmt}{\mytyb}$} \UnaryInfC{$\myjud{\myabss{x}{A}{\mytmt}}{\mytyb}$} \DisplayProof & \AxiomC{$\myjud{\mytmm}{\mytya \myarr \mytyb}$} \AxiomC{$\myjud{\mytmn}{\mytya}$} \BinaryInfC{$\myjud{\myapp{\mytmm}{\mytmn}}{\mytyb}$} \DisplayProof \end{tabular} } \caption{Syntax and typing rules for the STLC. Reduction is unchanged from the untyped $\lambda$-calculus.} \label{fig:stlc} \end{figure} In the typing rules, a context $\myctx$ is used to store the types of bound variables: $\myctx; \myb{x} : \mytya$ adds a variable to the context and $\myctx(x)$ returns the type of the rightmost occurrence of $x$. This typing system takes the name of `simply typed lambda calculus' (STLC), and enjoys a number of properties. Two of them are expected in most type systems \citep{Pierce2002}: \begin{description} \item[Progress] A well-typed term is not stuck---it is either a variable, or its constructor does not appear on the left of the $\myred$ relation (currently only $\lambda$), or it can take a step according to the evaluation rules. \item[Preservation] If a well-typed term takes a step of evaluation, then the resulting term is also well-typed, and preserves the previous type. Also known as \emph{subject reduction}. \end{description} However, STLC buys us much more: every well-typed term is normalising \citep{Tait1967}. It is easy to see that we can't fill the blanks if we want to give types to the non-normalising term shown before: \begin{equation*} \myapp{(\myabss{\myb{x}}{\myhole{?}}{\myapp{\myb{x}}{\myb{x}}})}{(\myabss{\myb{x}}{\myhole{?}}{\myapp{\myb{x}}{\myb{x}}})} \end{equation*} This makes the STLC Turing incomplete. We can recover the ability to loop by adding a combinator that recurses: \noindent \begin{minipage}{0.5\textwidth} \mydesc{syntax}{ } { $ \mytmsyn ::= \cdots b \mysynsep \myfix{\myb{x}}{\mytysyn}{\mytmsyn} $ \vspace{0.4cm} } \end{minipage} \begin{minipage}{0.5\textwidth} \mydesc{typing:}{\myjud{\mytmsyn}{\mytysyn}} { \AxiomC{$\myjudd{\myctx; \myb{x} : \mytya}{\mytmt}{\mytya}$} \UnaryInfC{$\myjud{\myfix{\myb{x}}{\mytya}{\mytmt}}{\mytya}$} \DisplayProof } \end{minipage} \mydesc{reduction:}{\myjud{\mytmsyn}{\mytmsyn}}{ $ \myfix{\myb{x}}{\mytya}{\mytmt} \myred \mysub{\mytmt}{\myb{x}}{(\myfix{\myb{x}}{\mytya}{\mytmt})}$ } This will deprive us of normalisation, which is a particularly bad thing if we want to use the STLC as described in the next section. \subsection{The Curry-Howard correspondence} It turns out that the STLC can be seen a natural deduction system for intuitionistic propositional logic. Terms are proofs, and their types are the propositions they prove. This remarkable fact is known as the Curry-Howard correspondence, or isomorphism. The arrow ($\myarr$) type corresponds to implication. If we wish to prove that that $(\mytya \myarr \mytyb) \myarr (\mytyb \myarr \mytycc) \myarr (\mytya \myarr \mytycc)$, all we need to do is to devise a $\lambda$-term that has the correct type: \[ \myabss{\myb{f}}{(\mytya \myarr \mytyb)}{\myabss{\myb{g}}{(\mytyb \myarr \mytycc)}{\myabss{\myb{x}}{\mytya}{\myapp{\myb{g}}{(\myapp{\myb{f}}{\myb{x}})}}}} \] That is, function composition. Going beyond arrow types, we can extend our bare lambda calculus with useful types to represent other logical constructs, as shown in figure \ref{fig:natded}. \begin{figure}[t] \mydesc{syntax}{ }{ $ \begin{array}{r@{\ }c@{\ }l} \mytmsyn & ::= & \cdots \\ & | & \mytt \mysynsep \myapp{\myabsurd{\mytysyn}}{\mytmsyn} \\ & | & \myapp{\myleft{\mytysyn}}{\mytmsyn} \mysynsep \myapp{\myright{\mytysyn}}{\mytmsyn} \mysynsep \myapp{\mycase{\mytmsyn}{\mytmsyn}}{\mytmsyn} \\ & | & \mypair{\mytmsyn}{\mytmsyn} \mysynsep \myapp{\myfst}{\mytmsyn} \mysynsep \myapp{\mysnd}{\mytmsyn} \\ \mytysyn & ::= & \cdots \mysynsep \myunit \mysynsep \myempty \mysynsep \mytmsyn \mysum \mytmsyn \mysynsep \mytysyn \myprod \mytysyn \end{array} $ } \mydesc{reduction:}{\mytmsyn \myred \mytmsyn}{ \begin{tabular}{cc} $ \begin{array}{l@{ }l@{\ }c@{\ }l} \myapp{\mycase{\mytmm}{\mytmn}}{(\myapp{\myleft{\mytya} &}{\mytmt})} & \myred & \myapp{\mytmm}{\mytmt} \\ \myapp{\mycase{\mytmm}{\mytmn}}{(\myapp{\myright{\mytya} &}{\mytmt})} & \myred & \myapp{\mytmn}{\mytmt} \end{array} $ & $ \begin{array}{l@{ }l@{\ }c@{\ }l} \myapp{\myfst &}{\mypair{\mytmm}{\mytmn}} & \myred & \mytmm \\ \myapp{\mysnd &}{\mypair{\mytmm}{\mytmn}} & \myred & \mytmn \end{array} $ \end{tabular} } \mydesc{typing:}{\myjud{\mytmsyn}{\mytysyn}}{ \begin{tabular}{cc} \AxiomC{\phantom{$\myjud{\mytmt}{\myempty}$}} \UnaryInfC{$\myjud{\mytt}{\myunit}$} \DisplayProof & \AxiomC{$\myjud{\mytmt}{\myempty}$} \UnaryInfC{$\myjud{\myapp{\myabsurd{\mytya}}{\mytmt}}{\mytya}$} \DisplayProof \end{tabular} \myderivsp \begin{tabular}{cc} \AxiomC{$\myjud{\mytmt}{\mytya}$} \UnaryInfC{$\myjud{\myapp{\myleft{\mytyb}}{\mytmt}}{\mytya \mysum \mytyb}$} \DisplayProof & \AxiomC{$\myjud{\mytmt}{\mytyb}$} \UnaryInfC{$\myjud{\myapp{\myright{\mytya}}{\mytmt}}{\mytya \mysum \mytyb}$} \DisplayProof \end{tabular} \myderivsp \begin{tabular}{cc} \AxiomC{$\myjud{\mytmm}{\mytya \myarr \mytyb}$} \AxiomC{$\myjud{\mytmn}{\mytya \myarr \mytycc}$} \AxiomC{$\myjud{\mytmt}{\mytya \mysum \mytyb}$} \TrinaryInfC{$\myjud{\myapp{\mycase{\mytmm}{\mytmn}}{\mytmt}}{\mytycc}$} \DisplayProof \end{tabular} \myderivsp \begin{tabular}{ccc} \AxiomC{$\myjud{\mytmm}{\mytya}$} \AxiomC{$\myjud{\mytmn}{\mytyb}$} \BinaryInfC{$\myjud{\mypair{\mytmm}{\mytmn}}{\mytya \myprod \mytyb}$} \DisplayProof & \AxiomC{$\myjud{\mytmt}{\mytya \myprod \mytyb}$} \UnaryInfC{$\myjud{\myapp{\myfst}{\mytmt}}{\mytya}$} \DisplayProof & \AxiomC{$\myjud{\mytmt}{\mytya \myprod \mytyb}$} \UnaryInfC{$\myjud{\myapp{\mysnd}{\mytmt}}{\mytyb}$} \DisplayProof \end{tabular} } \caption{Rules for the extendend STLC. Only the new features are shown, all the rules and syntax for the STLC apply here too.} \label{fig:natded} \end{figure} Tagged unions (or sums, or coproducts---$\mysum$ here, \texttt{Either} in Haskell) correspond to disjunctions, and dually tuples (or pairs, or products---$\myprod$ here, tuples in Haskell) correspond to conjunctions. This is apparent looking at the ways to construct and destruct the values inhabiting those types: for $\mysum$ $\myleft{ }$ and $\myright{ }$ correspond to $\vee$ introduction, and $\mycase{\myarg}{\myarg}$ to $\vee$ elimination; for $\myprod$ $\mypair{\myarg}{\myarg}$ corresponds to $\wedge$ introduction, $\myfst$ and $\mysnd$ to $\wedge$ elimination. The trivial type $\myunit$ corresponds to the logical $\top$, and dually $\myempty$ corresponds to the logical $\bot$. $\myunit$ has one introduction rule ($\mytt$), and thus one inhabitant; and no eliminators. $\myempty$ has no introduction rules, and thus no inhabitants; and one eliminator ($\myabsurd{ }$), corresponding to the logical \emph{ex falso quodlibet}. With these rules, our STLC now looks remarkably similar in power and use to the natural deduction we already know. $\myneg \mytya$ can be expressed as $\mytya \myarr \myempty$. However, there is an important omission: there is no term of the type $\mytya \mysum \myneg \mytya$ (excluded middle), or equivalently $\myneg \myneg \mytya \myarr \mytya$ (double negation), or indeed any term with a type equivalent to those. This has a considerable effect on our logic and it's no coincidence, since there is no obvious computational behaviour for laws like the excluded middle. Theories of this kind are called \emph{intuitionistic}, or \emph{constructive}, and all the systems analysed will have this characteristic since they build on the foundation of the STLC\footnote{There is research to give computational behaviour to classical logic, but I will not touch those subjects.}. As in logic, if we want to keep our system consistent, we must make sure that no closed terms (in other words terms not under a $\lambda$) inhabit $\myempty$. The variant of STLC presented here is indeed consistent, a result that follows from the fact that it is normalising. % TODO explain Going back to our $\mysyn{fix}$ combinator, it is easy to see how it ruins our desire for consistency. The following term works for every type $\mytya$, including bottom: \[ (\myfix{\myb{x}}{\mytya}{\myb{x}}) : \mytya \] \subsection{Inductive data} \label{sec:ind-data} To make the STLC more useful as a programming language or reasoning tool it is common to include (or let the user define) inductive data types. These comprise of a type former, various constructors, and an eliminator (or destructor) that serves as primitive recursor. For example, we might add a $\mylist$ type constructor, along with an `empty list' ($\mynil{ }$) and `cons cell' ($\mycons$) constructor. The eliminator for lists will be the usual folding operation ($\myfoldr$). See figure \ref{fig:list}. \begin{figure}[h] \mydesc{syntax}{ }{ $ \begin{array}{r@{\ }c@{\ }l} \mytmsyn & ::= & \cdots \mysynsep \mynil{\mytysyn} \mysynsep \mytmsyn \mycons \mytmsyn \mysynsep \myapp{\myapp{\myapp{\myfoldr}{\mytmsyn}}{\mytmsyn}}{\mytmsyn} \\ \mytysyn & ::= & \cdots \mysynsep \myapp{\mylist}{\mytysyn} \end{array} $ } \mydesc{reduction:}{\mytmsyn \myred \mytmsyn}{ $ \begin{array}{l@{\ }c@{\ }l} \myapp{\myapp{\myapp{\myfoldr}{\myse{f}}}{\mytmt}}{\mynil{\mytya}} & \myred & \mytmt \\ \myapp{\myapp{\myapp{\myfoldr}{\myse{f}}}{\mytmt}}{(\mytmm \mycons \mytmn)} & \myred & \myapp{\myapp{\myse{f}}{\mytmm}}{(\myapp{\myapp{\myapp{\myfoldr}{\myse{f}}}{\mytmt}}{\mytmn})} \end{array} $ } \mydesc{typing:}{\myjud{\mytmsyn}{\mytysyn}}{ \begin{tabular}{cc} \AxiomC{\phantom{$\myjud{\mytmm}{\mytya}$}} \UnaryInfC{$\myjud{\mynil{\mytya}}{\myapp{\mylist}{\mytya}}$} \DisplayProof & \AxiomC{$\myjud{\mytmm}{\mytya}$} \AxiomC{$\myjud{\mytmn}{\myapp{\mylist}{\mytya}}$} \BinaryInfC{$\myjud{\mytmm \mycons \mytmn}{\myapp{\mylist}{\mytya}}$} \DisplayProof \end{tabular} \myderivsp \AxiomC{$\myjud{\mysynel{f}}{\mytya \myarr \mytyb \myarr \mytyb}$} \AxiomC{$\myjud{\mytmm}{\mytyb}$} \AxiomC{$\myjud{\mytmn}{\myapp{\mylist}{\mytya}}$} \TrinaryInfC{$\myjud{\myapp{\myapp{\myapp{\myfoldr}{\mysynel{f}}}{\mytmm}}{\mytmn}}{\mytyb}$} \DisplayProof } \caption{Rules for lists in the STLC.} \label{fig:list} \end{figure} In section \ref{sec:well-order} we will see how to give a general account of inductive data. %TODO does this make sense to have here? \section{Intuitionistic Type Theory} \label{sec:itt} \subsection{Extending the STLC} The STLC can be made more expressive in various ways. \cite{Barendregt1991} succinctly expressed geometrically how we can add expressivity: $$ \xymatrix@!0@=1.5cm{ & \lambda\omega \ar@{-}[rr]\ar@{-}'[d][dd] & & \lambda C \ar@{-}[dd] \\ \lambda2 \ar@{-}[ur]\ar@{-}[rr]\ar@{-}[dd] & & \lambda P2 \ar@{-}[ur]\ar@{-}[dd] \\ & \lambda\underline\omega \ar@{-}'[r][rr] & & \lambda P\underline\omega \\ \lambda{\to} \ar@{-}[rr]\ar@{-}[ur] & & \lambda P \ar@{-}[ur] } $$ Here $\lambda{\to}$, in the bottom left, is the STLC. From there can move along 3 dimensions: \begin{description} \item[Terms depending on types (towards $\lambda{2}$)] We can quantify over types in our type signatures. For example, we can define a polymorphic identity function: \[\displaystyle (\myabss{\myb{A}}{\mytyp}{\myabss{\myb{x}}{\myb{A}}{\myb{x}}}) : (\myb{A} : \mytyp) \myarr \myb{A} \myarr \myb{A} \] The first and most famous instance of this idea has been System F. This form of polymorphism and has been wildly successful, also thanks to a well known inference algorithm for a restricted version of System F known as Hindley-Milner. Languages like Haskell and SML are based on this discipline. \item[Types depending on types (towards $\lambda{\underline{\omega}}$)] We have type operators. For example we could define a function that given types $R$ and $\mytya$ forms the type that represents a value of type $\mytya$ in continuation passing style: \[\displaystyle(\myabss{\myb{A} \myar \myb{R}}{\mytyp}{(\myb{A} \myarr \myb{R}) \myarr \myb{R}}) : \mytyp \myarr \mytyp \myarr \mytyp\] \item[Types depending on terms (towards $\lambda{P}$)] Also known as `dependent types', give great expressive power. For example, we can have values of whose type depend on a boolean: \[\displaystyle(\myabss{\myb{x}}{\mybool}{\myite{\myb{x}}{\mynat}{\myrat}}) : \mybool \myarr \mytyp\] \end{description} All the systems preserve the properties that make the STLC well behaved. The system we are going to focus on, Intuitionistic Type Theory, has all of the above additions, and thus would sit where $\lambda{C}$ sits in the `$\lambda$-cube'. It will serve as the logical `core' of all the other extensions that we will present and ultimately our implementation of a similar logic. \subsection{A Bit of History} Logic frameworks and programming languages based on type theory have a long history. Per Martin-L\"{o}f described the first version of his theory in 1971, but then revised it since the original version was inconsistent due to its impredicativity\footnote{In the early version there was only one universe $\mytyp$ and $\mytyp : \mytyp$, see section \ref{sec:term-types} for an explanation on why this causes problems.}. For this reason he gave a revised and consistent definition later \citep{Martin-Lof1984}. A related development is the polymorphic $\lambda$-calculus, and specifically the previously mentioned System F, which was developed independently by Girard and Reynolds. An overview can be found in \citep{Reynolds1994}. The surprising fact is that while System F is impredicative it is still consistent and strongly normalising. \cite{Coquand1986} further extended this line of work with the Calculus of Constructions (CoC). Most widely used interactive theorem provers are based on ITT. Popular ones include Agda \citep{Norell2007, Bove2009}, Coq \citep{Coq}, and Epigram \citep{McBride2004, EpigramTut}. \subsection{A note on inference} % TODO do this, adding links to the sections about bidi type checking and % implicit universes. In the following text I will often omit explicit typing for abstractions or Moreover, I will use $\mytyp$ without bothering to specify a universe, with the silent assumption that the definition is consistent regarding to the hierarchy. \subsection{A simple type theory} \label{sec:core-tt} The calculus I present follows the exposition in \citep{Thompson1991}, and is quite close to the original formulation of predicative ITT as found in \citep{Martin-Lof1984}. The system's syntax and reduction rules are presented in their entirety in figure \ref{fig:core-tt-syn}. The typing rules are presented piece by piece. An Agda rendition of the presented theory and all the examples is reproduced in appendix \ref{app:agda-itt}. \begin{figure}[t] \mydesc{syntax}{ }{ $ \begin{array}{r@{\ }c@{\ }l} \mytmsyn & ::= & \myb{x} \mysynsep \mytyp_{l} \mysynsep \myunit \mysynsep \mytt \mysynsep \myempty \mysynsep \myapp{\myabsurd{\mytmsyn}}{\mytmsyn} \\ & | & \mybool \mysynsep \mytrue \mysynsep \myfalse \mysynsep \myitee{\mytmsyn}{\myb{x}}{\mytmsyn}{\mytmsyn}{\mytmsyn} \\ & | & \myfora{\myb{x}}{\mytmsyn}{\mytmsyn} \mysynsep \myabss{\myb{x}}{\mytmsyn}{\mytmsyn} \mysynsep (\myapp{\mytmsyn}{\mytmsyn}) \\ & | & \myexi{\myb{x}}{\mytmsyn}{\mytmsyn} \mysynsep \mypairr{\mytmsyn}{\myb{x}}{\mytmsyn}{\mytmsyn} \\ & | & \myapp{\myfst}{\mytmsyn} \mysynsep \myapp{\mysnd}{\mytmsyn} \\ & | & \myw{\myb{x}}{\mytmsyn}{\mytmsyn} \mysynsep \mytmsyn \mynode{\myb{x}}{\mytmsyn} \mytmsyn \\ & | & \myrec{\mytmsyn}{\myb{x}}{\mytmsyn}{\mytmsyn} \\ l & \in & \mathbb{N} \end{array} $ } \mydesc{reduction:}{\mytmsyn \myred \mytmsyn}{ \begin{tabular}{ccc} $ \begin{array}{l@{ }l@{\ }c@{\ }l} \myitee{\mytrue &}{\myb{x}}{\myse{P}}{\mytmm}{\mytmn} & \myred & \mytmm \\ \myitee{\myfalse &}{\myb{x}}{\myse{P}}{\mytmm}{\mytmn} & \myred & \mytmn \\ \end{array} $ & $ \myapp{(\myabss{\myb{x}}{\mytya}{\mytmm})}{\mytmn} \myred \mysub{\mytmm}{\myb{x}}{\mytmn} $ & $ \begin{array}{l@{ }l@{\ }c@{\ }l} \myapp{\myfst &}{\mypair{\mytmm}{\mytmn}} & \myred & \mytmm \\ \myapp{\mysnd &}{\mypair{\mytmm}{\mytmn}} & \myred & \mytmn \end{array} $ \end{tabular} \myderivsp $ \myrec{(\myse{s} \mynode{\myb{x}}{\myse{T}} \myse{f})}{\myb{y}}{\myse{P}}{\myse{p}} \myred \myapp{\myapp{\myapp{\myse{p}}{\myse{s}}}{\myse{f}}}{(\myabss{\myb{t}}{\mysub{\myse{T}}{\myb{x}}{\myse{s}}}{ \myrec{\myapp{\myse{f}}{\myb{t}}}{\myb{y}}{\myse{P}}{\mytmt} })} $ } \caption{Syntax and reduction rules for our type theory.} \label{fig:core-tt-syn} \end{figure} \subsubsection{Types are terms, some terms are types} \label{sec:term-types} \mydesc{typing:}{\myjud{\mytmsyn}{\mytmsyn}}{ \begin{tabular}{cc} \AxiomC{$\myjud{\mytmt}{\mytya}$} \AxiomC{$\mytya \mydefeq \mytyb$} \BinaryInfC{$\myjud{\mytmt}{\mytyb}$} \DisplayProof & \AxiomC{\phantom{$\myjud{\mytmt}{\mytya}$}} \UnaryInfC{$\myjud{\mytyp_l}{\mytyp_{l + 1}}$} \DisplayProof \end{tabular} } The first thing to notice is that a barrier between values and types that we had in the STLC is gone: values can appear in types, and the two are treated uniformly in the syntax. While the usefulness of doing this will become clear soon, a consequence is that since types can be the result of computation, deciding type equality is not immediate as in the STLC. For this reason we define \emph{definitional equality}, $\mydefeq$, as the congruence relation extending $\myred$---moreover, when comparing types syntactically we do it up to renaming of bound names ($\alpha$-renaming). For example under this discipline we will find that \[ \myabss{\myb{x}}{\mytya}{\myb{x}} \mydefeq \myabss{\myb{y}}{\mytya}{\myb{y}} \] Types that are definitionally equal can be used interchangeably. Here the `conversion' rule is not syntax directed, however we will see how it is possible to employ $\myred$ to decide term equality in a systematic way. % TODO add section Another thing to notice is that considering the need to reduce terms to decide equality, it is essential for a dependently type system to be terminating and confluent for type checking to be decidable. Moreover, we specify a \emph{type hierarchy} to talk about `large' types: $\mytyp_0$ will be the type of types inhabited by data: $\mybool$, $\mynat$, $\mylist$, etc. $\mytyp_1$ will be the type of $\mytyp_0$, and so on---for example we have $\mytrue : \mybool : \mytyp_0 : \mytyp_1 : \cdots$. Each type `level' is often called a universe in the literature. While it is possible, to simplify things by having only one universe $\mytyp$ with $\mytyp : \mytyp$, this plan is inconsistent for much the same reason that impredicative na\"{\i}ve set theory is \citep{Hurkens1995}. Moreover, various techniques can be employed to lift the burden of explicitly handling universes. % TODO add sectioon about universes \subsubsection{Contexts} \begin{minipage}{0.5\textwidth} \mydesc{context validity:}{\myvalid{\myctx}}{ \begin{tabular}{cc} \AxiomC{\phantom{$\myjud{\mytya}{\mytyp_l}$}} \UnaryInfC{$\myvalid{\myemptyctx}$} \DisplayProof & \AxiomC{$\myjud{\mytya}{\mytyp_l}$} \UnaryInfC{$\myvalid{\myctx ; \myb{x} : \mytya}$} \DisplayProof \end{tabular} } \end{minipage} \begin{minipage}{0.5\textwidth} \mydesc{typing:}{\myjud{\mytmsyn}{\mytmsyn}}{ \AxiomC{$\myctx(x) = \mytya$} \UnaryInfC{$\myjud{\myb{x}}{\mytya}$} \DisplayProof } \end{minipage} \vspace{0.1cm} We need to refine the notion context to make sure that every variable appearing is typed correctly, or that in other words each type appearing in the context is indeed a type and not a value. In every other rule, if no premises are present, we assume the context in the conclusion to be valid. Then we can re-introduce the old rule to get the type of a variable for a context. \subsubsection{$\myunit$, $\myempty$} \mydesc{typing:}{\myjud{\mytmsyn}{\mytmsyn}}{ \begin{tabular}{ccc} \AxiomC{\phantom{$\myjud{\mytya}{\mytyp_l}$}} \UnaryInfC{$\myjud{\myunit}{\mytyp_0}$} \noLine \UnaryInfC{$\myjud{\myempty}{\mytyp_0}$} \DisplayProof & \AxiomC{\phantom{$\myjud{\mytya}{\mytyp_l}$}} \UnaryInfC{$\myjud{\mytt}{\myunit}$} \noLine \UnaryInfC{\phantom{$\myjud{\myempty}{\mytyp_0}$}} \DisplayProof & \AxiomC{$\myjud{\mytmt}{\myempty}$} \AxiomC{$\myjud{\mytya}{\mytyp_l}$} \BinaryInfC{$\myjud{\myapp{\myabsurd{\mytya}}{\mytmt}}{\mytya}$} \noLine \UnaryInfC{\phantom{$\myjud{\myempty}{\mytyp_0}$}} \DisplayProof \end{tabular} } Nothing surprising here: $\myunit$ and $\myempty$ are unchanged from the STLC, with the added rules to type $\myunit$ and $\myempty$ themselves, and to make sure that we are invoking $\myabsurd{}$ over a type. \subsubsection{$\mybool$, and dependent $\myfun{if}$} \mydesc{typing:}{\myjud{\mytmsyn}{\mytmsyn}}{ \begin{tabular}{ccc} \AxiomC{} \UnaryInfC{$\myjud{\mybool}{\mytyp_0}$} \DisplayProof & \AxiomC{} \UnaryInfC{$\myjud{\mytrue}{\mybool}$} \DisplayProof & \AxiomC{} \UnaryInfC{$\myjud{\myfalse}{\mybool}$} \DisplayProof \end{tabular} \myderivsp \AxiomC{$\myjud{\mytmt}{\mybool}$} \AxiomC{$\myjudd{\myctx : \mybool}{\mytya}{\mytyp_l}$} \noLine \BinaryInfC{$\myjud{\mytmm}{\mysub{\mytya}{x}{\mytrue}}$ \hspace{0.7cm} $\myjud{\mytmn}{\mysub{\mytya}{x}{\myfalse}}$} \UnaryInfC{$\myjud{\myitee{\mytmt}{\myb{x}}{\mytya}{\mytmm}{\mytmn}}{\mysub{\mytya}{\myb{x}}{\mytmt}}$} \DisplayProof } With booleans we get the first taste of `dependent' in `dependent types'. While the two introduction rules ($\mytrue$ and $\myfalse$) are not surprising, the typing rules for $\myfun{if}$ are. In most strongly typed languages we expect the branches of an $\myfun{if}$ statements to be of the same type, to preserve subject reduction, since execution could take both paths. This is a pity, since the type system does not reflect the fact that in each branch we gain knowledge on the term we are branching on. Which means that programs along the lines of \begin{verbatim} if null xs then head xs else 0 \end{verbatim} are a necessary, well typed, danger. However, in a more expressive system, we can do better: the branches' type can depend on the value of the scrutinised boolean. This is what the typing rule expresses: the user provides a type $\mytya$ ranging over an $\myb{x}$ representing the scrutinised boolean type, and the branches are typechecked with the updated knowledge on the value of $\myb{x}$. \subsubsection{$\myarr$, or dependent function} \mydesc{typing:}{\myjud{\mytmsyn}{\mytmsyn}}{ \AxiomC{$\myjud{\mytya}{\mytyp_{l_1}}$} \AxiomC{$\myjudd{\myctx;\myb{x} : \mytya}{\mytyb}{\mytyp_{l_2}}$} \BinaryInfC{$\myjud{\myfora{\myb{x}}{\mytya}{\mytyb}}{\mytyp_{l_1 \mylub l_2}}$} \DisplayProof \myderivsp \begin{tabular}{cc} \AxiomC{$\myjudd{\myctx; \myb{x} : \mytya}{\mytmt}{\mytyb}$} \UnaryInfC{$\myjud{\myabss{\myb{x}}{\mytya}{\mytmt}}{\myfora{\myb{x}}{\mytya}{\mytyb}}$} \DisplayProof & \AxiomC{$\myjud{\mytmm}{\myfora{\myb{x}}{\mytya}{\mytyb}}$} \AxiomC{$\myjud{\mytmn}{\mytya}$} \BinaryInfC{$\myjud{\myapp{\mytmm}{\mytmn}}{\mysub{\mytyb}{\myb{x}}{\mytmn}}$} \DisplayProof \end{tabular} } Dependent functions are one of the two key features that perhaps most characterise dependent types---the other being dependent products. With dependent functions, the result type can depend on the value of the argument. This feature, together with the fact that the result type might be a type itself, brings a lot of interesting possibilities. Following this intuition, in the introduction rule, the return type is typechecked in a context with an abstracted variable of lhs' type, and in the elimination rule the actual argument is substituted in the return type. Keeping the correspondence with logic alive, dependent functions are much like universal quantifiers ($\forall$) in logic. For example, assuming that we have lists and natural numbers in our language, using dependent functions we would be able to write: \[ \begin{array}{c@{\ }c@{\ }l@{\ }} \myfun{length} & : & (\myb{A} {:} \mytyp_0) \myarr \myapp{\mylist}{\myb{A}} \myarr \mynat \\ \myarg \myfun{$>$} \myarg & : & \mynat \myarr \mynat \myarr \mytyp_0 \\ \myfun{head} & : & (\myb{A} {:} \mytyp_0) \myarr (\myb{l} {:} \myapp{\mylist}{\myb{A}}) \myarr \myapp{\myapp{\myfun{length}}{\myb{A}}}{\myb{l}} \mathrel{\myfun{>}} 0 \myarr \myb{A} \end{array} \] \myfun{length} is the usual polymorphic length function. $\myfun{>}$ is a function that takes two naturals and returns a type: if the lhs is greater then the rhs, $\myunit$ is returned, $\myempty$ otherwise. This way, we can express a `non-emptyness' condition in $\myfun{head}$, by including a proof that the length of the list argument is non-zero. This allows us to rule out the `empty list' case, so that we can safely return the first element. Again, we need to make sure that the type hierarchy is respected, which is the reason why a type formed by $\myarr$ will live in the least upper bound of the levels of argument and return type. This trend will continue with the other type-level binders, $\myprod$ and $\mytyc{W}$. \subsubsection{$\myprod$, or dependent product} \mydesc{typing:}{\myjud{\mytmsyn}{\mytmsyn}}{ \AxiomC{$\myjud{\mytya}{\mytyp_{l_1}}$} \AxiomC{$\myjudd{\myctx;\myb{x} : \mytya}{\mytyb}{\mytyp_{l_2}}$} \BinaryInfC{$\myjud{\myexi{\myb{x}}{\mytya}{\mytyb}}{\mytyp_{l_1 \mylub l_2}}$} \DisplayProof \myderivsp \begin{tabular}{cc} \AxiomC{$\myjud{\mytmm}{\mytya}$} \AxiomC{$\myjud{\mytmn}{\mysub{\mytyb}{\myb{x}}{\mytmm}}$} \BinaryInfC{$\myjud{\mypairr{\mytmm}{\myb{x}}{\mytyb}{\mytmn}}{\myexi{\myb{x}}{\mytya}{\mytyb}}$} \noLine \UnaryInfC{\phantom{$--$}} \DisplayProof & \AxiomC{$\myjud{\mytmt}{\myexi{\myb{x}}{\mytya}{\mytyb}}$} \UnaryInfC{$\hspace{0.7cm}\myjud{\myapp{\myfst}{\mytmt}}{\mytya}\hspace{0.7cm}$} \noLine \UnaryInfC{$\myjud{\myapp{\mysnd}{\mytmt}}{\mysub{\mytyb}{\myb{x}}{\myapp{\myfst}{\mytmt}}}$} \DisplayProof \end{tabular} } If dependent functions are a generalisation of $\myarr$ in the STLC, dependent products are a generalisation of $\myprod$ in the STLC. The improvement is that the second element's type can depend on the value of the first element. The corrispondence with logic is through the existential quantifier: $\exists x \in \mathbb{N}. even(x)$ can be expressed as $\myexi{\myb{x}}{\mynat}{\myapp{\myfun{even}}{\myb{x}}}$. The first element will be a number, and the second evidence that the number is even. This highlights the fact that we are working in a constructive logic: if we have an existence proof, we can always ask for a witness. This means, for instance, that $\neg \forall \neg$ is not equivalent to $\exists$. \subsubsection{$\mytyc{W}$, or well-order} \label{sec:well-order} \mydesc{typing:}{\myjud{\mytmsyn}{\mytmsyn}}{ \AxiomC{$\myjud{\mytya}{\mytyp_{l_1}}$} \AxiomC{$\myjudd{\myctx;\myb{x} : \mytya}{\mytyb}{\mytyp_{l_2}}$} \BinaryInfC{$\myjud{\myw{\myb{x}}{\mytya}{\mytyb}}{\mytyp_{l_1 \mylub l_2}}$} \DisplayProof \myderivsp \AxiomC{$\myjud{\mytmt}{\mytya}$} \AxiomC{$\myjud{\mysynel{f}}{\mysub{\mytyb}{\myb{x}}{\mytmt} \myarr \myw{\myb{x}}{\mytya}{\mytyb}}$} \BinaryInfC{$\myjud{\mytmt \mynode{\myb{x}}{\mytyb} \myse{f}}{\myw{\myb{x}}{\mytya}{\mytyb}}$} \DisplayProof \myderivsp \AxiomC{$\myjud{\myse{u}}{\myw{\myb{x}}{\myse{S}}{\myse{T}}}$} \AxiomC{$\myjudd{\myctx; \myb{w} : \myw{\myb{x}}{\myse{S}}{\myse{T}}}{\myse{P}}{\mytyp_l}$} \noLine \BinaryInfC{$\myjud{\myse{p}}{ \myfora{\myb{s}}{\myse{S}}{\myfora{\myb{f}}{\mysub{\myse{T}}{\myb{x}}{\myse{s}} \myarr \myw{\myb{x}}{\myse{S}}{\myse{T}}}{(\myfora{\myb{t}}{\mysub{\myse{T}}{\myb{x}}{\myb{s}}}{\mysub{\myse{P}}{\myb{w}}{\myapp{\myb{f}}{\myb{t}}}}) \myarr \mysub{\myse{P}}{\myb{w}}{\myb{f}}}} }$} \UnaryInfC{$\myjud{\myrec{\myse{u}}{\myb{w}}{\myse{P}}{\myse{p}}}{\mysub{\myse{P}}{\myb{w}}{\myse{u}}}$} \DisplayProof } \section{The struggle for equality} \label{sec:equality} In the previous section we saw how a type checker (or a human) needs a notion of \emph{definitional equality}. Beyond this meta-theoretic notion, in this section we will explore the ways of expressing equality \emph{inside} the theory, as a reasoning tool available to the user. This area is the main concern of this thesis, and in general a very active research topic, since we do not have a fully satisfactory solution, yet. As in the previous section, everything presented is formalised in Agda in appendix \ref{app:agda-code}. \subsection{Propositional equality} \noindent \begin{minipage}{0.5\textwidth} \mydesc{syntax}{ }{ $ \begin{array}{r@{\ }c@{\ }l} \mytmsyn & ::= & \cdots \\ & | & \mytmsyn \mypeq{\mytmsyn} \mytmsyn \mysynsep \myapp{\myrefl}{\mytmsyn} \\ & | & \myjeq{\mytmsyn}{\mytmsyn}{\mytmsyn} \end{array} $ } \end{minipage} \begin{minipage}{0.5\textwidth} \mydesc{reduction:}{\mytmsyn \myred \mytmsyn}{ $ \myjeq{\myse{P}}{(\myapp{\myrefl}{\mytmm})}{\mytmn} \myred \mytmn $ \vspace{0.9cm} } \end{minipage} \mydesc{typing:}{\myjud{\mytmsyn}{\mytmsyn}}{ \AxiomC{$\myjud{\mytya}{\mytyp_l}$} \AxiomC{$\myjud{\mytmm}{\mytya}$} \AxiomC{$\myjud{\mytmn}{\mytya}$} \TrinaryInfC{$\myjud{\mytmm \mypeq{\mytya} \mytmn}{\mytyp_l}$} \DisplayProof \myderivsp \begin{tabular}{cc} \AxiomC{\phantom{$\myctx P \mytyp_l$}} \noLine \UnaryInfC{$\myjud{\mytmm}{\mytya}\hspace{1.1cm}\mytmm \mydefeq \mytmn$} \UnaryInfC{$\myjud{\myapp{\myrefl}{\mytmm}}{\mytmm \mypeq{\mytya} \mytmn}$} \DisplayProof & \AxiomC{$\myjud{\myse{P}}{\myfora{\myb{x}\ \myb{y}}{\mytya}{\myfora{q}{\myb{x} \mypeq{\mytya} \myb{y}}{\mytyp_l}}}$} \noLine \UnaryInfC{$\myjud{\myse{q}}{\mytmm \mypeq{\mytya} \mytmn}\hspace{1.1cm}\myjud{\myse{p}}{\myapp{\myapp{\myapp{\myse{P}}{\mytmm}}{\mytmm}}{(\myapp{\myrefl}{\mytmm})}}$} \UnaryInfC{$\myjud{\myjeq{\myse{P}}{\myse{q}}{\myse{p}}}{\myapp{\myapp{\myapp{\myse{P}}{\mytmm}}{\mytmn}}{q}}$} \DisplayProof \end{tabular} } To express equality between two terms inside ITT, the obvious way to do so is to have the equality construction to be a type-former. Here we present what has survived as the dominating form of equality in systems based on ITT up to the present day. Our type former is $\mypeq{\mytya}$, which given a type (in this case $\mytya$) relates equal terms of that type. $\mypeq{}$ has one introduction rule, $\myrefl$, which introduces an equality relation between definitionally equal terms---in the typing rule we display the term as `the same', meaning `the same up to $\mydefeq$'. % TODO maybe mention this earlier Finally, we have one eliminator for $\mypeq{}$, $\myjeqq$. $\myjeq{\myse{P}}{\myse{q}}{\myse{p}}$ takes \begin{itemize} \item $\myse{P}$, a predicate working with two terms of a certain type (say $\mytya$) and a proof of their equality \item $\myse{q}$, a proof that two terms in $\mytya$ (say $\myse{m}$ and $\myse{n}$) are equal \item and $\myse{p}$, an inhabitant of $\myse{P}$ applied to $\myse{m}$, plus the trivial proof by reflexivity showing that $\myse{m}$ is equal to itself \end{itemize} Given these ingredients, $\myjeqq$ retuns a member of $\myse{P}$ applied to $\mytmm$, $\mytmn$, and $\myse{q}$. In other words $\myjeqq$ takes a witness that $\myse{P}$ works with \emph{definitionally equal} terms, and returns a witness of $\myse{P}$ working with \emph{propositionally equal} terms. Invokations of $\myjeqq$ will vanish when the equality proofs will reduce to invocations to reflexivity, at which point the arguments must be definitionally equal, and thus the provided $\myapp{\myapp{\myapp{\myse{P}}{\mytmm}}{\mytmm}}{(\myapp{\myrefl}{\mytmm})}$ can be returned. While the $\myjeqq$ rule is slightly convoluted, ve can derive many more `friendly' rules from it, for example a more obvious `substitution' rule, that replaces equal for equal in predicates: \[ \begin{array}{l} (\myabs{\myb{A}\ \myb{P}\ \myb{x}\ \myb{y}\ \myb{q}\ \myb{p}}{ \myjeq{(\myabs{\myb{x}\ \myb{y}\ \myb{q}}{\myapp{\myb{P}}{\myb{y}}})}{\myb{q}}{\myb{p}}}) : \\ \myind{1} \myfora{\myb{A}}{\mytyp}{\myfora{\myb{P}}{\myb{A} \myarr \mytyp}{\myfora{\myb{x}\ \myb{y}}{\myb{A}}{\myb{x} \mypeq{\myb{A}} \myb{y} \myarr \myapp{\myb{P}}{\myb{x}} \myarr \myapp{\myb{P}}{\myb{y}}}}} \end{array} \] This rule is often called $\myfun{subst}$---here we will invoke it without specifying the type ($\myb{A}$) and the sides of the equality ($\myb{x},\myb{y}$). Once we have $\myfun{subst}$, we can easily prove more familiar laws regarding equality, such as symmetry, transitivity, and a congruence law: % TODO finish this \subsection{Common extensions} eta law congruence UIP \subsection{Limitations} \epigraph{\emph{Half of my time spent doing research involves thinking up clever schemes to avoid needing functional extensionality.}}{@larrytheliquid} However, propositional equality as described is quite restricted when reasoning about equality beyond the term structure, which is what definitional equality gives us (extension notwithstanding). The problem is best exemplified by \emph{function extensionality}. In mathematics, we would expect to be able to treat functions that give equal output for equal input as the same. When reasoning in a mechanised framework we ought to be able to do the same: in the end, without considering the operational behaviour, all functions equal extensionally are going to be replaceable with one another. However this is not the case, or in other words with the tools we have we have no term of type \[ \myfun{ext} : \myfora{\myb{A}\ \myb{B}}{\mytyp}{\myfora{\myb{f}\ \myb{g}}{ \myb{A} \myarr \myb{B}}{ (\myfora{\myb{x}}{\myb{A}}{\myapp{\myb{f}}{\myb{x}} \mypeq{\myb{B}} \myapp{\myb{g}}{\myb{x}}}) \myarr \myb{f} \mypeq{\myb{A} \myarr \myb{B}} \myb{g} } } \] To see why this is the case, consider the functions \[\myabs{\myb{x}}{0 \mathrel{\myfun{+}} \myb{x}}$ and $\myabs{\myb{x}}{\myb{x} \mathrel{\myfun{+}} 0}\] where $\myfun{+}$ is defined by recursion on the first argument, gradually destructing it to build up successors of the second argument. The two functions are clearly extensionally equal, and we can in fact prove that \[ \myfora{\myb{x}}{\mynat}{(0 \mathrel{\myfun{+}} \myb{x}) \mypeq{\mynat} (\myb{x} \mathrel{\myfun{+}} 0)} \] By analysis on the $\myb{x}$. However, the two functions are not definitionally equal, and thus we won't be able to get rid of the quantification. For the reasons above, theories that offer a propositional equality similar to what we presented are called \emph{intensional}, as opposed to \emph{extensional}. Most systems in wide use today (such as Agda, Coq and Epigram) are of this kind. This is quite an annoyance that often makes reasoning awkward to execute. It also extends to other fields, for example proving bisimulation between processes specified by coinduction, or in general proving equivalences based on the behaviour on a term. \subsection{Equality reflection} One way to `solve' this problem is by identifying propositional equality with definitional equality: \mydesc{typing:}{\myjud{\mytmsyn}{\mytmsyn}}{ \AxiomC{$\myjud{\myse{q}}{\mytmm \mypeq{\mytya} \mytmn}$} \UnaryInfC{$\myjud{\mytmm \mydefeq \mytmn}{\mytya}$} \DisplayProof } This rule takes the name of \emph{equality reflection}, and is a very different rule from the ones we saw up to now: it links a typing judgement internal to the type theory to a meta-theoretic judgement that the type checker uses to work with terms. It is easy to see the dangerous consequences that this causes: \begin{itemize} \item The rule is syntax directed, and the type checker is presumably expected to come up with equality proofs when needed. \item More worryingly, type checking becomes undecidable also because computing under false assumptions becomes unsafe. Consider for example \[ \myabss{\myb{q}}{\mytya \mypeq{\mytyp} (\mytya \myarr \mytya)}{\myhole{?}} \] Using the assumed proof in tandem with equality reflection we could easily write a classic Y combinator, sending the compiler into a loop. \end{itemize} Given these facts theories employing equality reflection, like NuPRL \citep{NuPRL}, carry the derivations that gave rise to each typing judgement to keep the systems manageable. % TODO more info, problems with that. For all its faults, equality reflection does allow us to prove extensionality, using the extensions we gave above. Assuming that $\myctx$ contains \[\myb{A}, \myb{B} : \mytyp; \myb{f}, \myb{g} : \myb{A} \myarr \myb{B}; \myb{q} : \myfora{\myb{x}}{\myb{A}}{\myapp{\myb{f}}{\myb{x}} \mypeq{} \myapp{\myb{g}}{\myb{x}}}\] We can then derive \begin{prooftree} \AxiomC{$\hspace{1.1cm}\myjudd{\myctx; \myb{x} : \myb{A}}{\myapp{\myb{q}}{\myb{x}}}{\myapp{\myb{f}}{\myb{x}} \mypeq{} \myapp{\myb{g}}{\myb{x}}}\hspace{1.1cm}$} \RightLabel{equality reflection} \UnaryInfC{$\myjudd{\myctx; \myb{x} : \myb{A}}{\myapp{\myb{f}}{\myb{x}} \mydefeq \myapp{\myb{g}}{\myb{x}}}{\myb{B}}$} \RightLabel{congruence for $\lambda$s} \UnaryInfC{$\myjud{(\myabs{\myb{x}}{\myapp{\myb{f}}{\myb{x}}}) \mydefeq (\myabs{\myb{x}}{\myapp{\myb{g}}{\myb{x}}})}{\myb{A} \myarr \myb{B}}$} \RightLabel{$\eta$-law for $\lambda$} \UnaryInfC{$\hspace{1.4cm}\myjud{\myb{f} \mydefeq \myb{g}}{\myb{A} \myarr \myb{B}}\hspace{1.4cm}$} \RightLabel{$\myrefl$} \UnaryInfC{$\myjud{\myapp{\myrefl}{\myb{f}}}{\myb{f} \mypeq{} \myb{g}}$} \end{prooftree} Now, the question is: do we need to give up well-behavedness of our theory to gain extensionality? \subsection{Observational equality} \label{sec:ott} % TODO should we explain this in detail? A recent development by \citet{Altenkirch2007}, \emph{Observational Type Theory} (OTT), promises to keep the well behavedness of ITT while being able to gain many useful equality proofs\footnote{It is suspected that OTT gains \emph{all} the equality proofs of ETT, but no proof exists yet.}, including function extensionality. The main idea is to give the user the possibility to \emph{coerce} (or transport) values from a type $\mytya$ to a type $\mytyb$, if the type checker can prove structurally that $\mytya$ and $\mytya$ are equal; and providing a value-level equality based on similar principles. A brief overview is given below, \mydesc{syntax}{ }{ $\mytyp_l$ is replaced by $\mytyp$. \\ $ \begin{array}{r@{\ }c@{\ }l} \mytmsyn & ::= & \cdots \\ & | & \myprdec{\myprsyn} \mysynsep \mycoee{\mytmsyn}{\mytmsyn}{\mytmsyn}{\mytmsyn} \mysynsep \mycohh{\mytmsyn}{\mytmsyn}{\mytmsyn}{\mytmsyn} \\ \myprsyn & ::= & \mybot \mysynsep \mytop \mysynsep \myprsyn \myand \myprsyn \mysynsep \myprfora{\myb{x}}{\mytmsyn}{\myprsyn} \\\ & | & \mytmsyn \myeq \mytmsyn \mysynsep \myjm{\mytmsyn}{\mytmsyn}{\mytmsyn}{\mytmsyn} \end{array} $ } \mydesc{typing:}{\myjud{\mytmsyn}{\mytmsyn}}{ There is only $\mytyp$, which corresponds to $\mytyp_0$. \\ Thus all the type-formers take $\mytyp$ arguments and form a $\mytyp$. \\ \ \\ % TODO insert large eliminator \begin{tabular}{cc} \AxiomC{$\myjud{\myse{P}}{\myprop}$} \UnaryInfC{$\myjud{\myprdec{\myse{P}}}{\mytyp}$} \DisplayProof & \AxiomC{$\myjud{\myse{P}}{\myprdec{\mytya \myeq \mytyb}}$} \AxiomC{$\myjud{\mytmt}{\mytya}$} \BinaryInfC{$\myjud{\mycoee{\mytya}{\mytyb}{\myse{P}}{\mytmt}}{\mytyb}$} \DisplayProof \end{tabular} \myderivsp \AxiomC{$\myjud{\myse{P}}{\myprdec{\mytya \myeq \mytyb}}$} \AxiomC{$\myjud{\mytmt}{\mytya}$} \BinaryInfC{$\myjud{\mycohh{\mytya}{\mytyb}{\myse{P}}{\mytmt}}{\myprdec{\myjm{\mytmt}{\mytya}{\mycoee{\mytya}{\mytyb}{\myse{P}}{\mytmt}}{\mytyb}}}$} \DisplayProof } \mydesc{propositions:}{\myjud{\myprsyn}{\myprop}}{ \begin{tabular}{cc} \AxiomC{\phantom{$\myjud{\myse{P}}{\myprop}$}} \UnaryInfC{$\myjud{\mytop}{\myprop}$} \noLine \UnaryInfC{$\myjud{\mybot}{\myprop}$} \DisplayProof & \AxiomC{$\myjud{\myse{P}}{\myprop}$} \AxiomC{$\myjud{\myse{Q}}{\myprop}$} \BinaryInfC{$\myjud{\myse{P} \myand \myse{Q}}{\myprop}$} \noLine \UnaryInfC{\phantom{$\myjud{\mybot}{\myprop}$}} \DisplayProof \end{tabular} \myderivsp \begin{tabular}{cc} \AxiomC{$\myjud{\myse{A}}{\mytyp}$} \AxiomC{$\myjudd{\myctx; \myb{x} : \mytya}{\myse{P}}{\myprop}$} \BinaryInfC{$\myjud{\myprfora{\myb{x}}{\mytya}{\myse{P}}}{\myprop}$} \DisplayProof & \AxiomC{$\myjud{\myse{A}}{\mytyp}$} \AxiomC{$\myjud{\myse{B}}{\mytyp}$} \BinaryInfC{$\myjud{\mytya \myeq \mytyb}{\myprop}$} \DisplayProof \end{tabular} \myderivsp \AxiomC{$\myjud{\myse{A}}{\mytyp}$} \AxiomC{$\myjud{\mytmm}{\myse{A}}$} \AxiomC{$\myjud{\myse{B}}{\mytyp}$} \AxiomC{$\myjud{\mytmn}{\myse{B}}$} \QuaternaryInfC{$\myjud{\myjm{\mytmm}{\myse{A}}{\mytmn}{\myse{B}}}{\myprop}$} \DisplayProof } \mydesc{proposition decoding:}{\myprdec{\mytmsyn} \myred \mytmsyn}{ \begin{tabular}{cc} $ \begin{array}{l@{\ }c@{\ }l} \myprdec{\mybot} & \myred & \myempty \\ \myprdec{\mytop} & \myred & \myunit \end{array} $ & $ \begin{array}{r@{ }c@{ }l@{\ }c@{\ }l} \myprdec{&\myse{P} \myand \myse{Q} &} & \myred & \myprdec{\myse{P}} \myprod \myprdec{\myse{Q}} \\ \myprdec{&\myprfora{\myb{x}}{\mytya}{\myse{P}} &} & \myred & \myfora{\myb{x}}{\mytya}{\myprdec{\myse{P}}} \end{array} $ \end{tabular} } \mydesc{equality reduction:}{\myprsyn \myred \myprsyn}{ $ \begin{array}{c@{\ }c@{\ }c@{\ }l} \myempty & \myeq & \myempty & \myred \mytop \\ \myunit & \myeq & \myunit & \myred \mytop \\ \mybool & \myeq & \mybool & \myred \mytop \\ \myexi{\myb{x_1}}{\mytya_1}{\mytyb_1} & \myeq & \myexi{\myb{x_2}}{\mytya_2}{\mytyb_2} & \myred \\ \multicolumn{4}{l}{ \myind{2} \mytya_1 \myeq \mytyb_1 \myand \myprfora{\myb{x_1}}{\mytya_1}{\myprfora{\myb{x_2}}{\mytya_2}{\myjm{\myb{x_1}}{\mytya_1}{\myb{x_2}}{\mytya_2}} \myimpl \mytyb_1 \myeq \mytyb_2} } \\ \myfora{\myb{x_1}}{\mytya_1}{\mytyb_1} & \myeq & \myfora{\myb{x_2}}{\mytya_2}{\mytyb_2} & \myred \cdots \\ \myw{\myb{x_1}}{\mytya_1}{\mytyb_1} & \myeq & \myw{\myb{x_2}}{\mytya_2}{\mytyb_2} & \myred \cdots \\ \mytya & \myeq & \mytyb & \myred \mybot\ \text{for other canonical types.} \end{array} $ } \mydesc{reduction}{\mytmsyn \myred \mytmsyn}{ $ \begin{array}{l@{\ }l@{\ }l@{\ }l@{\ }l@{\ }c@{\ }l@{\ }} \mycoe & \myempty & \myempty & \myse{Q} & \myse{t} & \myred & \myse{t} \\ \mycoe & \myunit & \myunit & \myse{Q} & \mytt & \myred & \mytt \\ \mycoe & \mybool & \mybool & \myse{Q} & \mytrue & \myred & \mytrue \\ \mycoe & \mybool & \mybool & \myse{Q} & \myfalse & \myred & \myfalse \\ \mycoe & (\myexi{\myb{x_1}}{\mytya_1}{\mytyb_1}) & (\myexi{\myb{x_2}}{\mytya_2}{\mytyb_2}) & \myse{Q} & \mytmt_1 & \myred & foo \\ \mycoe & (\myfora{\myb{x_1}}{\mytya_1}{\mytyb_1}) & (\myfora{\myb{x_2}}{\mytya_2}{\mytyb_2}) & \myse{Q} & \mytmt_1 & \myred & \cdots \\ \mycoe & (\myw{\myb{x_1}}{\mytya_1}{\mytyb_1}) & (\myw{\myb{x_2}}{\mytya_2}{\mytyb_2}) & \myse{Q} & \mytmt_1 & \myred & \cdots \\ \mycoe & \mytya & \mytyb & \myse{Q} & \mytmt & \myred & \myapp{\myabsurd{\mytyb}}{\myse{Q}} \end{array} $ } The original presentation of OTT employs the theory presented above. It is close to the one presented in section \ref{sec:itt}, with the additions presented above, and the change that only one the `first' universe, the type of small types ($\mytyp_0$), is present. The propositional universe is meant to be where equality proofs live in. The equality proofs are respectively between types ($\mytya = \mytyb$), and between values However, only one universe is present ($\mytyp_0$), and a \emph{propositional} universe is isolated, intended to be the universe where equality proofs live in. Propositions (as long as our system is consistent) are inhabited only by one element, and thus can all be treated as definitionally equal. % \section{Augmenting ITT} % \label{sec:practical} % \subsection{A more liberal hierarchy} % \subsection{Type inference} % \subsubsection{Bidirectional type checking} % \subsubsection{Pattern unification} % \subsection{Pattern matching and explicit fixpoints} % \subsection{Induction-recursion} % \subsection{Coinduction} % \subsection{Dealing with partiality} % \subsection{Type holes} \section{\mykant : the theory} \label{sec:kant-theory} \mykant\ is an interactive theorem prover developed as part of this thesis. The plan is to present a core language which would be capable of serving as the basis for a more featureful system, while still presenting interesting features and more importantly observational equality. The author learnt the hard way the implementations challenges for such a project, and while there is a solid and working base to work on, observational equality is not currently implemented. However, a detailed plan on how to add it this functionality is provided, and should not prove to be too much work. The features currently implemented in \mykant\ are: \begin{description} \item[Full dependent types] As we would expect, we have dependent a system which is as expressive as the `best' corner in the lambda cube described in section \ref{sec:itt}. \item[Implicit, cumulative universe hierarchy] The user does not need to specify universe level explicitly, and universes are \emph{cumulative}. \item[User defined data types and records] Instead of forcing the user to choose from a restricted toolbox, we let her define inductive data types, with associated primitive recursion operators; or records, with associated projections for each field. \item[Bidirectional type checking] While no `fancy' inference via unification is present, we take advantage of an type synthesis system in the style of \cite{Pierce2000}, extending the concept for user defined data types. \item[Type holes] When building up programs interactively, it is useful to leave parts unfinished while exploring the current context. This is what type holes are for. \end{description} The planned features are: \begin{description} \item[Observational equality] As described in section \ref{sec:ott} but extended to work with the type hierarchy and to admit equality between arbitrary data types. \item[Coinductive data] ... \end{description} We will analyse the features one by one, along with motivations and tradeoffs for the design decisions made. \subsection{Bidirectional type checking} We start by describing bidirectional type checking since it calls for fairly different typing rules that what we have seen up to now. The idea is to have two kind of terms: terms for which a type can always be inferred, and terms that need to be checked against a type. A nice observation is that this duality runs through the semantics of the terms: data destructors (function application, record projections, primitive re cursors) \emph{infer} types, while data constructors (abstractions, record/data types data constructors) need to be checked. In the literature these terms are respectively known as To introduce the concept and notation, we will revisit the STLC in a bidirectional style. The presentation follows \cite{Loh2010}. % TODO do this --- is it even necessary % \subsubsection{Declarations and contexts} % A \mykant declaration can be one of 4 kinds: % \begin{description} % \item[Value] A declared variable, together with a type and a body. % \item[Postulate] An abstract variable, with a type but no body. % \item[Inductive data] A datatype, with a type constructor and various data % constructors---somewhat similar to what we find in Haskell. A primitive % recursor (or `destructor') will be generated automatically. % \item[Record] A record, which consists of one data constructor and various % fields, with no recursive occurrences. We will explain the need for records % later. % \end{description} % The syntax of \subsection{Base terms and types} Let us begin by describing the primitives available without the user defining any data types, and without equality. The syntax given here is the one of the core (`desugared') terms, and the way we handle variables and substitution is left unspecified, and explained in section \ref{sec:term-repr}, along with other implementation issues. We are also going to give an account of the implicit type hierarchy separately in section \ref{sec:term-hierarchy}, so as not to clutter derivation rules too much, and just treat types as impredicative for the time being. \mydesc{syntax}{ }{ $ \begin{array}{r@{\ }c@{\ }l} \mytmsyn & ::= & \mynamesyn \mysynsep \mytyp \\ & | & \myfora{\myb{x}}{\mytmsyn}{\mytmsyn} \mysynsep \myabss{\myb{x}}{\mytmsyn}{\mytmsyn} \mysynsep (\myapp{\mytmsyn}{\mytmsyn}) \mysynsep (\myann{\mytmsyn}{\mytmsyn}) \\ \mynamesyn & ::= & \myb{x} \mysynsep \myfun{f} \end{array} $ } The syntax for our calculus includes just two basic constructs: abstractions and $\mytyp$s. Everything else will be provided by user-definable constructs. Since we let the user define values, we will need a context capable of carrying the body of variables along with their type. We also want to make sure not to have duplicate top names, so we enforce that. % \mytyc{D} \mysynsep \mytyc{D}.\mydc{c} % \mysynsep \mytyc{D}.\myfun{f} \mysynsep \mydesc{context validity:}{\myvalid{\myctx}}{ \begin{tabular}{ccc} \AxiomC{\phantom{$\myjud{\mytya}{\mytyp_l}$}} \UnaryInfC{$\myvalid{\myemptyctx}$} \DisplayProof & \AxiomC{$\myjud{\mytya}{\mytyp}$} \AxiomC{$\mynamesyn \not\in \myctx$} \BinaryInfC{$\myvalid{\myctx ; \mynamesyn : \mytya}$} \DisplayProof & \AxiomC{$\myjud{\mytmt}{\mytya}$} \AxiomC{$\myfun{f} \not\in \myctx$} \BinaryInfC{$\myvalid{\myctx ; \myfun{f} \mapsto \mytmt : \mytya}$} \DisplayProof \end{tabular} } Now we can present the reduction rules, which are unsurprising. We have the usual functional application ($\beta$-reduction), but also a rule to replace names with their bodies, if in the context ($\delta$-reduction), and one to discard type annotations. For this reason the new reduction rules are dependent on the context: \mydesc{reduction:}{\myctx \vdash \mytmsyn \myred \mytmsyn}{ \begin{tabular}{ccc} \AxiomC{\phantom{$\myb{x} \mapsto \mytmt : \mytya \in \myctx$}} \UnaryInfC{$\myctx \vdash \myapp{(\myabs{\myb{x}}{\mytmm})}{\mytmn} \myred \mysub{\mytmm}{\myb{x}}{\mytmn}$} \DisplayProof & \AxiomC{$\myfun{f} \mapsto \mytmt : \mytya \in \myctx$} \UnaryInfC{$\myctx \vdash \myfun{f} \myred \mytmt$} \DisplayProof & \AxiomC{\phantom{$\myb{x} \mapsto \mytmt : \mytya \in \myctx$}} \UnaryInfC{$\myctx \vdash \myann{\mytmm}{\mytya} \myred \mytmm$} \DisplayProof \end{tabular} } We want to define a \emph{weak head normal form} (WHNF) for our terms, to give a syntax directed presentation of type rules with no `conversion' rule. We will consider all \emph{canonical} forms (abstractions and data constructors) to be in weak head normal form... % TODO finish We can now give types to our terms. Using our definition of WHNF, I will use $\mytmm \mynf \mytmn$ to indicate that $\mytmm$'s normal form is $\mytmn$. This way, we can avoid the non syntax-directed conversion rule, giving a more algorithmic presentation of type checking. \mydesc{typing:}{\myctx \vdash \mytmsyn \Leftrightarrow \mytmsyn}{ \begin{tabular}{ccc} \AxiomC{$\myb{x} : A \in \myctx$ or $\myb{x} \mapsto \mytmt : A \in \myctx$} \UnaryInfC{$\myinf{\myb{x}}{A}$} \DisplayProof & \AxiomC{$\mychk{\mytmt}{\mytya}$} \UnaryInfC{$\myinf{\myann{\mytmt}{\mytya}}{\mytya}$} \DisplayProof \end{tabular} \myderivsp \AxiomC{$\myinf{\mytmm}{\mytya}$} \AxiomC{$\myctx \vdash \mytya \mynf \myfora{\myb{x}}{\mytyb}{\myse{C}}$} \AxiomC{$\mychk{\mytmn}{\mytyb}$} \TrinaryInfC{$\myinf{\myapp{\mytmm}{\mytmn}}{\mysub{\myse{C}}{\myb{x}}{\mytmn}}$} \DisplayProof \myderivsp \AxiomC{$\myctx \vdash \mytya \mynf \myfora{\myb{x}}{\mytyb}{\myse{C}}$} \AxiomC{$\mychkk{\myctx; \myb{x}: \mytyb}{\mytmt}{\myse{C}}$} \BinaryInfC{$\mychk{\myabs{\myb{x}}{\mytmt}}{\mytya}$} \DisplayProof } \subsection{Elaboration} \mydesc{syntax}{ }{ $ \begin{array}{r@{\ }c@{\ }l} \mydeclsyn & ::= & \myval{\myb{x}}{\mytmsyn}{\mytmsyn} \\ & | & \mypost{\myb{x}}{\mytmsyn} \\ & | & \myadt{\mytyc{D}}{\mytelesyn}{}{\mydc{c} : \mytelesyn\ |\ \cdots } \\ & | & \myreco{\mytyc{D}}{\mytelesyn}{}{\myfun{f} : \mytmsyn,\ \cdots } \\ \mytelesyn & ::= & \myemptytele \mysynsep \mytelesyn \mycc (\myb{x} {:} \mytmsyn) \end{array} $ } \mydesc{typing:}{\myctx \vdash \mytmsyn \Leftrightarrow \mytmsyn}{ } \subsubsection{Values and postulated variables} As mentioned, in \mykant\ we can defined top level variables, with or without a body. We call the variables \mydesc{context elaboration:}{\myelab{\mydeclsyn}{\myctx}}{ \begin{tabular}{cc} \AxiomC{$\myjud{\mytmt}{\mytya}$} \AxiomC{$\myfun{f} \not\in \myctx$} \BinaryInfC{ $\myctx \myelabt \myval{\myfun{f}}{\mytya}{\mytmt} \ \ \myelabf\ \ \myctx; \myfun{f} \mapsto \mytmt : \mytya$ } \DisplayProof & \AxiomC{$\myjud{\mytya}{\mytyp}$} \AxiomC{$\myfun{f} \not\in \myctx$} \BinaryInfC{ $ \myctx \myelabt \mypost{\myfun{f}}{\mytya} \ \ \myelabf\ \ \myctx; \myfun{f} : \mytya $ } \DisplayProof \end{tabular} } \subsubsection{User defined types} \mydesc{syntax}{ }{ $ \begin{array}{l} \mynamesyn ::= \cdots \mysynsep \mytyc{D} \mysynsep \mytyc{D}.\mydc{c} \mysynsep \mytyc{D}.\myfun{f} \end{array} $ } \mydesc{typing:}{ }{ \AxiomC{$\mytyc{D} : \mytele \myarr \mytyp \in \myctx$} \AxiomC{$\mytyc{D}.\mydc{c} : \mytele \mycc \mytele' \myarr \myapp{\mytyc{D}}{\mytelee} \in \myctx$} \BinaryInfC{$\mychk{\myapp{\mytyc{D}.\mydc{c}}{\vec{t}}}{\myapp{\mytyc{D}}{\vec{A}}}$} \DisplayProof % TODO \myderivsp \AxiomC{$\mytyc{D} : \mytele \myarr \mytyp \in \myctx$} \AxiomC{$\mytyc{D}.\myfun{f} : \mytele \myarr \myapp{\mytyc{D}}{\mytelee} \myarr \myse{F}$} \AxiomC{$\myjud{\mytmt}{\myapp{\mytyc{D}}{\vec{A}}}$} \TrinaryInfC{$\myinf{\myapp{\mytyc{D}.\myfun{f}}{\mytmt}}{TODO}$} \DisplayProof } \subsubsection{Data types} \begin{figure}[t] \mydesc{syntax elaboration:}{\mydeclsyn \myelabf \mytmsyn ::= \cdots}{ $ \begin{array}{r@{\ }l} & \myadt{\mytyc{D}}{\mytele}{}{\cdots\ |\ \mydc{c}_n : \myvec{(\myb{x} {:} \mytya)} \ |\ \cdots } \\ \myelabf & \begin{array}{r@{\ }c@{\ }l} \mytmsyn & ::= & \cdots \mysynsep \myapp{\mytyc{D}}{\myvec{\mytmsyn}} \mysynsep \mytyc{D}.\mydc{c}_n \myappsp \myvec{\mytmsyn} \mysynsep \cdots \mysynsep \mytyc{D}.\myfun{elim} \myappsp \mytmsyn \\ \end{array} \end{array} $ } \mydesc{context elaboration:}{\myelab{\mydeclsyn}{\myctx}}{ \AxiomC{$\myinf{\mytele \myarr \mytyp}{\mytyp}$} \AxiomC{$\mytyc{D} \not\in \myctx$} \noLine \BinaryInfC{$\myinff{\myctx;\ \mytyc{D} : \mytele \myarr \mytyp}{\mytele \mycc \mytele_i \myarr \myapp{\mytyc{D}}{\mytelee}}{\mytyp}\ \ \ (1 \leq i \leq n)$} \noLine \UnaryInfC{For each $(\myb{x} {:} \mytya)$ in each $\mytele_i$, if $\mytyc{D} \in \mytya$, then $\mytya = \myapp{\mytyc{D}}{\vec{\mytmt}}$.} \UnaryInfC{$ \begin{array}{r@{\ }c@{\ }l} \myctx & \myelabt & \myadt{\mytyc{D}}{\mytele}{}{ \mydc{c} : \mytele_1 \ |\ \cdots \ |\ \mydc{c}_n : \mytele_n } \\ & & \vspace{-0.2cm} \\ & \myelabf & \myctx;\ \mytyc{D} : \mytele \mycc \mytyp;\ \mytyc{D}.\mydc{c}_1 : \mytele \mycc \mytele_1 \myarr \myapp{\mytyc{D}}{\mytelee};\ \cdots;\ \mytyc{D}.\mydc{c}_n : \mytele \mycc \mytele_n \myarr \myapp{\mytyc{D}}{\mytelee}; \\ & & \begin{array}{@{}r@{\ }l l} \mytyc{D}.\myfun{elim} : & \mytele \myarr (\myb{x} {:} \myapp{\mytyc{D}}{\mytelee}) \myarr & \textbf{target} \\ & (\myb{P} {:} \myapp{\mytyc{D}}{\mytelee} \myarr \mytyp) \myarr & \textbf{motive} \\ & \left. \begin{array}{@{}l} (\mytele_1 \mycc \myhyps(\myb{P}, \mytele_1) \myarr \myapp{\myb{P}}{(\myapp{\mytyc{D}.\mydc{c}_1}{\mytelee_1})}) \myarr \\ \myind{3} \vdots \\ (\mytele_n \mycc \myhyps(\myb{P}, \mytele_n) \myarr \myapp{\myb{P}}{(\myapp{\mytyc{D}.\mydc{c}_n}{\mytelee_n})}) \myarr \end{array} \right \} & \textbf{methods} \\ & \myapp{\myb{P}}{\myb{x}} & \end{array} \\ \\ \multicolumn{3}{l}{ \begin{array}{@{}l l@{\ } l@{} r c l} \textbf{where} & \myhyps(\myb{P}, & \myemptytele &) & \mymetagoes & \myemptytele \\ & \myhyps(\myb{P}, & (\myb{r} {:} \myapp{\mytyc{D}}{\vec{\mytmt}}) \mycc \mytele &) & \mymetagoes & (\myb{r'} {:} \myapp{\myb{P}}{\myb{r}}) \mycc \myhyps(\myb{P}, \mytele) \\ & \myhyps(\myb{P}, & (\myb{x} {:} \mytya) \mycc \mytele & ) & \mymetagoes & \myhyps(\myb{P}, \mytele) \end{array} } \end{array} $} \DisplayProof } \mydesc{reduction elaboration:}{\mydeclsyn \myelabf \myctx \vdash \mytmsyn \myred \mytmsyn}{ \AxiomC{$\mytyc{D} : \mytele \myarr \mytyp \in \myctx$} \AxiomC{$\mytyc{D}.\mydc{c}_i : \mytele;\mytele_i \myarr \myapp{\mytyc{D}}{\mytelee} \in \myctx$} \BinaryInfC{$ \begin{array}{c} \myctx \vdash \myapp{\myapp{\myapp{\mytyc{D}.\myfun{elim}}{(\myapp{\mytyc{D}.\mydc{c}_i}{\vec{\myse{t}}})}}{\myse{P}}}{\vec{\myse{m}}} \myred \myapp{\myapp{\myse{m}_i}{\vec{\mytmt}}}{\myrecs(\myse{P}, \vec{m}, \mytele_i)} \\ \\ \begin{array}{@{}l l@{\ } l@{} r c l} \textbf{where} & \myrecs(\myse{P}, \vec{m}, & \myemptytele &) & \mymetagoes & \myemptytele \\ & \myrecs(\myse{P}, \vec{m}, & (\myb{r} {:} \myapp{\mytyc{D}}{\vec{A}}); \mytele & ) & \mymetagoes & (\mytyc{D}.\myfun{elim} \myappsp \myb{r} \myappsp \myse{P} \myappsp \vec{m}); \myrecs(\myse{P}, \vec{m}, \mytele) \\ & \myrecs(\myse{P}, \vec{m}, & (\myb{x} {:} \mytya); \mytele &) & \mymetagoes & \myrecs(\myse{P}, \vec{m}, \mytele) \end{array} \end{array} $} \DisplayProof } \caption{Elaborations for data types.} \label{fig:elab-adt} \end{figure} \subsubsection{Records} \begin{figure}[t] \mydesc{syntax elaboration:}{\myelab{\mydeclsyn}{\mytmsyn ::= \cdots}}{ $ \begin{array}{r@{\ }c@{\ }l} \myctx & \myelabt & \myadt{\mytyc{D}}{\mytele}{}{\cdots\ |\ \mydc{c}_n : \myvec{(\myb{x} {:} \mytya)} \ |\ \cdots } \\ & \myelabf & \begin{array}{r@{\ }c@{\ }l} \mytmsyn & ::= & \cdots \mysynsep \myapp{\mytyc{D}}{\myvec{\mytmsyn}} \mysynsep \mytyc{D}.\mydc{c}_n \myappsp \myvec{\mytmsyn} \mysynsep \cdots \mysynsep \mytyc{D}.\myfun{elim} \myappsp \mytmsyn \\ \end{array} \end{array} $ } \mydesc{context elaboration:}{\myelab{\mydeclsyn}{\myctx}}{ \AxiomC{$\myinf{\mytele \myarr \mytyp}{\mytyp}$} \AxiomC{$\mytyc{D} \not\in \myctx$} \noLine \BinaryInfC{$\myinff{\myctx; \mytele; (\myb{f}_j : \myse{F}_j)_{j=1}^{i - 1}}{F_i}{\mytyp} \myind{3} (1 \le i \le n)$} \UnaryInfC{$ \begin{array}{r@{\ }c@{\ }l} \myctx & \myelabt & \myreco{\mytyc{D}}{\mytele}{}{ \myfun{f}_1 : \myse{F}_1, \cdots, \myfun{f}_n : \myse{F}_n } \\ & & \vspace{-0.2cm} \\ & \myelabf & \myctx;\ \mytyc{D} : \mytele \myarr \mytyp;\\ & & \mytyc{D}.\myfun{f}_1 : \mytele \myarr \myapp{\mytyc{D}}{\mytelee} \myarr \myse{F}_1;\ \cdots;\ \mytyc{D}.\myfun{f}_n : \mytele \myarr (\myb{x} {:} \myapp{\mytyc{D}}{\mytelee}) \myarr \mysub{\myse{F}_n}{\myb{f}_i}{\myapp{\myfun{f}_i}{\myb{x}}}_{i = 1}^{n-1}; \\ & & \mytyc{D}.\mydc{constr} : \mytele \myarr \myse{F}_1 \myarr \cdots \myarr \myse{F}_n \myarr \myapp{\mytyc{D}}{\mytelee}; \end{array} $} \DisplayProof } \mydesc{reduction elaboration:}{\mydeclsyn \myelabf \myctx \vdash \mytmsyn \myred \mytmsyn}{ \AxiomC{$\mytyc{D} \in \myctx$} \UnaryInfC{$\myctx \vdash \myapp{\mytyc{D}.\myfun{f}_i}{(\mytyc{D}.\mydc{constr} \myappsp \vec{t})} \myred t_i$} \DisplayProof } \caption{Elaborations for records.} \label{fig:elab-adt} \end{figure} \subsection{Type hierarchy} \label{sec:term-hierarchy} \subsection{Observational equality, \mykant\ style} \mydesc{syntax}{ }{ $ \begin{array}{r@{\ }c@{\ }l} \mytmsyn & ::= & \mytmsyn \myeq \mytmsyn \mysynsep \myjm{\mytmsyn}{\mytmsyn}{\mytmsyn}{\mytmsyn} \\ & | & \mycoee{\mytmsyn}{\mytmsyn}{\mytmsyn}{\mytmsyn} \mysynsep \mycohh{\mytmsyn}{\mytmsyn}{\mytmsyn}{\mytmsyn} \end{array} $ } \section{\mykant : The practice} \label{sec:kant-practice} The codebase consists of around 2500 lines of Haskell, as reported by the \texttt{cloc} utility. The high level design is heavily inspired by Conor McBride's work on various incarnations of Epigram, and specifically by the first version as described \citep{McBride2004} and the codebase for the new version \footnote{Available intermittently as a \texttt{darcs} repository at \url{http://sneezy.cs.nott.ac.uk/darcs/Pig09}.}. In many ways \mykant\ is something in between the first and second version of Epigram. The interaction happens in a read-eval-print loop (REPL). The repl is a available both as a commandline application and in a web interface, which is available at \url{kant.mazzo.li} and presents itself as in figure \ref{fig:kant-web}. \begin{figure} \centering{ \includegraphics[scale=1.0]{kant-web.png} } \caption{The \mykant\ web prompt.} \label{fig:kant-web} \end{figure} The interaction with the user takes place in a loop living in and updating a context \mykant\ declarations. The user inputs a new declaration that goes through various stages starts with the user inputing a \mykant\ declaration or another REPL command, which then goes through various stages that can end up in a context update, or in failures of various kind. The process is described diagrammatically in figure \ref{fig:kant-process}: \begin{description} \item[Parse] In this phase the text input gets converted to a sugared version of the core language. \item[Desugar] The sugared declaration is converted to a core term. \item[Reference] Occurrences of $\mytyp$ get decorated by a unique reference, which is necessary to implement the type hierarchy check. \item[Elaborate] Convert the declaration to some context item, which might be a value declaration (type and body) or a data type declaration (constructors and destructors). This phase works in tandem with \textbf{Typechecking}, which in turns needs to \textbf{Evaluate} terms. \item[Distill] and report the result. `Distilling' refers to the process of converting a core term back to a sugared version that the user can visualise. This can be necessary both to display errors including terms or to display result of evaluations or type checking that the user has requested. \item[Pretty print] Format the terms in a nice way, and display the result to the user. \end{description} The details of each phase will be described in section % TODO insert section \begin{figure} \centering{\small \tikzstyle{block} = [rectangle, draw, text width=5em, text centered, rounded corners, minimum height=2.5em, node distance=0.7cm] \tikzstyle{decision} = [diamond, draw, text width=4.5em, text badly centered, inner sep=0pt, node distance=0.7cm] \tikzstyle{line} = [draw, -latex'] \tikzstyle{cloud} = [draw, ellipse, minimum height=2em, text width=5em, text centered, node distance=1.5cm] \begin{tikzpicture}[auto] \node [cloud] (user) {User}; \node [block, below left=1cm and 0.1cm of user] (parse) {Parse}; \node [block, below=of parse] (desugar) {Desugar}; \node [block, below=of desugar] (reference) {Reference}; \node [block, below=of reference] (elaborate) {Elaborate}; \node [block, left=of elaborate] (tycheck) {Typecheck}; \node [block, left=of tycheck] (evaluate) {Evaluate}; \node [decision, right=of elaborate] (error) {Error?}; \node [block, right=of parse] (distill) {Distill}; \node [block, right=of desugar] (update) {Update context}; \path [line] (user) -- (parse); \path [line] (parse) -- (desugar); \path [line] (desugar) -- (reference); \path [line] (reference) -- (elaborate); \path [line] (elaborate) edge[bend right] (tycheck); \path [line] (tycheck) edge[bend right] (elaborate); \path [line] (elaborate) -- (error); \path [line] (error) edge[out=0,in=0] node [near start] {yes} (distill); \path [line] (error) -- node [near start] {no} (update); \path [line] (update) -- (distill); \path [line] (distill) -- (user); \path [line] (tycheck) edge[bend right] (evaluate); \path [line] (evaluate) edge[bend right] (tycheck); \end{tikzpicture} } \caption{High level overview of the life of a \mykant\ prompt cycle.} \label{fig:kant-process} \end{figure} \subsection{Term representation} \label{sec:term-repr} \subsection{Type hierarchy} \subsection{Elaboration} \section{Evaluation} \section{Future work} \appendix \section{Notation and syntax} Syntax, derivation rules, and reduction rules, are enclosed in frames describing the type of relation being established and the syntactic elements appearing, for example \mydesc{typing:}{\myjud{\mytmsyn}{\mytysyn}}{ Typing derivations here. } In the languages presented and Agda code samples I also highlight the syntax, following a uniform color and font convention: \begin{center} \begin{tabular}{c | l} $\mytyc{Sans}$ & Type constructors. \\ $\mydc{sans}$ & Data constructors. \\ % $\myfld{sans}$ & Field accessors (e.g. \myfld{fst} and \myfld{snd} for products). \\ $\mysyn{roman}$ & Keywords of the language. \\ $\myfun{roman}$ & Defined values and destructors. \\ $\myb{math}$ & Bound variables. \end{tabular} \end{center} Moreover, I will from time to time give examples in the Haskell programming language as defined in \citep{Haskell2010}, which I will typeset in \texttt{teletype} font. I assume that the reader is already familiar with Haskell, plenty of good introductions are available \citep{LYAH,ProgInHask}. When presenting grammars, I will use a word in $\mysynel{math}$ font (e.g. $\mytmsyn$ or $\mytysyn$) to indicate indicate nonterminals. Additionally, I will use quite flexibly a $\mysynel{math}$ font to indicate a syntactic element. More specifically, terms are usually indicated by lowercase letters (often $\mytmt$, $\mytmm$, or $\mytmn$); and types by an uppercase letter (often $\mytya$, $\mytyb$, or $\mytycc$). When presenting type derivations, I will often abbreviate and present multiple conclusions, each on a separate line: \begin{prooftree} \AxiomC{$\myjud{\mytmt}{\mytya \myprod \mytyb}$} \UnaryInfC{$\myjud{\myapp{\myfst}{\mytmt}}{\mytya}$} \noLine \UnaryInfC{$\myjud{\myapp{\mysnd}{\mytmt}}{\mytyb}$} \end{prooftree} \section{Agda rendition of ITT} \label{app:agda-itt} Note that in what follows rules for `base' types are universe-polymorphic, to reflect the exposition. Derived definitions, on the other hand, mostly work with \mytyc{Set}, reflecting the fact that in the theory presented we don't have universe polymorphism. \begin{code} module ITT where open import Level data Empty : Set where absurd : ∀ {a} {A : Set a} → Empty → A absurd () ¬_ : ∀ {a} → (A : Set a) → Set a ¬ A = A → Empty record Unit : Set where constructor tt record _×_ {a b} (A : Set a) (B : A → Set b) : Set (a ⊔ b) where constructor _,_ field fst : A snd : B fst data Bool : Set where true false : Bool if_then_else_ : ∀ {a} {P : Bool → Set a} (x : Bool) → P true → P false → P x if true then x else _ = x if false then _ else x = x data W {s p} (S : Set s) (P : S → Set p) : Set (s ⊔ p) where _◁_ : (s : S) → (P s → W S P) → W S P rec : ∀ {a b} {S : Set a} {P : S → Set b} (C : W S P → Set) → -- some conclusion we hope holds ((s : S) → -- given a shape... (f : P s → W S P) → -- ...and a bunch of kids... ((p : P s) → C (f p)) → -- ...and C for each kid in the bunch... C (s ◁ f)) → -- ...does C hold for the node? (x : W S P) → -- If so, ... C x -- ...C always holds. rec C c (s ◁ f) = c s f (λ p → rec C c (f p)) module Examples-→ where open ITT data ℕ : Set where zero : ℕ suc : ℕ → ℕ -- These pragmas are needed so we can use number literals. {-# BUILTIN NATURAL ℕ #-} {-# BUILTIN ZERO zero #-} {-# BUILTIN SUC suc #-} data List (A : Set) : Set where [] : List A _∷_ : A → List A → List A length : ∀ {A} → List A → ℕ length [] = zero length (_ ∷ l) = suc (length l) _>_ : ℕ → ℕ → Set zero > _ = Empty suc _ > zero = Unit suc x > suc y = x > y head : ∀ {A} → (l : List A) → length l > 0 → A head [] p = absurd p head (x ∷ _) _ = x module Examples-× where open ITT open Examples-→ even : ℕ → Set even zero = Unit even (suc zero) = Empty even (suc (suc n)) = even n 6-is-even : even 6 6-is-even = tt 5-is-not-even : ¬ (even 5) 5-is-not-even = absurd there-is-an-even-number : ℕ × even there-is-an-even-number = 6 , 6-is-even module Equality where open ITT data _≡_ {a} {A : Set a} : A → A → Set a where refl : ∀ x → x ≡ x ≡-elim : ∀ {a b} {A : Set a} (P : (x y : A) → x ≡ y → Set b) → ∀ {x y} → P x x (refl x) → (x≡y : x ≡ y) → P x y x≡y ≡-elim P p (refl x) = p subst : ∀ {A : Set} (P : A → Set) → ∀ {x y} → (x≡y : x ≡ y) → P x → P y subst P x≡y p = ≡-elim (λ _ y _ → P y) p x≡y sym : ∀ {A : Set} (x y : A) → x ≡ y → y ≡ x sym x y p = subst (λ y′ → y′ ≡ x) p (refl x) trans : ∀ {A : Set} (x y z : A) → x ≡ y → y ≡ z → x ≡ z trans x y z p q = subst (λ z′ → x ≡ z′) q p cong : ∀ {A B : Set} (x y : A) → x ≡ y → (f : A → B) → f x ≡ f y cong x y p f = subst (λ y′ → f x ≡ f y′) p (refl (f x)) \end{code} \nocite{*} \bibliographystyle{authordate1} \bibliography{thesis} \end{document}