\chapter{Functional Programming in HOL}

Although on the surface this chapter is mainly concerned with how to write

functional programs in HOL and how to verify them, most of the

constructs and proof procedures introduced are general purpose and recur in

any specification or verification task.

The dedicated functional programmer should be warned: HOL offers only

\emph{total functional programming} --- all functions in HOL must be total;

lazy data structures are not directly available. On the positive side,

functions in HOL need not be computable: HOL is a specification language that

goes well beyond what can be expressed as a program. However, for the time

being we concentrate on the computable.

\section{An introductory theory}

\label{sec:intro-theory}

Functional programming needs datatypes and functions. Both of them can be

defined in a theory with a syntax reminiscent of languages like ML or

Haskell. As an example consider the theory in figure~\ref{fig:ToyList}.

We will now examine it line by line.

\begin{figure}[htbp]

\begin{ttbox}\makeatother

\input{ToyList2/ToyList1}\end{ttbox}

\caption{A theory of lists}

\label{fig:ToyList}

\end{figure}

{\makeatother\input{ToyList/document/ToyList.tex}}

The complete proof script is shown in figure~\ref{fig:ToyList-proofs}. The

concatenation of figures \ref{fig:ToyList} and \ref{fig:ToyList-proofs}

constitutes the complete theory \texttt{ToyList} and should reside in file

\texttt{ToyList.thy}. It is good practice to present all declarations and

definitions at the beginning of a theory to facilitate browsing.

\begin{figure}[htbp]

\begin{ttbox}\makeatother

\input{ToyList2/ToyList2}\end{ttbox}

\caption{Proofs about lists}

\label{fig:ToyList-proofs}

\end{figure}

\subsubsection*{Review}

This is the end of our toy proof. It should have familiarized you with

\begin{itemize}

\item the standard theorem proving procedure:

state a goal (lemma or theorem); proceed with proof until a separate lemma is

required; prove that lemma; come back to the original goal.

\item a specific procedure that works well for functional programs:

induction followed by all-out simplification via \isa{auto}.

\item a basic repertoire of proof commands.

\end{itemize}

\section{Some helpful commands}

\label{sec:commands-and-hints}

This section discusses a few basic commands for manipulating the proof state

and can be skipped by casual readers.

There are two kinds of commands used during a proof: the actual proof

commands and auxiliary commands for examining the proof state and controlling

the display. Simple proof commands are of the form

\isacommand{apply}\isa{(method)}\indexbold{apply} where \bfindex{method} is a

synonym for ``theorem proving function''. Typical examples are

\isa{induct_tac} and \isa{auto}. Further methods are introduced throughout

the tutorial.  Unless stated otherwise you may assume that a method attacks

merely the first subgoal. An exception is \isa{auto} which tries to solve all

subgoals.

The most useful auxiliary commands are:

\begin{description}

\item[Undoing:] \isacommand{undo}\indexbold{*undo} undoes the effect of the

  last command; \isacommand{undo} can be undone by

  \isacommand{redo}\indexbold{*redo}.  Both are only needed at the shell

  level and should not occur in the final theory.

\item[Printing the current state:] \isacommand{pr}\indexbold{*pr} redisplays

  the current proof state, for example when it has disappeared off the

  screen.

\item[Limiting the number of subgoals:] \isacommand{pr}~$n$ tells Isabelle to

  print only the first $n$ subgoals from now on and redisplays the current

  proof state. This is helpful when there are many subgoals.

\item[Modifying the order of subgoals:]

\isacommand{defer}\indexbold{*defer} moves the first subgoal to the end and

\isacommand{prefer}\indexbold{*prefer}~$n$ moves subgoal $n$ to the front.

\item[Printing theorems:]

  \isacommand{thm}\indexbold{*thm}~\textit{name}$@1$~\dots~\textit{name}$@n$

  prints the named theorems.

\item[Displaying types:] We have already mentioned the flag

  \ttindex{show_types} above. It can also be useful for detecting typos in

  formulae early on. For example, if \texttt{show_types} is set and the goal

  \isa{rev(rev xs) = xs} is started, Isabelle prints the additional output

\par\noindent

\begin{isabelle}%

Variables:\isanewline

~~xs~::~'a~list

\end{isabelle}%

\par\noindent

which tells us that Isabelle has correctly inferred that

\isa{xs} is a variable of list type. On the other hand, had we

made a typo as in \isa{rev(re xs) = xs}, the response

\par\noindent

\begin{isabelle}%

Variables:\isanewline

~~re~::~'a~list~{\isasymRightarrow}~'a~list\isanewline

~~xs~::~'a~list%

\end{isabelle}%

\par\noindent

would have alerted us because of the unexpected variable \isa{re}.

\item[Reading terms and types:] \isacommand{term}\indexbold{*term}

  \textit{string} reads, type-checks and prints the given string as a term in

  the current context; the inferred type is output as well.

  \isacommand{typ}\indexbold{*typ} \textit{string} reads and prints the given

  string as a type in the current context.

\item[(Re)loading theories:] When you start your interaction you must open a

  named theory with the line \isa{\isacommand{theory}~T~=~\dots~:}. Isabelle

  automatically loads all the required parent theories from their respective

  files (which may take a moment, unless the theories are already loaded and

  the files have not been modified).

  If you suddenly discover that you need to modify a parent theory of your

  current theory you must first abandon your current theory\indexbold{abandon

  theory}\indexbold{theory!abandon} (at the shell

  level type \isacommand{kill}\indexbold{*kill}). After the parent theory has

  been modified you go back to your original theory. When its first line

  \isacommand{theory}\texttt{~T~=}~\dots~\texttt{:} is processed, the

  modified parent is reloaded automatically.

  The only time when you need to load a theory by hand is when you simply

  want to check if it loads successfully without wanting to make use of the

  theory itself. This you can do by typing

  \isa{\isacommand{use\_thy}\indexbold{*use_thy}~"T"}.

\end{description}

Further commands are found in the Isabelle/Isar Reference Manual.

We now examine Isabelle's functional programming constructs systematically,

starting with inductive datatypes.

\section{Datatypes}

\label{sec:datatype}

Inductive datatypes are part of almost every non-trivial application of HOL.

First we take another look at a very important example, the datatype of

lists, before we turn to datatypes in general. The section closes with a

case study.

\subsection{Lists}

\indexbold{*list}

Lists are one of the essential datatypes in computing. Readers of this

tutorial and users of HOL need to be familiar with their basic operations.

Theory \isa{ToyList} is only a small fragment of HOL's predefined theory

\isa{List}\footnote{\url{http://isabelle.in.tum.de/library/HOL/List.html}}.

The latter contains many further operations. For example, the functions

\isaindexbold{hd} (``head'') and \isaindexbold{tl} (``tail'') return the first

element and the remainder of a list. (However, pattern-matching is usually

preferable to \isa{hd} and \isa{tl}.)  Theory \isa{List} also contains

more syntactic sugar: \isa{[}$x@1$\isa{,}\dots\isa{,}$x@n$\isa{]} abbreviates

$x@1$\isa{\#}\dots\isa{\#}$x@n$\isa{\#[]}.  In the rest of the tutorial we

always use HOL's predefined lists.

\subsection{The general format}

\label{sec:general-datatype}

The general HOL \isacommand{datatype} definition is of the form

\[

\isacommand{datatype}~(\alpha@1, \dots, \alpha@n) \, t ~=~

C@1~\tau@{11}~\dots~\tau@{1k@1} ~\mid~ \dots ~\mid~

C@m~\tau@{m1}~\dots~\tau@{mk@m}

\]

where $\alpha@i$ are distinct type variables (the parameters), $C@i$ are distinct

constructor names and $\tau@{ij}$ are types; it is customary to capitalize

the first letter in constructor names. There are a number of

restrictions (such as that the type should not be empty) detailed

elsewhere~\cite{isabelle-HOL}. Isabelle notifies you if you violate them.

Laws about datatypes, such as \isa{[] \isasymnoteq~x\#xs} and

\isa{(x\#xs = y\#ys) = (x=y \isasymand~xs=ys)}, are used automatically

during proofs by simplification.  The same is true for the equations in

primitive recursive function definitions.

Every datatype $t$ comes equipped with a \isa{size} function from $t$ into

the natural numbers (see~{\S}\ref{sec:nat} below). For lists, \isa{size} is

just the length, i.e.\ \isa{size [] = 0} and \isa{size(x \# xs) = size xs +

  1}.  In general, \isaindexbold{size} returns \isa{0} for all constructors

that do not have an argument of type $t$, and for all other constructors

\isa{1 +} the sum of the sizes of all arguments of type $t$. Note that because

\isa{size} is defined on every datatype, it is overloaded; on lists

\isa{size} is also called \isaindexbold{length}, which is not overloaded.

Isbelle will always show \isa{size} on lists as \isa{length}.

\subsection{Primitive recursion}

Functions on datatypes are usually defined by recursion. In fact, most of the

time they are defined by what is called \bfindex{primitive recursion}.

The keyword \isacommand{primrec}\indexbold{*primrec} is followed by a list of

equations

\[ f \, x@1 \, \dots \, (C \, y@1 \, \dots \, y@k)\, \dots \, x@n = r \]

such that $C$ is a constructor of the datatype $t$ and all recursive calls of

$f$ in $r$ are of the form $f \, \dots \, y@i \, \dots$ for some $i$. Thus

Isabelle immediately sees that $f$ terminates because one (fixed!) argument

becomes smaller with every recursive call. There must be exactly one equation

for each constructor.  Their order is immaterial.

A more general method for defining total recursive functions is introduced in

{\S}\ref{sec:recdef}.

\begin{exercise}\label{ex:Tree}

\input{Misc/document/Tree.tex}%

\end{exercise}

\input{Misc/document/case_exprs.tex}

\begin{warn}

  Induction is only allowed on free (or \isasymAnd-bound) variables that

  should not occur among the assumptions of the subgoal; see

  {\S}\ref{sec:ind-var-in-prems} for details. Case distinction

  (\isa{case_tac}) works for arbitrary terms, which need to be

  quoted if they are non-atomic.

\end{warn}

\input{Ifexpr/document/Ifexpr.tex}

\section{Some basic types}

\subsection{Natural numbers}

\label{sec:nat}

\index{arithmetic|(}

\input{Misc/document/fakenat.tex}

\input{Misc/document/natsum.tex}

\index{arithmetic|)}

\subsection{Pairs}

\input{Misc/document/pairs.tex}

\section{Definitions}

\label{sec:Definitions}

A definition is simply an abbreviation, i.e.\ a new name for an existing

construction. In particular, definitions cannot be recursive. Isabelle offers

definitions on the level of types and terms. Those on the type level are

called type synonyms, those on the term level are called (constant)

definitions.

\subsection{Type synonyms}

\indexbold{type synonym}

Type synonyms are similar to those found in ML. Their syntax is fairly self

explanatory:

\input{Misc/document/types.tex}%

Note that pattern-matching is not allowed, i.e.\ each definition must be of

the form $f\,x@1\,\dots\,x@n~\isasymequiv~t$.

Section~{\S}\ref{sec:Simplification} explains how definitions are used

in proofs.

\input{Misc/document/prime_def.tex}

\chapter{More Functional Programming}

The purpose of this chapter is to deepen the reader's understanding of the

concepts encountered so far and to introduce advanced forms of datatypes and

recursive functions. The first two sections give a structured presentation of

theorem proving by simplification ({\S}\ref{sec:Simplification}) and discuss

important heuristics for induction ({\S}\ref{sec:InductionHeuristics}). They can

be skipped by readers less interested in proofs. They are followed by a case

study, a compiler for expressions ({\S}\ref{sec:ExprCompiler}). Advanced

datatypes, including those involving function spaces, are covered in

{\S}\ref{sec:advanced-datatypes}, which closes with another case study, search

trees (``tries'').  Finally we introduce \isacommand{recdef}, a very general

form of recursive function definition which goes well beyond what

\isacommand{primrec} allows ({\S}\ref{sec:recdef}).

\section{Simplification}

\label{sec:Simplification}

\index{simplification|(}

So far we have proved our theorems by \isa{auto}, which ``simplifies''

\emph{all} subgoals. In fact, \isa{auto} can do much more than that, except

that it did not need to so far. However, when you go beyond toy examples, you

need to understand the ingredients of \isa{auto}.  This section covers the

method that \isa{auto} always applies first, namely simplification.

Simplification is one of the central theorem proving tools in Isabelle and

many other systems. The tool itself is called the \bfindex{simplifier}. The

purpose of this section is introduce the many features of the simplifier.

Anybody intending to use HOL should read this section. Later on

({\S}\ref{sec:simplification-II}) we explain some more advanced features and a

little bit of how the simplifier works. The serious student should read that

section as well, in particular in order to understand what happened if things

do not simplify as expected.

\subsubsection{What is simplification}

In its most basic form, simplification means repeated application of

equations from left to right. For example, taking the rules for \isa{\at}

and applying them to the term \isa{[0,1] \at\ []} results in a sequence of

simplification steps:

\begin{ttbox}\makeatother

(0#1#[]) @ []  \(\leadsto\)  0#((1#[]) @ [])  \(\leadsto\)  0#(1#([] @ []))  \(\leadsto\)  0#1#[]

\end{ttbox}

This is also known as \bfindex{term rewriting}\indexbold{rewriting} and the

equations are referred to as \textbf{rewrite rules}\indexbold{rewrite rule}.

``Rewriting'' is more honest than ``simplification'' because the terms do not

necessarily become simpler in the process.

\input{Misc/document/simp.tex}

\index{simplification|)}

\input{Misc/document/Itrev.tex}

\begin{exercise}

\input{Misc/document/Tree2.tex}%

\end{exercise}

\input{CodeGen/document/CodeGen.tex}

\section{Advanced datatypes}

\label{sec:advanced-datatypes}

\index{*datatype|(}

\index{*primrec|(}

%|)

This section presents advanced forms of \isacommand{datatype}s.

\subsection{Mutual recursion}

\label{sec:datatype-mut-rec}

\input{Datatype/document/ABexpr.tex}

\subsection{Nested recursion}

\label{sec:nested-datatype}

{\makeatother\input{Datatype/document/Nested.tex}}

\subsection{The limits of nested recursion}

How far can we push nested recursion? By the unfolding argument above, we can

reduce nested to mutual recursion provided the nested recursion only involves

previously defined datatypes. This does not include functions:

\begin{isabelle}

\isacommand{datatype} t = C "t \isasymRightarrow\ bool"

\end{isabelle}

is a real can of worms: in HOL it must be ruled out because it requires a type

\isa{t} such that \isa{t} and its power set \isa{t \isasymFun\ bool} have the

same cardinality---an impossibility. For the same reason it is not possible

to allow recursion involving the type \isa{set}, which is isomorphic to

\isa{t \isasymFun\ bool}.

Fortunately, a limited form of recursion

involving function spaces is permitted: the recursive type may occur on the

right of a function arrow, but never on the left. Hence the above can of worms

is ruled out but the following example of a potentially infinitely branching tree is

accepted:

\smallskip

\input{Datatype/document/Fundata.tex}

\bigskip

If you need nested recursion on the left of a function arrow, there are

alternatives to pure HOL: LCF~\cite{paulson87} is a logic where types like

\begin{isabelle}

\isacommand{datatype} lam = C "lam \isasymrightarrow\ lam"

\end{isabelle}

do indeed make sense (but note the intentionally different arrow

\isa{\isasymrightarrow}). There is even a version of LCF on top of HOL,

called HOLCF~\cite{MuellerNvOS99}.

\index{*primrec|)}

\index{*datatype|)}

\subsection{Case study: Tries}

Tries are a classic search tree data structure~\cite{Knuth3-75} for fast

indexing with strings. Figure~\ref{fig:trie} gives a graphical example of a

trie containing the words ``all'', ``an'', ``ape'', ``can'', ``car'' and

``cat''.  When searching a string in a trie, the letters of the string are

examined sequentially. Each letter determines which subtrie to search next.

In this case study we model tries as a datatype, define a lookup and an

update function, and prove that they behave as expected.

\begin{figure}[htbp]

\begin{center}

\unitlength1mm

\begin{picture}(60,30)

\put( 5, 0){\makebox(0,0)[b]{l}}

\put(25, 0){\makebox(0,0)[b]{e}}

\put(35, 0){\makebox(0,0)[b]{n}}

\put(45, 0){\makebox(0,0)[b]{r}}

\put(55, 0){\makebox(0,0)[b]{t}}

%

\put( 5, 9){\line(0,-1){5}}

\put(25, 9){\line(0,-1){5}}

\put(44, 9){\line(-3,-2){9}}

\put(45, 9){\line(0,-1){5}}

\put(46, 9){\line(3,-2){9}}

%

\put( 5,10){\makebox(0,0)[b]{l}}

\put(15,10){\makebox(0,0)[b]{n}}

\put(25,10){\makebox(0,0)[b]{p}}

\put(45,10){\makebox(0,0)[b]{a}}

%

\put(14,19){\line(-3,-2){9}}

\put(15,19){\line(0,-1){5}}

\put(16,19){\line(3,-2){9}}

\put(45,19){\line(0,-1){5}}

%

\put(15,20){\makebox(0,0)[b]{a}}

\put(45,20){\makebox(0,0)[b]{c}}

%

\put(30,30){\line(-3,-2){13}}

\put(30,30){\line(3,-2){13}}

\end{picture}

\end{center}

\caption{A sample trie}

\label{fig:trie}

\end{figure}

Proper tries associate some value with each string. Since the

information is stored only in the final node associated with the string, many

nodes do not carry any value. This distinction is captured by the

following predefined datatype (from theory \isa{Option}, which is a parent

of \isa{Main}):

\smallskip

\input{Trie/document/Option2.tex}

\indexbold{*option}\indexbold{*None}\indexbold{*Some}%

\input{Trie/document/Trie.tex}

\begin{exercise}

  Write an improved version of \isa{update} that does not suffer from the

  space leak in the version above. Prove the main theorem for your improved

  \isa{update}.

\end{exercise}

\begin{exercise}

  Write a function to \emph{delete} entries from a trie. An easy solution is

  a clever modification of \isa{update} which allows both insertion and

  deletion with a single function.  Prove (a modified version of) the main

  theorem above. Optimize you function such that it shrinks tries after

  deletion, if possible.

\end{exercise}

\section{Total recursive functions}

\label{sec:recdef}

\index{*recdef|(}

Although many total functions have a natural primitive recursive definition,

this is not always the case. Arbitrary total recursive functions can be

defined by means of \isacommand{recdef}: you can use full pattern-matching,

recursion need not involve datatypes, and termination is proved by showing

that the arguments of all recursive calls are smaller in a suitable (user

supplied) sense. In this section we ristrict ourselves to measure functions;

more advanced termination proofs are discussed in {\S}\ref{sec:beyond-measure}.

\subsection{Defining recursive functions}

\input{Recdef/document/examples.tex}

\subsection{Proving termination}

\input{Recdef/document/termination.tex}

\subsection{Simplification with recdef}

\label{sec:recdef-simplification}

\input{Recdef/document/simplification.tex}

\subsection{Induction}

\index{induction!recursion|(}

\index{recursion induction|(}

\input{Recdef/document/Induction.tex}

\label{sec:recdef-induction}

\index{induction!recursion|)}

\index{recursion induction|)}

\index{*recdef|)}