doc-src/TutorialI/fp.tex
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\chapter{Functional Programming in HOL}
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Although on the surface this chapter is mainly concerned with how to write
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functional programs in HOL and how to verify them, most of the
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constructs and proof procedures introduced are general purpose and recur in
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any specification or verification task.
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The dedicated functional programmer should be warned: HOL offers only
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\emph{total functional programming} --- all functions in HOL must be total;
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lazy data structures are not directly available. On the positive side,
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functions in HOL need not be computable: HOL is a specification language that
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goes well beyond what can be expressed as a program. However, for the time
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being we concentrate on the computable.
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\section{An introductory theory}
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\label{sec:intro-theory}
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Functional programming needs datatypes and functions. Both of them can be
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defined in a theory with a syntax reminiscent of languages like ML or
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Haskell. As an example consider the theory in figure~\ref{fig:ToyList}.
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We will now examine it line by line.
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\begin{figure}[htbp]
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\begin{ttbox}\makeatother
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\input{ToyList2/ToyList1}\end{ttbox}
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\caption{A theory of lists}
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\label{fig:ToyList}
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\end{figure}
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{\makeatother\input{ToyList/document/ToyList.tex}}
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The complete proof script is shown in figure~\ref{fig:ToyList-proofs}. The
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concatenation of figures \ref{fig:ToyList} and \ref{fig:ToyList-proofs}
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constitutes the complete theory \texttt{ToyList} and should reside in file
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\texttt{ToyList.thy}. It is good practice to present all declarations and
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definitions at the beginning of a theory to facilitate browsing.
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\begin{figure}[htbp]
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\begin{ttbox}\makeatother
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\input{ToyList2/ToyList2}\end{ttbox}
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\caption{Proofs about lists}
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\label{fig:ToyList-proofs}
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\end{figure}
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\subsubsection*{Review}
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This is the end of our toy proof. It should have familiarized you with
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\begin{itemize}
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\item the standard theorem proving procedure:
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state a goal (lemma or theorem); proceed with proof until a separate lemma is
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required; prove that lemma; come back to the original goal.
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\item a specific procedure that works well for functional programs:
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induction followed by all-out simplification via \isa{auto}.
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\item a basic repertoire of proof commands.
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\end{itemize}
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\section{Some helpful commands}
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\label{sec:commands-and-hints}
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This section discusses a few basic commands for manipulating the proof state
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and can be skipped by casual readers.
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There are two kinds of commands used during a proof: the actual proof
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commands and auxiliary commands for examining the proof state and controlling
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the display. Simple proof commands are of the form
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\isacommand{apply}\isa{(method)}\indexbold{apply} where \bfindex{method} is a
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synonym for ``theorem proving function''. Typical examples are
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\isa{induct_tac} and \isa{auto}. Further methods are introduced throughout
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the tutorial.  Unless stated otherwise you may assume that a method attacks
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merely the first subgoal. An exception is \isa{auto} which tries to solve all
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subgoals.
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The most useful auxiliary commands are:
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\begin{description}
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\item[Undoing:] \isacommand{undo}\indexbold{*undo} undoes the effect of the
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  last command; \isacommand{undo} can be undone by
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  \isacommand{redo}\indexbold{*redo}.  Both are only needed at the shell
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  level and should not occur in the final theory.
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\item[Printing the current state:] \isacommand{pr}\indexbold{*pr} redisplays
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  the current proof state, for example when it has disappeared off the
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  screen.
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\item[Limiting the number of subgoals:] \isacommand{pr}~$n$ tells Isabelle to
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  print only the first $n$ subgoals from now on and redisplays the current
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  proof state. This is helpful when there are many subgoals.
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\item[Modifying the order of subgoals:]
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\isacommand{defer}\indexbold{*defer} moves the first subgoal to the end and
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\isacommand{prefer}\indexbold{*prefer}~$n$ moves subgoal $n$ to the front.
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\item[Printing theorems:]
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  \isacommand{thm}\indexbold{*thm}~\textit{name}$@1$~\dots~\textit{name}$@n$
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  prints the named theorems.
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\item[Displaying types:] We have already mentioned the flag
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  \ttindex{show_types} above. It can also be useful for detecting typos in
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  formulae early on. For example, if \texttt{show_types} is set and the goal
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  \isa{rev(rev xs) = xs} is started, Isabelle prints the additional output
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\par\noindent
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\begin{isabelle}%
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Variables:\isanewline
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~~xs~::~'a~list
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\end{isabelle}%
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\par\noindent
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which tells us that Isabelle has correctly inferred that
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\isa{xs} is a variable of list type. On the other hand, had we
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made a typo as in \isa{rev(re xs) = xs}, the response
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\par\noindent
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\begin{isabelle}%
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Variables:\isanewline
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~~re~::~'a~list~{\isasymRightarrow}~'a~list\isanewline
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~~xs~::~'a~list%
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\end{isabelle}%
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\par\noindent
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would have alerted us because of the unexpected variable \isa{re}.
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\item[Reading terms and types:] \isacommand{term}\indexbold{*term}
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  \textit{string} reads, type-checks and prints the given string as a term in
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  the current context; the inferred type is output as well.
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  \isacommand{typ}\indexbold{*typ} \textit{string} reads and prints the given
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  string as a type in the current context.
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\item[(Re)loading theories:] When you start your interaction you must open a
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  named theory with the line \isa{\isacommand{theory}~T~=~\dots~:}. Isabelle
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  automatically loads all the required parent theories from their respective
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  files (which may take a moment, unless the theories are already loaded and
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  the files have not been modified).
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  If you suddenly discover that you need to modify a parent theory of your
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  current theory you must first abandon your current theory\indexbold{abandon
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  theory}\indexbold{theory!abandon} (at the shell
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  level type \isacommand{kill}\indexbold{*kill}). After the parent theory has
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  been modified you go back to your original theory. When its first line
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  \isacommand{theory}\texttt{~T~=}~\dots~\texttt{:} is processed, the
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  modified parent is reloaded automatically.
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  The only time when you need to load a theory by hand is when you simply
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  want to check if it loads successfully without wanting to make use of the
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  theory itself. This you can do by typing
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  \isa{\isacommand{use\_thy}\indexbold{*use_thy}~"T"}.
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\end{description}
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Further commands are found in the Isabelle/Isar Reference Manual.
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We now examine Isabelle's functional programming constructs systematically,
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starting with inductive datatypes.
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\section{Datatypes}
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\label{sec:datatype}
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Inductive datatypes are part of almost every non-trivial application of HOL.
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First we take another look at a very important example, the datatype of
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lists, before we turn to datatypes in general. The section closes with a
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case study.
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\subsection{Lists}
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\indexbold{*list}
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Lists are one of the essential datatypes in computing. Readers of this
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tutorial and users of HOL need to be familiar with their basic operations.
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Theory \isa{ToyList} is only a small fragment of HOL's predefined theory
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\isa{List}\footnote{\url{http://isabelle.in.tum.de/library/HOL/List.html}}.
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The latter contains many further operations. For example, the functions
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\isaindexbold{hd} (``head'') and \isaindexbold{tl} (``tail'') return the first
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element and the remainder of a list. (However, pattern-matching is usually
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preferable to \isa{hd} and \isa{tl}.)  Theory \isa{List} also contains
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more syntactic sugar: \isa{[}$x@1$\isa{,}\dots\isa{,}$x@n$\isa{]} abbreviates
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$x@1$\isa{\#}\dots\isa{\#}$x@n$\isa{\#[]}.  In the rest of the tutorial we
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always use HOL's predefined lists.
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\subsection{The general format}
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\label{sec:general-datatype}
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The general HOL \isacommand{datatype} definition is of the form
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\[
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\isacommand{datatype}~(\alpha@1, \dots, \alpha@n) \, t ~=~
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C@1~\tau@{11}~\dots~\tau@{1k@1} ~\mid~ \dots ~\mid~
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C@m~\tau@{m1}~\dots~\tau@{mk@m}
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\]
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where $\alpha@i$ are distinct type variables (the parameters), $C@i$ are distinct
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constructor names and $\tau@{ij}$ are types; it is customary to capitalize
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the first letter in constructor names. There are a number of
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restrictions (such as that the type should not be empty) detailed
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elsewhere~\cite{isabelle-HOL}. Isabelle notifies you if you violate them.
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Laws about datatypes, such as \isa{[] \isasymnoteq~x\#xs} and
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\isa{(x\#xs = y\#ys) = (x=y \isasymand~xs=ys)}, are used automatically
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during proofs by simplification.  The same is true for the equations in
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primitive recursive function definitions.
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Every datatype $t$ comes equipped with a \isa{size} function from $t$ into
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the natural numbers (see~\S\ref{sec:nat} below). For lists, \isa{size} is
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just the length, i.e.\ \isa{size [] = 0} and \isa{size(x \# xs) = size xs +
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  1}.  In general, \isa{size} returns \isa{0} for all constructors that do
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not have an argument of type $t$, and for all other constructors \isa{1 +}
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the sum of the sizes of all arguments of type $t$. Note that because
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\isa{size} is defined on every datatype, it is overloaded; on lists
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\isa{size} is also called \isa{length}, which is not overloaded.
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\subsection{Primitive recursion}
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Functions on datatypes are usually defined by recursion. In fact, most of the
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time they are defined by what is called \bfindex{primitive recursion}.
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The keyword \isacommand{primrec}\indexbold{*primrec} is followed by a list of
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equations
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\[ f \, x@1 \, \dots \, (C \, y@1 \, \dots \, y@k)\, \dots \, x@n = r \]
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such that $C$ is a constructor of the datatype $t$ and all recursive calls of
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$f$ in $r$ are of the form $f \, \dots \, y@i \, \dots$ for some $i$. Thus
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Isabelle immediately sees that $f$ terminates because one (fixed!) argument
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becomes smaller with every recursive call. There must be exactly one equation
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for each constructor.  Their order is immaterial.
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A more general method for defining total recursive functions is introduced in
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\S\ref{sec:recdef}.
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\begin{exercise}\label{ex:Tree}
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\input{Misc/document/Tree.tex}%
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\end{exercise}
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\input{Misc/document/case_exprs.tex}
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\begin{warn}
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  Induction is only allowed on free (or \isasymAnd-bound) variables that
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  should not occur among the assumptions of the subgoal; see
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  \S\ref{sec:ind-var-in-prems} for details. Case distinction
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  (\isa{case_tac}) works for arbitrary terms, which need to be
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  quoted if they are non-atomic.
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\end{warn}
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\subsection{Case study: boolean expressions}
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\label{sec:boolex}
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The aim of this case study is twofold: it shows how to model boolean
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expressions and some algorithms for manipulating them, and it demonstrates
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the constructs introduced above.
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\input{Ifexpr/document/Ifexpr.tex}
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\medskip
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How does one come up with the required lemmas? Try to prove the main theorems
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without them and study carefully what \isa{auto} leaves unproved. This has
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to provide the clue.  The necessity of universal quantification
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(\isa{\isasymforall{}t e}) in the two lemmas is explained in
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\S\ref{sec:InductionHeuristics}
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\begin{exercise}
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  We strengthen the definition of a \isa{normal} If-expression as follows:
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  the first argument of all \isa{IF}s must be a variable. Adapt the above
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  development to this changed requirement. (Hint: you may need to formulate
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  some of the goals as implications (\isasymimp) rather than equalities
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  (\isa{=}).)
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\end{exercise}
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\section{Some basic types}
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\subsection{Natural numbers}
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\label{sec:nat}
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\index{arithmetic|(}
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\input{Misc/document/fakenat.tex}
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\input{Misc/document/natsum.tex}
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The usual arithmetic operations \ttindexboldpos{+}{$HOL2arithfun},
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\ttindexboldpos{-}{$HOL2arithfun}, \ttindexboldpos{*}{$HOL2arithfun},
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\isaindexbold{div}, \isaindexbold{mod}, \isaindexbold{min} and
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\isaindexbold{max} are predefined, as are the relations
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\indexboldpos{\isasymle}{$HOL2arithrel} and
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\ttindexboldpos{<}{$HOL2arithrel}. There is even a least number operation
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\isaindexbold{LEAST}. For example, \isa{(LEAST n.$\,$1 < n) = 2}, although
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Isabelle does not prove this completely automatically. Note that \isa{1} and
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\isa{2} are available as abbreviations for the corresponding
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\isa{Suc}-expressions. If you need the full set of numerals,
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see~\S\ref{nat-numerals}.
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\begin{warn}
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  The constant \ttindexbold{0} and the operations
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  \ttindexboldpos{+}{$HOL2arithfun}, \ttindexboldpos{-}{$HOL2arithfun},
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  \ttindexboldpos{*}{$HOL2arithfun}, \isaindexbold{min}, \isaindexbold{max},
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  \indexboldpos{\isasymle}{$HOL2arithrel} and
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  \ttindexboldpos{<}{$HOL2arithrel} are overloaded, i.e.\ they are available
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  not just for natural numbers but at other types as well (see
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  \S\ref{sec:TypeClasses}). For example, given the goal \isa{x+0 = x}, there
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  is nothing to indicate that you are talking about natural numbers.  Hence
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  Isabelle can only infer that \isa{x} is of some arbitrary type where
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  \isa{0} and \isa{+} are declared. As a consequence, you will be unable to
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  prove the goal (although it may take you some time to realize what has
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  happened if \texttt{show_types} is not set).  In this particular example,
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  you need to include an explicit type constraint, for example \isa{x+0 =
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    (x::nat)}.  If there is enough contextual information this may not be
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  necessary: \isa{Suc x = x} automatically implies \isa{x::nat} because
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  \isa{Suc} is not overloaded.
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\end{warn}
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Simple arithmetic goals are proved automatically by both \isa{auto}
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and the simplification methods introduced in \S\ref{sec:Simplification}.  For
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example,
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\input{Misc/document/arith1.tex}%
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is proved automatically. The main restriction is that only addition is taken
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into account; other arithmetic operations and quantified formulae are ignored.
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For more complex goals, there is the special method
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\isaindexbold{arith} (which attacks the first subgoal). It proves
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arithmetic goals involving the usual logical connectives (\isasymnot,
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\isasymand, \isasymor, \isasymimp), the relations \isasymle\ and \isa{<}, and
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the operations \isa{+}, \isa{-}, \isa{min} and \isa{max}. For example,
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\input{Misc/document/arith2.tex}%
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succeeds because \isa{k*k} can be treated as atomic.
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In contrast,
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\input{Misc/document/arith3.tex}%
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is not even proved by \isa{arith} because the proof relies essentially
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on properties of multiplication.
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\begin{warn}
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  The running time of \isa{arith} is exponential in the number of occurrences
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  of \ttindexboldpos{-}{$HOL2arithfun}, \isaindexbold{min} and
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  \isaindexbold{max} because they are first eliminated by case distinctions.
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  \isa{arith} is incomplete even for the restricted class of formulae
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  described above (known as ``linear arithmetic''). If divisibility plays a
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  role, it may fail to prove a valid formula, for example $m+m \neq n+n+1$.
nipkow@8743
   323
  Fortunately, such examples are rare in practice.
nipkow@8743
   324
\end{warn}
nipkow@8743
   325
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   326
\index{arithmetic|)}
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   327
nipkow@8743
   328
nipkow@8743
   329
\subsection{Products}
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   330
\input{Misc/document/pairs.tex}
nipkow@8743
   331
nipkow@8743
   332
%FIXME move stuff below into section on proofs about products?
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   333
\begin{warn}
nipkow@8743
   334
  Abstraction over pairs and tuples is merely a convenient shorthand for a
nipkow@8743
   335
  more complex internal representation.  Thus the internal and external form
nipkow@8743
   336
  of a term may differ, which can affect proofs. If you want to avoid this
nipkow@8743
   337
  complication, use \isa{fst} and \isa{snd}, i.e.\ write
nipkow@8743
   338
  \isa{\isasymlambda{}p.~fst p + snd p} instead of
nipkow@8743
   339
  \isa{\isasymlambda(x,y).~x + y}.  See~\S\ref{proofs-about-products} for
nipkow@8743
   340
  theorem proving with tuple patterns.
nipkow@8743
   341
\end{warn}
nipkow@8743
   342
nipkow@9541
   343
Note that products, like natural numbers, are datatypes, which means
nipkow@8743
   344
in particular that \isa{induct_tac} and \isa{case_tac} are applicable to
nipkow@8743
   345
products (see \S\ref{proofs-about-products}).
nipkow@8743
   346
nipkow@9541
   347
Instead of tuples with many components (where ``many'' is not much above 2),
nipkow@9541
   348
it is far preferable to use record types (see \S\ref{sec:records}).
nipkow@9541
   349
nipkow@8743
   350
\section{Definitions}
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   351
\label{sec:Definitions}
nipkow@8743
   352
nipkow@8743
   353
A definition is simply an abbreviation, i.e.\ a new name for an existing
nipkow@8743
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construction. In particular, definitions cannot be recursive. Isabelle offers
nipkow@8743
   355
definitions on the level of types and terms. Those on the type level are
nipkow@8743
   356
called type synonyms, those on the term level are called (constant)
nipkow@8743
   357
definitions.
nipkow@8743
   358
nipkow@8743
   359
nipkow@8743
   360
\subsection{Type synonyms}
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   361
\indexbold{type synonym}
nipkow@8743
   362
nipkow@8743
   363
Type synonyms are similar to those found in ML. Their syntax is fairly self
nipkow@8743
   364
explanatory:
nipkow@8743
   365
nipkow@8743
   366
\input{Misc/document/types.tex}%
nipkow@8743
   367
nipkow@8743
   368
Note that pattern-matching is not allowed, i.e.\ each definition must be of
nipkow@8743
   369
the form $f\,x@1\,\dots\,x@n~\isasymequiv~t$.
nipkow@8743
   370
Section~\S\ref{sec:Simplification} explains how definitions are used
nipkow@8743
   371
in proofs.
nipkow@8743
   372
nipkow@8743
   373
\begin{warn}%
nipkow@8743
   374
A common mistake when writing definitions is to introduce extra free
nipkow@8743
   375
variables on the right-hand side as in the following fictitious definition:
nipkow@8743
   376
\input{Misc/document/prime_def.tex}%
nipkow@8743
   377
\end{warn}
nipkow@8743
   378
nipkow@8743
   379
nipkow@8743
   380
\chapter{More Functional Programming}
nipkow@8743
   381
nipkow@8743
   382
The purpose of this chapter is to deepen the reader's understanding of the
nipkow@8771
   383
concepts encountered so far and to introduce advanced forms of datatypes and
nipkow@8771
   384
recursive functions. The first two sections give a structured presentation of
nipkow@8771
   385
theorem proving by simplification (\S\ref{sec:Simplification}) and discuss
nipkow@8771
   386
important heuristics for induction (\S\ref{sec:InductionHeuristics}). They can
nipkow@8771
   387
be skipped by readers less interested in proofs. They are followed by a case
nipkow@8771
   388
study, a compiler for expressions (\S\ref{sec:ExprCompiler}). Advanced
nipkow@8771
   389
datatypes, including those involving function spaces, are covered in
nipkow@8771
   390
\S\ref{sec:advanced-datatypes}, which closes with another case study, search
nipkow@8771
   391
trees (``tries'').  Finally we introduce \isacommand{recdef}, a very general
nipkow@8771
   392
form of recursive function definition which goes well beyond what
nipkow@8771
   393
\isacommand{primrec} allows (\S\ref{sec:recdef}).
nipkow@8743
   394
nipkow@8743
   395
nipkow@8743
   396
\section{Simplification}
nipkow@8743
   397
\label{sec:Simplification}
nipkow@8743
   398
\index{simplification|(}
nipkow@8743
   399
nipkow@9541
   400
So far we have proved our theorems by \isa{auto}, which ``simplifies''
nipkow@9541
   401
\emph{all} subgoals. In fact, \isa{auto} can do much more than that, except
nipkow@9541
   402
that it did not need to so far. However, when you go beyond toy examples, you
nipkow@9541
   403
need to understand the ingredients of \isa{auto}.  This section covers the
nipkow@9541
   404
method that \isa{auto} always applies first, namely simplification.
nipkow@8743
   405
nipkow@8743
   406
Simplification is one of the central theorem proving tools in Isabelle and
nipkow@8743
   407
many other systems. The tool itself is called the \bfindex{simplifier}. The
nipkow@8743
   408
purpose of this section is twofold: to introduce the many features of the
nipkow@8743
   409
simplifier (\S\ref{sec:SimpFeatures}) and to explain a little bit how the
nipkow@8743
   410
simplifier works (\S\ref{sec:SimpHow}).  Anybody intending to use HOL should
nipkow@8743
   411
read \S\ref{sec:SimpFeatures}, and the serious student should read
nipkow@8743
   412
\S\ref{sec:SimpHow} as well in order to understand what happened in case
nipkow@8743
   413
things do not simplify as expected.
nipkow@8743
   414
nipkow@8743
   415
nipkow@8743
   416
\subsection{Using the simplifier}
nipkow@8743
   417
\label{sec:SimpFeatures}
nipkow@8743
   418
nipkow@9458
   419
\subsubsection{What is simplification}
nipkow@9458
   420
nipkow@8743
   421
In its most basic form, simplification means repeated application of
nipkow@8743
   422
equations from left to right. For example, taking the rules for \isa{\at}
nipkow@8743
   423
and applying them to the term \isa{[0,1] \at\ []} results in a sequence of
nipkow@8743
   424
simplification steps:
nipkow@8743
   425
\begin{ttbox}\makeatother
nipkow@8743
   426
(0#1#[]) @ []  \(\leadsto\)  0#((1#[]) @ [])  \(\leadsto\)  0#(1#([] @ []))  \(\leadsto\)  0#1#[]
nipkow@8743
   427
\end{ttbox}
nipkow@8743
   428
This is also known as \bfindex{term rewriting} and the equations are referred
nipkow@8771
   429
to as \bfindex{rewrite rules}. ``Rewriting'' is more honest than ``simplification''
nipkow@8743
   430
because the terms do not necessarily become simpler in the process.
nipkow@8743
   431
nipkow@8743
   432
\subsubsection{Simplification rules}
nipkow@8743
   433
\indexbold{simplification rules}
nipkow@8743
   434
nipkow@8743
   435
To facilitate simplification, theorems can be declared to be simplification
nipkow@8743
   436
rules (with the help of the attribute \isa{[simp]}\index{*simp
nipkow@8743
   437
  (attribute)}), in which case proofs by simplification make use of these
nipkow@8771
   438
rules automatically. In addition the constructs \isacommand{datatype} and
nipkow@8743
   439
\isacommand{primrec} (and a few others) invisibly declare useful
nipkow@8743
   440
simplification rules. Explicit definitions are \emph{not} declared
nipkow@8743
   441
simplification rules automatically!
nipkow@8743
   442
nipkow@8743
   443
Not merely equations but pretty much any theorem can become a simplification
nipkow@8743
   444
rule. The simplifier will try to make sense of it.  For example, a theorem
nipkow@8743
   445
\isasymnot$P$ is automatically turned into \isa{$P$ = False}. The details
nipkow@8743
   446
are explained in \S\ref{sec:SimpHow}.
nipkow@8743
   447
nipkow@8743
   448
The simplification attribute of theorems can be turned on and off as follows:
nipkow@8743
   449
\begin{ttbox}
nipkow@9541
   450
lemmas [simp] = \(list of theorem names\);
nipkow@9541
   451
lemmas [simp del] = \(list of theorem names\);
nipkow@8743
   452
\end{ttbox}
nipkow@8771
   453
As a rule of thumb, equations that really simplify (like \isa{rev(rev xs) =
nipkow@8743
   454
  xs} and \mbox{\isa{xs \at\ [] = xs}}) should be made simplification
nipkow@8743
   455
rules.  Those of a more specific nature (e.g.\ distributivity laws, which
nipkow@8743
   456
alter the structure of terms considerably) should only be used selectively,
nipkow@8743
   457
i.e.\ they should not be default simplification rules.  Conversely, it may
nipkow@8743
   458
also happen that a simplification rule needs to be disabled in certain
nipkow@8743
   459
proofs.  Frequent changes in the simplification status of a theorem may
nipkow@8771
   460
indicate a badly designed theory.
nipkow@8743
   461
\begin{warn}
nipkow@8743
   462
  Simplification may not terminate, for example if both $f(x) = g(x)$ and
nipkow@8743
   463
  $g(x) = f(x)$ are simplification rules. It is the user's responsibility not
nipkow@8743
   464
  to include simplification rules that can lead to nontermination, either on
nipkow@8743
   465
  their own or in combination with other simplification rules.
nipkow@8743
   466
\end{warn}
nipkow@8743
   467
nipkow@8743
   468
\subsubsection{The simplification method}
nipkow@8743
   469
\index{*simp (method)|bold}
nipkow@8743
   470
nipkow@8743
   471
The general format of the simplification method is
nipkow@8743
   472
\begin{ttbox}
nipkow@8743
   473
simp \(list of modifiers\)
nipkow@8743
   474
\end{ttbox}
nipkow@8743
   475
where the list of \emph{modifiers} helps to fine tune the behaviour and may
nipkow@8743
   476
be empty. Most if not all of the proofs seen so far could have been performed
nipkow@8743
   477
with \isa{simp} instead of \isa{auto}, except that \isa{simp} attacks
nipkow@9689
   478
only the first subgoal and may thus need to be repeated---use \isaindex{simp_all}
nipkow@9689
   479
to simplify all subgoals.
nipkow@8743
   480
Note that \isa{simp} fails if nothing changes.
nipkow@8743
   481
nipkow@8743
   482
\subsubsection{Adding and deleting simplification rules}
nipkow@8743
   483
nipkow@8743
   484
If a certain theorem is merely needed in a few proofs by simplification,
nipkow@8743
   485
we do not need to make it a global simplification rule. Instead we can modify
nipkow@8743
   486
the set of simplification rules used in a simplification step by adding rules
nipkow@8743
   487
to it and/or deleting rules from it. The two modifiers for this are
nipkow@8743
   488
\begin{ttbox}
nipkow@8743
   489
add: \(list of theorem names\)
nipkow@8743
   490
del: \(list of theorem names\)
nipkow@8743
   491
\end{ttbox}
nipkow@8743
   492
In case you want to use only a specific list of theorems and ignore all
nipkow@8743
   493
others:
nipkow@8743
   494
\begin{ttbox}
nipkow@8743
   495
only: \(list of theorem names\)
nipkow@8743
   496
\end{ttbox}
nipkow@8743
   497
nipkow@8743
   498
nipkow@8743
   499
\subsubsection{Assumptions}
nipkow@8743
   500
\index{simplification!with/of assumptions}
nipkow@8743
   501
nipkow@8743
   502
{\makeatother\input{Misc/document/asm_simp.tex}}
nipkow@8743
   503
nipkow@8743
   504
\subsubsection{Rewriting with definitions}
nipkow@8743
   505
\index{simplification!with definitions}
nipkow@8743
   506
nipkow@8743
   507
\input{Misc/document/def_rewr.tex}
nipkow@8743
   508
nipkow@8743
   509
\begin{warn}
nipkow@8743
   510
  If you have defined $f\,x\,y~\isasymequiv~t$ then you can only expand
nipkow@8743
   511
  occurrences of $f$ with at least two arguments. Thus it is safer to define
nipkow@8743
   512
  $f$~\isasymequiv~\isasymlambda$x\,y.\;t$.
nipkow@8743
   513
\end{warn}
nipkow@8743
   514
nipkow@8743
   515
\subsubsection{Simplifying let-expressions}
nipkow@8743
   516
\index{simplification!of let-expressions}
nipkow@8743
   517
nipkow@8743
   518
Proving a goal containing \isaindex{let}-expressions almost invariably
nipkow@8743
   519
requires the \isa{let}-con\-structs to be expanded at some point. Since
nipkow@8771
   520
\isa{let}-\isa{in} is just syntactic sugar for a predefined constant (called
nipkow@8743
   521
\isa{Let}), expanding \isa{let}-constructs means rewriting with
nipkow@8743
   522
\isa{Let_def}:
nipkow@8743
   523
nipkow@8743
   524
{\makeatother\input{Misc/document/let_rewr.tex}}
nipkow@8743
   525
nipkow@8743
   526
\subsubsection{Conditional equations}
nipkow@8743
   527
nipkow@8743
   528
\input{Misc/document/cond_rewr.tex}
nipkow@8743
   529
nipkow@8743
   530
nipkow@8743
   531
\subsubsection{Automatic case splits}
nipkow@8743
   532
\indexbold{case splits}
nipkow@8743
   533
\index{*split|(}
nipkow@8743
   534
nipkow@8743
   535
{\makeatother\input{Misc/document/case_splits.tex}}
nipkow@8743
   536
\index{*split|)}
nipkow@8743
   537
nipkow@8743
   538
\begin{warn}
nipkow@8743
   539
  The simplifier merely simplifies the condition of an \isa{if} but not the
nipkow@8743
   540
  \isa{then} or \isa{else} parts. The latter are simplified only after the
nipkow@8743
   541
  condition reduces to \isa{True} or \isa{False}, or after splitting. The
nipkow@8743
   542
  same is true for \isaindex{case}-expressions: only the selector is
nipkow@8743
   543
  simplified at first, until either the expression reduces to one of the
nipkow@8743
   544
  cases or it is split.
nipkow@8743
   545
\end{warn}
nipkow@8743
   546
nipkow@8743
   547
\subsubsection{Arithmetic}
nipkow@8743
   548
\index{arithmetic}
nipkow@8743
   549
nipkow@8743
   550
The simplifier routinely solves a small class of linear arithmetic formulae
nipkow@8771
   551
(over type \isa{nat} and other numeric types): it only takes into account
nipkow@8743
   552
assumptions and conclusions that are (possibly negated) (in)equalities
nipkow@8743
   553
(\isa{=}, \isasymle, \isa{<}) and it only knows about addition. Thus
nipkow@8743
   554
nipkow@8743
   555
\input{Misc/document/arith1.tex}%
nipkow@8743
   556
is proved by simplification, whereas the only slightly more complex
nipkow@8743
   557
nipkow@8743
   558
\input{Misc/document/arith4.tex}%
nipkow@8743
   559
is not proved by simplification and requires \isa{arith}.
nipkow@8743
   560
nipkow@8743
   561
\subsubsection{Permutative rewrite rules}
nipkow@8743
   562
nipkow@9721
   563
A rewrite rule is \textbf{permutative} if the left-hand side and right-hand
nipkow@9721
   564
side are the same up to renaming of variables.  The most common permutative
nipkow@9721
   565
rule is commutativity: $x+y = y+x$.  Another example is $(x-y)-z = (x-z)-y$.
nipkow@9721
   566
Such rules are problematic because once they apply, they can be used forever.
nipkow@8743
   567
The simplifier is aware of this danger and treats permutative rules
nipkow@8743
   568
separately. For details see~\cite{isabelle-ref}.
nipkow@8743
   569
nipkow@8743
   570
\subsubsection{Tracing}
nipkow@8743
   571
\indexbold{tracing the simplifier}
nipkow@8743
   572
nipkow@8743
   573
{\makeatother\input{Misc/document/trace_simp.tex}}
nipkow@8743
   574
nipkow@8743
   575
\subsection{How it works}
nipkow@8743
   576
\label{sec:SimpHow}
nipkow@8743
   577
nipkow@8743
   578
\subsubsection{Higher-order patterns}
nipkow@8743
   579
nipkow@8743
   580
\subsubsection{Local assumptions}
nipkow@8743
   581
nipkow@8743
   582
\subsubsection{The preprocessor}
nipkow@8743
   583
nipkow@8743
   584
\index{simplification|)}
nipkow@8743
   585
nipkow@8743
   586
\section{Induction heuristics}
nipkow@8743
   587
\label{sec:InductionHeuristics}
nipkow@8743
   588
nipkow@8743
   589
The purpose of this section is to illustrate some simple heuristics for
nipkow@8743
   590
inductive proofs. The first one we have already mentioned in our initial
nipkow@8743
   591
example:
nipkow@8743
   592
\begin{quote}
nipkow@8743
   593
{\em 1. Theorems about recursive functions are proved by induction.}
nipkow@8743
   594
\end{quote}
nipkow@8743
   595
In case the function has more than one argument
nipkow@8743
   596
\begin{quote}
nipkow@8743
   597
{\em 2. Do induction on argument number $i$ if the function is defined by
nipkow@8743
   598
recursion in argument number $i$.}
nipkow@8743
   599
\end{quote}
nipkow@8743
   600
When we look at the proof of {\makeatother\isa{(xs @ ys) @ zs = xs @ (ys @
nipkow@8743
   601
  zs)}} in \S\ref{sec:intro-proof} we find (a) \isa{\at} is recursive in
nipkow@8743
   602
the first argument, (b) \isa{xs} occurs only as the first argument of
nipkow@8743
   603
\isa{\at}, and (c) both \isa{ys} and \isa{zs} occur at least once as
nipkow@8743
   604
the second argument of \isa{\at}. Hence it is natural to perform induction
nipkow@8743
   605
on \isa{xs}.
nipkow@8743
   606
nipkow@8743
   607
The key heuristic, and the main point of this section, is to
nipkow@8743
   608
generalize the goal before induction. The reason is simple: if the goal is
nipkow@8743
   609
too specific, the induction hypothesis is too weak to allow the induction
nipkow@8743
   610
step to go through. Let us now illustrate the idea with an example.
nipkow@8743
   611
nipkow@8743
   612
{\makeatother\input{Misc/document/Itrev.tex}}
nipkow@8743
   613
nipkow@8743
   614
A final point worth mentioning is the orientation of the equation we just
nipkow@8743
   615
proved: the more complex notion (\isa{itrev}) is on the left-hand
nipkow@8743
   616
side, the simpler \isa{rev} on the right-hand side. This constitutes
nipkow@8743
   617
another, albeit weak heuristic that is not restricted to induction:
nipkow@8743
   618
\begin{quote}
nipkow@8743
   619
  {\em 5. The right-hand side of an equation should (in some sense) be
nipkow@8743
   620
    simpler than the left-hand side.}
nipkow@8743
   621
\end{quote}
nipkow@8743
   622
The heuristic is tricky to apply because it is not obvious that
nipkow@8743
   623
\isa{rev xs \at\ ys} is simpler than \isa{itrev xs ys}. But see what
nipkow@8771
   624
happens if you try to prove \isa{rev xs \at\ ys = itrev xs ys}!
nipkow@8743
   625
nipkow@9493
   626
\begin{exercise}
nipkow@9493
   627
\input{Misc/document/Tree2.tex}%
nipkow@9493
   628
\end{exercise}
nipkow@8743
   629
nipkow@8743
   630
\section{Case study: compiling expressions}
nipkow@8743
   631
\label{sec:ExprCompiler}
nipkow@8743
   632
nipkow@8743
   633
{\makeatother\input{CodeGen/document/CodeGen.tex}}
nipkow@8743
   634
nipkow@8743
   635
nipkow@8743
   636
\section{Advanced datatypes}
nipkow@8743
   637
\label{sec:advanced-datatypes}
nipkow@8743
   638
\index{*datatype|(}
nipkow@8743
   639
\index{*primrec|(}
nipkow@8743
   640
%|)
nipkow@8743
   641
nipkow@8743
   642
This section presents advanced forms of \isacommand{datatype}s.
nipkow@8743
   643
nipkow@8743
   644
\subsection{Mutual recursion}
nipkow@8743
   645
\label{sec:datatype-mut-rec}
nipkow@8743
   646
nipkow@8743
   647
\input{Datatype/document/ABexpr.tex}
nipkow@8743
   648
nipkow@8743
   649
\subsection{Nested recursion}
nipkow@9644
   650
\label{sec:nested-datatype}
nipkow@8743
   651
nipkow@9644
   652
{\makeatother\input{Datatype/document/Nested.tex}}
nipkow@8743
   653
nipkow@8743
   654
nipkow@8743
   655
\subsection{The limits of nested recursion}
nipkow@8743
   656
nipkow@8743
   657
How far can we push nested recursion? By the unfolding argument above, we can
nipkow@8743
   658
reduce nested to mutual recursion provided the nested recursion only involves
nipkow@8743
   659
previously defined datatypes. This does not include functions:
nipkow@8743
   660
\begin{ttbox}
nipkow@8743
   661
datatype t = C (t => bool)
nipkow@8743
   662
\end{ttbox}
nipkow@8743
   663
is a real can of worms: in HOL it must be ruled out because it requires a type
nipkow@8743
   664
\isa{t} such that \isa{t} and its power set \isa{t \isasymFun\ bool} have the
nipkow@8743
   665
same cardinality---an impossibility. For the same reason it is not possible
nipkow@8743
   666
to allow recursion involving the type \isa{set}, which is isomorphic to
nipkow@8743
   667
\isa{t \isasymFun\ bool}.
nipkow@8743
   668
nipkow@8743
   669
Fortunately, a limited form of recursion
nipkow@8743
   670
involving function spaces is permitted: the recursive type may occur on the
nipkow@8743
   671
right of a function arrow, but never on the left. Hence the above can of worms
nipkow@8743
   672
is ruled out but the following example of a potentially infinitely branching tree is
nipkow@8743
   673
accepted:
nipkow@8771
   674
\smallskip
nipkow@8743
   675
nipkow@8743
   676
\input{Datatype/document/Fundata.tex}
nipkow@8743
   677
\bigskip
nipkow@8743
   678
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If you need nested recursion on the left of a function arrow,
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there are alternatives to pure HOL: LCF~\cite{paulson87} is a logic where types like
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\begin{ttbox}
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datatype lam = C (lam -> lam)
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   683
\end{ttbox}
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   684
do indeed make sense (note the intentionally different arrow \isa{->}).
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   685
There is even a version of LCF on top of HOL, called
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   686
HOLCF~\cite{MuellerNvOS99}.
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\index{*primrec|)}
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   689
\index{*datatype|)}
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   690
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   691
\subsection{Case study: Tries}
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   692
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   693
Tries are a classic search tree data structure~\cite{Knuth3-75} for fast
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   694
indexing with strings. Figure~\ref{fig:trie} gives a graphical example of a
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   695
trie containing the words ``all'', ``an'', ``ape'', ``can'', ``car'' and
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``cat''.  When searching a string in a trie, the letters of the string are
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examined sequentially. Each letter determines which subtrie to search next.
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   698
In this case study we model tries as a datatype, define a lookup and an
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update function, and prove that they behave as expected.
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\begin{figure}[htbp]
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\begin{center}
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   703
\unitlength1mm
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\begin{picture}(60,30)
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\put( 5, 0){\makebox(0,0)[b]{l}}
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\put(25, 0){\makebox(0,0)[b]{e}}
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   707
\put(35, 0){\makebox(0,0)[b]{n}}
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\put(45, 0){\makebox(0,0)[b]{r}}
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   709
\put(55, 0){\makebox(0,0)[b]{t}}
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   710
%
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   711
\put( 5, 9){\line(0,-1){5}}
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   712
\put(25, 9){\line(0,-1){5}}
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   713
\put(44, 9){\line(-3,-2){9}}
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   714
\put(45, 9){\line(0,-1){5}}
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   715
\put(46, 9){\line(3,-2){9}}
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   716
%
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   717
\put( 5,10){\makebox(0,0)[b]{l}}
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   718
\put(15,10){\makebox(0,0)[b]{n}}
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   719
\put(25,10){\makebox(0,0)[b]{p}}
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   720
\put(45,10){\makebox(0,0)[b]{a}}
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   721
%
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   722
\put(14,19){\line(-3,-2){9}}
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   723
\put(15,19){\line(0,-1){5}}
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   724
\put(16,19){\line(3,-2){9}}
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   725
\put(45,19){\line(0,-1){5}}
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   726
%
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   727
\put(15,20){\makebox(0,0)[b]{a}}
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   728
\put(45,20){\makebox(0,0)[b]{c}}
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   729
%
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   730
\put(30,30){\line(-3,-2){13}}
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   731
\put(30,30){\line(3,-2){13}}
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   732
\end{picture}
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   733
\end{center}
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   734
\caption{A sample trie}
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   735
\label{fig:trie}
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   736
\end{figure}
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   737
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   738
Proper tries associate some value with each string. Since the
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   739
information is stored only in the final node associated with the string, many
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   740
nodes do not carry any value. This distinction is captured by the
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   741
following predefined datatype (from theory \isa{Option}, which is a parent
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   742
of \isa{Main}):
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   743
\smallskip
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   744
\input{Trie/document/Option2.tex}
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   745
\indexbold{*option}\indexbold{*None}\indexbold{*Some}%
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   746
\input{Trie/document/Trie.tex}
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   747
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   748
\begin{exercise}
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   749
  Write an improved version of \isa{update} that does not suffer from the
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   750
  space leak in the version above. Prove the main theorem for your improved
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   751
  \isa{update}.
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   752
\end{exercise}
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   753
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   754
\begin{exercise}
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   755
  Write a function to \emph{delete} entries from a trie. An easy solution is
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   756
  a clever modification of \isa{update} which allows both insertion and
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   757
  deletion with a single function.  Prove (a modified version of) the main
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   758
  theorem above. Optimize you function such that it shrinks tries after
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   759
  deletion, if possible.
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   760
\end{exercise}
nipkow@8743
   761
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   762
\section{Total recursive functions}
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   763
\label{sec:recdef}
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   764
\index{*recdef|(}
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   765
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   766
Although many total functions have a natural primitive recursive definition,
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   767
this is not always the case. Arbitrary total recursive functions can be
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   768
defined by means of \isacommand{recdef}: you can use full pattern-matching,
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   769
recursion need not involve datatypes, and termination is proved by showing
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   770
that the arguments of all recursive calls are smaller in a suitable (user
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   771
supplied) sense.
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   772
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   773
\subsection{Defining recursive functions}
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   774
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   775
\input{Recdef/document/examples.tex}
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   776
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   777
\subsection{Proving termination}
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   778
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   779
\input{Recdef/document/termination.tex}
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   780
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   781
\subsection{Simplification with recdef}
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   782
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   783
\input{Recdef/document/simplification.tex}
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   784
nipkow@8743
   785
\subsection{Induction}
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   786
\index{induction!recursion|(}
nipkow@8743
   787
\index{recursion induction|(}
nipkow@8743
   788
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   789
\input{Recdef/document/Induction.tex}
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   790
\label{sec:recdef-induction}
nipkow@8743
   791
nipkow@8743
   792
\index{induction!recursion|)}
nipkow@8743
   793
\index{recursion induction|)}
nipkow@9644
   794
nipkow@9689
   795
\subsection{Advanced forms of recursion}
nipkow@9689
   796
\label{sec:advanced-recdef}
nipkow@9644
   797
nipkow@9689
   798
\input{Recdef/document/Nested0.tex}
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   799
\input{Recdef/document/Nested1.tex}
nipkow@9689
   800
\input{Recdef/document/Nested2.tex}
nipkow@9644
   801
nipkow@8743
   802
\index{*recdef|)}
nipkow@9644
   803
nipkow@9644
   804
\section{Advanced induction techniques}
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   805
\label{sec:advanced-ind}
nipkow@9644
   806
\input{Misc/document/AdvancedInd.tex}
nipkow@9644
   807
wenzelm@9673
   808
%\input{Datatype/document/Nested2.tex}