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doc-src/Logics/Old_HOL.tex

author | paulson |

Tue, 10 Feb 2004 12:02:11 +0100 | |

changeset 14378 | 69c4d5997669 |

parent 9695 | ec7d7f877712 |

permissions | -rw-r--r-- |

generic of_nat and of_int functions, and generalization of iszero
and neg

%% $Id$ \chapter{Higher-Order Logic} \index{higher-order logic|(} \index{HOL system@{\sc hol} system} The theory~\thydx{HOL} implements higher-order logic. It is based on Gordon's~{\sc hol} system~\cite{mgordon-hol}, which itself is based on Church's original paper~\cite{church40}. Andrews's book~\cite{andrews86} is a full description of higher-order logic. Experience with the {\sc hol} system has demonstrated that higher-order logic is useful for hardware verification; beyond this, it is widely applicable in many areas of mathematics. It is weaker than ZF set theory but for most applications this does not matter. If you prefer {\ML} to Lisp, you will probably prefer HOL to~ZF. Previous releases of Isabelle included a different version of~HOL, with explicit type inference rules~\cite{paulson-COLOG}. This version no longer exists, but \thydx{ZF} supports a similar style of reasoning. HOL has a distinct feel, compared with ZF and CTT. It identifies object-level types with meta-level types, taking advantage of Isabelle's built-in type checker. It identifies object-level functions with meta-level functions, so it uses Isabelle's operations for abstraction and application. There is no `apply' operator: function applications are written as simply~$f(a)$ rather than $f{\tt`}a$. These identifications allow Isabelle to support HOL particularly nicely, but they also mean that HOL requires more sophistication from the user --- in particular, an understanding of Isabelle's type system. Beginners should work with {\tt show_types} set to {\tt true}. Gain experience by working in first-order logic before attempting to use higher-order logic. This chapter assumes familiarity with~FOL. \begin{figure} \begin{center} \begin{tabular}{rrr} \it name &\it meta-type & \it description \\ \cdx{Trueprop}& $bool\To prop$ & coercion to $prop$\\ \cdx{not} & $bool\To bool$ & negation ($\neg$) \\ \cdx{True} & $bool$ & tautology ($\top$) \\ \cdx{False} & $bool$ & absurdity ($\bot$) \\ \cdx{if} & $[bool,\alpha,\alpha]\To\alpha::term$ & conditional \\ \cdx{Inv} & $(\alpha\To\beta)\To(\beta\To\alpha)$ & function inversion\\ \cdx{Let} & $[\alpha,\alpha\To\beta]\To\beta$ & let binder \end{tabular} \end{center} \subcaption{Constants} \begin{center} \index{"@@{\tt\at} symbol} \index{*"! symbol}\index{*"? symbol} \index{*"?"! symbol}\index{*"E"X"! symbol} \begin{tabular}{llrrr} \it symbol &\it name &\it meta-type & \it description \\ \tt\at & \cdx{Eps} & $(\alpha\To bool)\To\alpha::term$ & Hilbert description ($\epsilon$) \\ {\tt!~} or \sdx{ALL} & \cdx{All} & $(\alpha::term\To bool)\To bool$ & universal quantifier ($\forall$) \\ {\tt?~} or \sdx{EX} & \cdx{Ex} & $(\alpha::term\To bool)\To bool$ & existential quantifier ($\exists$) \\ {\tt?!} or {\tt EX!} & \cdx{Ex1} & $(\alpha::term\To bool)\To bool$ & unique existence ($\exists!$) \end{tabular} \end{center} \subcaption{Binders} \begin{center} \index{*"= symbol} \index{&@{\tt\&} symbol} \index{*"| symbol} \index{*"-"-"> symbol} \begin{tabular}{rrrr} \it symbol & \it meta-type & \it priority & \it description \\ \sdx{o} & $[\beta\To\gamma,\alpha\To\beta]\To (\alpha\To\gamma)$ & Right 50 & composition ($\circ$) \\ \tt = & $[\alpha::term,\alpha]\To bool$ & Left 50 & equality ($=$) \\ \tt < & $[\alpha::ord,\alpha]\To bool$ & Left 50 & less than ($<$) \\ \tt <= & $[\alpha::ord,\alpha]\To bool$ & Left 50 & less than or equals ($\leq$)\\ \tt \& & $[bool,bool]\To bool$ & Right 35 & conjunction ($\conj$) \\ \tt | & $[bool,bool]\To bool$ & Right 30 & disjunction ($\disj$) \\ \tt --> & $[bool,bool]\To bool$ & Right 25 & implication ($\imp$) \end{tabular} \end{center} \subcaption{Infixes} \caption{Syntax of {\tt HOL}} \label{hol-constants} \end{figure} \begin{figure} \index{*let symbol} \index{*in symbol} \dquotes \[\begin{array}{rclcl} term & = & \hbox{expression of class~$term$} \\ & | & "\at~" id~id^* " . " formula \\ & | & \multicolumn{3}{l}{"let"~id~"="~term";"\dots";"~id~"="~term~"in"~term} \\[2ex] formula & = & \hbox{expression of type~$bool$} \\ & | & term " = " term \\ & | & term " \ttilde= " term \\ & | & term " < " term \\ & | & term " <= " term \\ & | & "\ttilde\ " formula \\ & | & formula " \& " formula \\ & | & formula " | " formula \\ & | & formula " --> " formula \\ & | & "!~~~" id~id^* " . " formula & | & "ALL~" id~id^* " . " formula \\ & | & "?~~~" id~id^* " . " formula & | & "EX~~" id~id^* " . " formula \\ & | & "?!~~" id~id^* " . " formula & | & "EX!~" id~id^* " . " formula \end{array} \] \caption{Full grammar for HOL} \label{hol-grammar} \end{figure} \section{Syntax} The type class of higher-order terms is called~\cldx{term}. Type variables range over this class by default. The equality symbol and quantifiers are polymorphic over class {\tt term}. Class \cldx{ord} consists of all ordered types; the relations $<$ and $\leq$ are polymorphic over this class, as are the functions \cdx{mono}, \cdx{min} and \cdx{max}. Three other type classes --- \cldx{plus}, \cldx{minus} and \cldx{times} --- permit overloading of the operators {\tt+}, {\tt-} and {\tt*}. In particular, {\tt-} is overloaded for set difference and subtraction. \index{*"+ symbol} \index{*"- symbol} \index{*"* symbol} Figure~\ref{hol-constants} lists the constants (including infixes and binders), while Fig.\ts\ref{hol-grammar} presents the grammar of higher-order logic. Note that $a$\verb|~=|$b$ is translated to $\neg(a=b)$. \begin{warn} HOL has no if-and-only-if connective; logical equivalence is expressed using equality. But equality has a high priority, as befitting a relation, while if-and-only-if typically has the lowest priority. Thus, $\neg\neg P=P$ abbreviates $\neg\neg (P=P)$ and not $(\neg\neg P)=P$. When using $=$ to mean logical equivalence, enclose both operands in parentheses. \end{warn} \subsection{Types}\label{HOL-types} The type of formulae, \tydx{bool}, belongs to class \cldx{term}; thus, formulae are terms. The built-in type~\tydx{fun}, which constructs function types, is overloaded with arity {\tt(term,term)term}. Thus, $\sigma\To\tau$ belongs to class~{\tt term} if $\sigma$ and~$\tau$ do, allowing quantification over functions. Types in HOL must be non-empty; otherwise the quantifier rules would be unsound. I have commented on this elsewhere~\cite[\S7]{paulson-COLOG}. \index{type definitions} Gordon's {\sc hol} system supports {\bf type definitions}. A type is defined by exhibiting an existing type~$\sigma$, a predicate~$P::\sigma\To bool$, and a theorem of the form $\exists x::\sigma.P(x)$. Thus~$P$ specifies a non-empty subset of~$\sigma$, and the new type denotes this subset. New function constants are generated to establish an isomorphism between the new type and the subset. If type~$\sigma$ involves type variables $\alpha@1$, \ldots, $\alpha@n$, then the type definition creates a type constructor $(\alpha@1,\ldots,\alpha@n)ty$ rather than a particular type. Melham~\cite{melham89} discusses type definitions at length, with examples. Isabelle does not support type definitions at present. Instead, they are mimicked by explicit definitions of isomorphism functions. The definitions should be supported by theorems of the form $\exists x::\sigma.P(x)$, but Isabelle cannot enforce this. \subsection{Binders} Hilbert's {\bf description} operator~$\epsilon x.P[x]$ stands for some~$a$ satisfying~$P[a]$, if such exists. Since all terms in HOL denote something, a description is always meaningful, but we do not know its value unless $P[x]$ defines it uniquely. We may write descriptions as \cdx{Eps}($P$) or use the syntax \hbox{\tt \at $x$.$P[x]$}. Existential quantification is defined by \[ \exists x.P(x) \;\equiv\; P(\epsilon x.P(x)). \] The unique existence quantifier, $\exists!x.P[x]$, is defined in terms of~$\exists$ and~$\forall$. An Isabelle binder, it admits nested quantifications. For instance, $\exists!x y.P(x,y)$ abbreviates $\exists!x. \exists!y.P(x,y)$; note that this does not mean that there exists a unique pair $(x,y)$ satisfying~$P(x,y)$. \index{*"! symbol}\index{*"? symbol}\index{HOL system@{\sc hol} system} Quantifiers have two notations. As in Gordon's {\sc hol} system, HOL uses~{\tt!}\ and~{\tt?}\ to stand for $\forall$ and $\exists$. The existential quantifier must be followed by a space; thus {\tt?x} is an unknown, while \verb'? x.f(x)=y' is a quantification. Isabelle's usual notation for quantifiers, \sdx{ALL} and \sdx{EX}, is also available. Both notations are accepted for input. The {\ML} reference \ttindexbold{HOL_quantifiers} governs the output notation. If set to {\tt true}, then~{\tt!}\ and~{\tt?}\ are displayed; this is the default. If set to {\tt false}, then~{\tt ALL} and~{\tt EX} are displayed. All these binders have priority 10. \subsection{The \sdx{let} and \sdx{case} constructions} Local abbreviations can be introduced by a {\tt let} construct whose syntax appears in Fig.\ts\ref{hol-grammar}. Internally it is translated into the constant~\cdx{Let}. It can be expanded by rewriting with its definition, \tdx{Let_def}. HOL also defines the basic syntax \[\dquotes"case"~e~"of"~c@1~"=>"~e@1~"|" \dots "|"~c@n~"=>"~e@n\] as a uniform means of expressing {\tt case} constructs. Therefore {\tt case} and \sdx{of} are reserved words. However, so far this is mere syntax and has no logical meaning. By declaring translations, you can cause instances of the {\tt case} construct to denote applications of particular case operators. The patterns supplied for $c@1$,~\ldots,~$c@n$ distinguish among the different case operators. For an example, see the case construct for lists on page~\pageref{hol-list} below. \begin{figure} \begin{ttbox}\makeatother \tdx{refl} t = (t::'a) \tdx{subst} [| s=t; P(s) |] ==> P(t::'a) \tdx{ext} (!!x::'a. (f(x)::'b) = g(x)) ==> (\%x.f(x)) = (\%x.g(x)) \tdx{impI} (P ==> Q) ==> P-->Q \tdx{mp} [| P-->Q; P |] ==> Q \tdx{iff} (P-->Q) --> (Q-->P) --> (P=Q) \tdx{selectI} P(x::'a) ==> P(@x.P(x)) \tdx{True_or_False} (P=True) | (P=False) \end{ttbox} \caption{The {\tt HOL} rules} \label{hol-rules} \end{figure} \begin{figure}\hfuzz=4pt%suppress "Overfull \hbox" message \begin{ttbox}\makeatother \tdx{True_def} True == ((\%x::bool.x)=(\%x.x)) \tdx{All_def} All == (\%P. P = (\%x.True)) \tdx{Ex_def} Ex == (\%P. P(@x.P(x))) \tdx{False_def} False == (!P.P) \tdx{not_def} not == (\%P. P-->False) \tdx{and_def} op & == (\%P Q. !R. (P-->Q-->R) --> R) \tdx{or_def} op | == (\%P Q. !R. (P-->R) --> (Q-->R) --> R) \tdx{Ex1_def} Ex1 == (\%P. ? x. P(x) & (! y. P(y) --> y=x)) \tdx{Inv_def} Inv == (\%(f::'a=>'b) y. @x. f(x)=y) \tdx{o_def} op o == (\%(f::'b=>'c) g (x::'a). f(g(x))) \tdx{if_def} if == (\%P x y.@z::'a.(P=True --> z=x) & (P=False --> z=y)) \tdx{Let_def} Let(s,f) == f(s) \end{ttbox} \caption{The {\tt HOL} definitions} \label{hol-defs} \end{figure} \section{Rules of inference} Figure~\ref{hol-rules} shows the inference rules of~HOL, with their~{\ML} names. Some of the rules deserve additional comments: \begin{ttdescription} \item[\tdx{ext}] expresses extensionality of functions. \item[\tdx{iff}] asserts that logically equivalent formulae are equal. \item[\tdx{selectI}] gives the defining property of the Hilbert $\epsilon$-operator. It is a form of the Axiom of Choice. The derived rule \tdx{select_equality} (see below) is often easier to use. \item[\tdx{True_or_False}] makes the logic classical.\footnote{In fact, the $\epsilon$-operator already makes the logic classical, as shown by Diaconescu; see Paulson~\cite{paulson-COLOG} for details.} \end{ttdescription} HOL follows standard practice in higher-order logic: only a few connectives are taken as primitive, with the remainder defined obscurely (Fig.\ts\ref{hol-defs}). Gordon's {\sc hol} system expresses the corresponding definitions \cite[page~270]{mgordon-hol} using object-equality~({\tt=}), which is possible because equality in higher-order logic may equate formulae and even functions over formulae. But theory~HOL, like all other Isabelle theories, uses meta-equality~({\tt==}) for definitions. Some of the rules mention type variables; for example, {\tt refl} mentions the type variable~{\tt'a}. This allows you to instantiate type variables explicitly by calling {\tt res_inst_tac}. By default, explicit type variables have class \cldx{term}. Include type constraints whenever you state a polymorphic goal. Type inference may otherwise make the goal more polymorphic than you intended, with confusing results. \begin{warn} If resolution fails for no obvious reason, try setting \ttindex{show_types} to {\tt true}, causing Isabelle to display types of terms. Possibly set \ttindex{show_sorts} to {\tt true} as well, causing Isabelle to display sorts. \index{unification!incompleteness of} Where function types are involved, Isabelle's unification code does not guarantee to find instantiations for type variables automatically. Be prepared to use \ttindex{res_inst_tac} instead of {\tt resolve_tac}, possibly instantiating type variables. Setting \ttindex{Unify.trace_types} to {\tt true} causes Isabelle to report omitted search paths during unification.\index{tracing!of unification} \end{warn} \begin{figure} \begin{ttbox} \tdx{sym} s=t ==> t=s \tdx{trans} [| r=s; s=t |] ==> r=t \tdx{ssubst} [| t=s; P(s) |] ==> P(t::'a) \tdx{box_equals} [| a=b; a=c; b=d |] ==> c=d \tdx{arg_cong} x=y ==> f(x)=f(y) \tdx{fun_cong} f=g ==> f(x)=g(x) \subcaption{Equality} \tdx{TrueI} True \tdx{FalseE} False ==> P \tdx{conjI} [| P; Q |] ==> P&Q \tdx{conjunct1} [| P&Q |] ==> P \tdx{conjunct2} [| P&Q |] ==> Q \tdx{conjE} [| P&Q; [| P; Q |] ==> R |] ==> R \tdx{disjI1} P ==> P|Q \tdx{disjI2} Q ==> P|Q \tdx{disjE} [| P | Q; P ==> R; Q ==> R |] ==> R \tdx{notI} (P ==> False) ==> ~ P \tdx{notE} [| ~ P; P |] ==> R \tdx{impE} [| P-->Q; P; Q ==> R |] ==> R \subcaption{Propositional logic} \tdx{iffI} [| P ==> Q; Q ==> P |] ==> P=Q \tdx{iffD1} [| P=Q; P |] ==> Q \tdx{iffD2} [| P=Q; Q |] ==> P \tdx{iffE} [| P=Q; [| P --> Q; Q --> P |] ==> R |] ==> R \tdx{eqTrueI} P ==> P=True \tdx{eqTrueE} P=True ==> P \subcaption{Logical equivalence} \end{ttbox} \caption{Derived rules for HOL} \label{hol-lemmas1} \end{figure} \begin{figure} \begin{ttbox}\makeatother \tdx{allI} (!!x::'a. P(x)) ==> !x. P(x) \tdx{spec} !x::'a.P(x) ==> P(x) \tdx{allE} [| !x.P(x); P(x) ==> R |] ==> R \tdx{all_dupE} [| !x.P(x); [| P(x); !x.P(x) |] ==> R |] ==> R \tdx{exI} P(x) ==> ? x::'a.P(x) \tdx{exE} [| ? x::'a.P(x); !!x. P(x) ==> Q |] ==> Q \tdx{ex1I} [| P(a); !!x. P(x) ==> x=a |] ==> ?! x. P(x) \tdx{ex1E} [| ?! x.P(x); !!x. [| P(x); ! y. P(y) --> y=x |] ==> R |] ==> R \tdx{select_equality} [| P(a); !!x. P(x) ==> x=a |] ==> (@x.P(x)) = a \subcaption{Quantifiers and descriptions} \tdx{ccontr} (~P ==> False) ==> P \tdx{classical} (~P ==> P) ==> P \tdx{excluded_middle} ~P | P \tdx{disjCI} (~Q ==> P) ==> P|Q \tdx{exCI} (! x. ~ P(x) ==> P(a)) ==> ? x.P(x) \tdx{impCE} [| P-->Q; ~ P ==> R; Q ==> R |] ==> R \tdx{iffCE} [| P=Q; [| P;Q |] ==> R; [| ~P; ~Q |] ==> R |] ==> R \tdx{notnotD} ~~P ==> P \tdx{swap} ~P ==> (~Q ==> P) ==> Q \subcaption{Classical logic} \tdx{if_True} if(True,x,y) = x \tdx{if_False} if(False,x,y) = y \tdx{if_P} P ==> if(P,x,y) = x \tdx{if_not_P} ~ P ==> if(P,x,y) = y \tdx{expand_if} P(if(Q,x,y)) = ((Q --> P(x)) & (~Q --> P(y))) \subcaption{Conditionals} \end{ttbox} \caption{More derived rules} \label{hol-lemmas2} \end{figure} Some derived rules are shown in Figures~\ref{hol-lemmas1} and~\ref{hol-lemmas2}, with their {\ML} names. These include natural rules for the logical connectives, as well as sequent-style elimination rules for conjunctions, implications, and universal quantifiers. Note the equality rules: \tdx{ssubst} performs substitution in backward proofs, while \tdx{box_equals} supports reasoning by simplifying both sides of an equation. \begin{figure} \begin{center} \begin{tabular}{rrr} \it name &\it meta-type & \it description \\ \index{{}@\verb'{}' symbol} \verb|{}| & $\alpha\,set$ & the empty set \\ \cdx{insert} & $[\alpha,\alpha\,set]\To \alpha\,set$ & insertion of element \\ \cdx{Collect} & $(\alpha\To bool)\To\alpha\,set$ & comprehension \\ \cdx{Compl} & $(\alpha\,set)\To\alpha\,set$ & complement \\ \cdx{INTER} & $[\alpha\,set,\alpha\To\beta\,set]\To\beta\,set$ & intersection over a set\\ \cdx{UNION} & $[\alpha\,set,\alpha\To\beta\,set]\To\beta\,set$ & union over a set\\ \cdx{Inter} & $(\alpha\,set)set\To\alpha\,set$ &set of sets intersection \\ \cdx{Union} & $(\alpha\,set)set\To\alpha\,set$ &set of sets union \\ \cdx{Pow} & $\alpha\,set \To (\alpha\,set)set$ & powerset \\[1ex] \cdx{range} & $(\alpha\To\beta )\To\beta\,set$ & range of a function \\[1ex] \cdx{Ball}~~\cdx{Bex} & $[\alpha\,set,\alpha\To bool]\To bool$ & bounded quantifiers \\ \cdx{mono} & $(\alpha\,set\To\beta\,set)\To bool$ & monotonicity \\ \cdx{inj}~~\cdx{surj}& $(\alpha\To\beta )\To bool$ & injective/surjective \\ \cdx{inj_onto} & $[\alpha\To\beta ,\alpha\,set]\To bool$ & injective over subset \end{tabular} \end{center} \subcaption{Constants} \begin{center} \begin{tabular}{llrrr} \it symbol &\it name &\it meta-type & \it priority & \it description \\ \sdx{INT} & \cdx{INTER1} & $(\alpha\To\beta\,set)\To\beta\,set$ & 10 & intersection over a type\\ \sdx{UN} & \cdx{UNION1} & $(\alpha\To\beta\,set)\To\beta\,set$ & 10 & union over a type \end{tabular} \end{center} \subcaption{Binders} \begin{center} \index{*"`"` symbol} \index{*": symbol} \index{*"<"= symbol} \begin{tabular}{rrrr} \it symbol & \it meta-type & \it priority & \it description \\ \tt `` & $[\alpha\To\beta ,\alpha\,set]\To (\beta\,set)$ & Left 90 & image \\ \sdx{Int} & $[\alpha\,set,\alpha\,set]\To\alpha\,set$ & Left 70 & intersection ($\inter$) \\ \sdx{Un} & $[\alpha\,set,\alpha\,set]\To\alpha\,set$ & Left 65 & union ($\union$) \\ \tt: & $[\alpha ,\alpha\,set]\To bool$ & Left 50 & membership ($\in$) \\ \tt <= & $[\alpha\,set,\alpha\,set]\To bool$ & Left 50 & subset ($\subseteq$) \end{tabular} \end{center} \subcaption{Infixes} \caption{Syntax of the theory {\tt Set}} \label{hol-set-syntax} \end{figure} \begin{figure} \begin{center} \tt\frenchspacing \index{*"! symbol} \begin{tabular}{rrr} \it external & \it internal & \it description \\ $a$ \ttilde: $b$ & \ttilde($a$ : $b$) & \rm non-membership\\ \{$a@1$, $\ldots$\} & insert($a@1$, $\ldots$\{\}) & \rm finite set \\ \{$x$.$P[x]$\} & Collect($\lambda x.P[x]$) & \rm comprehension \\ \sdx{INT} $x$:$A$.$B[x]$ & INTER($A$,$\lambda x.B[x]$) & \rm intersection \\ \sdx{UN}{\tt\ } $x$:$A$.$B[x]$ & UNION($A$,$\lambda x.B[x]$) & \rm union \\ \tt ! $x$:$A$.$P[x]$ or \sdx{ALL} $x$:$A$.$P[x]$ & Ball($A$,$\lambda x.P[x]$) & \rm bounded $\forall$ \\ \sdx{?} $x$:$A$.$P[x]$ or \sdx{EX}{\tt\ } $x$:$A$.$P[x]$ & Bex($A$,$\lambda x.P[x]$) & \rm bounded $\exists$ \end{tabular} \end{center} \subcaption{Translations} \dquotes \[\begin{array}{rclcl} term & = & \hbox{other terms\ldots} \\ & | & "\{\}" \\ & | & "\{ " term\; ("," term)^* " \}" \\ & | & "\{ " id " . " formula " \}" \\ & | & term " `` " term \\ & | & term " Int " term \\ & | & term " Un " term \\ & | & "INT~~" id ":" term " . " term \\ & | & "UN~~~" id ":" term " . " term \\ & | & "INT~~" id~id^* " . " term \\ & | & "UN~~~" id~id^* " . " term \\[2ex] formula & = & \hbox{other formulae\ldots} \\ & | & term " : " term \\ & | & term " \ttilde: " term \\ & | & term " <= " term \\ & | & "!~" id ":" term " . " formula & | & "ALL " id ":" term " . " formula \\ & | & "?~" id ":" term " . " formula & | & "EX~~" id ":" term " . " formula \end{array} \] \subcaption{Full Grammar} \caption{Syntax of the theory {\tt Set} (continued)} \label{hol-set-syntax2} \end{figure} \section{A formulation of set theory} Historically, higher-order logic gives a foundation for Russell and Whitehead's theory of classes. Let us use modern terminology and call them {\bf sets}, but note that these sets are distinct from those of ZF set theory, and behave more like ZF classes. \begin{itemize} \item Sets are given by predicates over some type~$\sigma$. Types serve to define universes for sets, but type checking is still significant. \item There is a universal set (for each type). Thus, sets have complements, and may be defined by absolute comprehension. \item Although sets may contain other sets as elements, the containing set must have a more complex type. \end{itemize} Finite unions and intersections have the same behaviour in HOL as they do in~ZF. In HOL the intersection of the empty set is well-defined, denoting the universal set for the given type. \subsection{Syntax of set theory}\index{*set type} HOL's set theory is called \thydx{Set}. The type $\alpha\,set$ is essentially the same as $\alpha\To bool$. The new type is defined for clarity and to avoid complications involving function types in unification. Since Isabelle does not support type definitions (as mentioned in \S\ref{HOL-types}), the isomorphisms between the two types are declared explicitly. Here they are natural: {\tt Collect} maps $\alpha\To bool$ to $\alpha\,set$, while \hbox{\tt op :} maps in the other direction (ignoring argument order). Figure~\ref{hol-set-syntax} lists the constants, infixes, and syntax translations. Figure~\ref{hol-set-syntax2} presents the grammar of the new constructs. Infix operators include union and intersection ($A\union B$ and $A\inter B$), the subset and membership relations, and the image operator~{\tt``}\@. Note that $a$\verb|~:|$b$ is translated to $\neg(a\in b)$. The {\tt\{\ldots\}} notation abbreviates finite sets constructed in the obvious manner using~{\tt insert} and~$\{\}$: \begin{eqnarray*} \{a@1, \ldots, a@n\} & \equiv & {\tt insert}(a@1,\ldots,{\tt insert}(a@n,\{\})) \end{eqnarray*} The set \hbox{\tt\{$x$.$P[x]$\}} consists of all $x$ (of suitable type) that satisfy~$P[x]$, where $P[x]$ is a formula that may contain free occurrences of~$x$. This syntax expands to \cdx{Collect}$(\lambda x.P[x])$. It defines sets by absolute comprehension, which is impossible in~ZF; the type of~$x$ implicitly restricts the comprehension. The set theory defines two {\bf bounded quantifiers}: \begin{eqnarray*} \forall x\in A.P[x] &\hbox{abbreviates}& \forall x. x\in A\imp P[x] \\ \exists x\in A.P[x] &\hbox{abbreviates}& \exists x. x\in A\conj P[x] \end{eqnarray*} The constants~\cdx{Ball} and~\cdx{Bex} are defined accordingly. Instead of {\tt Ball($A$,$P$)} and {\tt Bex($A$,$P$)} we may write\index{*"! symbol}\index{*"? symbol} \index{*ALL symbol}\index{*EX symbol} % \hbox{\tt !~$x$:$A$.$P[x]$} and \hbox{\tt ?~$x$:$A$.$P[x]$}. Isabelle's usual quantifier symbols, \sdx{ALL} and \sdx{EX}, are also accepted for input. As with the primitive quantifiers, the {\ML} reference \ttindex{HOL_quantifiers} specifies which notation to use for output. Unions and intersections over sets, namely $\bigcup@{x\in A}B[x]$ and $\bigcap@{x\in A}B[x]$, are written \sdx{UN}~\hbox{\tt$x$:$A$.$B[x]$} and \sdx{INT}~\hbox{\tt$x$:$A$.$B[x]$}. Unions and intersections over types, namely $\bigcup@x B[x]$ and $\bigcap@x B[x]$, are written \sdx{UN}~\hbox{\tt$x$.$B[x]$} and \sdx{INT}~\hbox{\tt$x$.$B[x]$}. They are equivalent to the previous union and intersection operators when $A$ is the universal set. The operators $\bigcup A$ and $\bigcap A$ act upon sets of sets. They are not binders, but are equal to $\bigcup@{x\in A}x$ and $\bigcap@{x\in A}x$, respectively. \begin{figure} \underscoreon \begin{ttbox} \tdx{mem_Collect_eq} (a : \{x.P(x)\}) = P(a) \tdx{Collect_mem_eq} \{x.x:A\} = A \tdx{empty_def} \{\} == \{x.False\} \tdx{insert_def} insert(a,B) == \{x.x=a\} Un B \tdx{Ball_def} Ball(A,P) == ! x. x:A --> P(x) \tdx{Bex_def} Bex(A,P) == ? x. x:A & P(x) \tdx{subset_def} A <= B == ! x:A. x:B \tdx{Un_def} A Un B == \{x.x:A | x:B\} \tdx{Int_def} A Int B == \{x.x:A & x:B\} \tdx{set_diff_def} A - B == \{x.x:A & x~:B\} \tdx{Compl_def} Compl(A) == \{x. ~ x:A\} \tdx{INTER_def} INTER(A,B) == \{y. ! x:A. y: B(x)\} \tdx{UNION_def} UNION(A,B) == \{y. ? x:A. y: B(x)\} \tdx{INTER1_def} INTER1(B) == INTER(\{x.True\}, B) \tdx{UNION1_def} UNION1(B) == UNION(\{x.True\}, B) \tdx{Inter_def} Inter(S) == (INT x:S. x) \tdx{Union_def} Union(S) == (UN x:S. x) \tdx{Pow_def} Pow(A) == \{B. B <= A\} \tdx{image_def} f``A == \{y. ? x:A. y=f(x)\} \tdx{range_def} range(f) == \{y. ? x. y=f(x)\} \tdx{mono_def} mono(f) == !A B. A <= B --> f(A) <= f(B) \tdx{inj_def} inj(f) == ! x y. f(x)=f(y) --> x=y \tdx{surj_def} surj(f) == ! y. ? x. y=f(x) \tdx{inj_onto_def} inj_onto(f,A) == !x:A. !y:A. f(x)=f(y) --> x=y \end{ttbox} \caption{Rules of the theory {\tt Set}} \label{hol-set-rules} \end{figure} \begin{figure} \underscoreon \begin{ttbox} \tdx{CollectI} [| P(a) |] ==> a : \{x.P(x)\} \tdx{CollectD} [| a : \{x.P(x)\} |] ==> P(a) \tdx{CollectE} [| a : \{x.P(x)\}; P(a) ==> W |] ==> W \tdx{ballI} [| !!x. x:A ==> P(x) |] ==> ! x:A. P(x) \tdx{bspec} [| ! x:A. P(x); x:A |] ==> P(x) \tdx{ballE} [| ! x:A. P(x); P(x) ==> Q; ~ x:A ==> Q |] ==> Q \tdx{bexI} [| P(x); x:A |] ==> ? x:A. P(x) \tdx{bexCI} [| ! x:A. ~ P(x) ==> P(a); a:A |] ==> ? x:A.P(x) \tdx{bexE} [| ? x:A. P(x); !!x. [| x:A; P(x) |] ==> Q |] ==> Q \subcaption{Comprehension and Bounded quantifiers} \tdx{subsetI} (!!x.x:A ==> x:B) ==> A <= B \tdx{subsetD} [| A <= B; c:A |] ==> c:B \tdx{subsetCE} [| A <= B; ~ (c:A) ==> P; c:B ==> P |] ==> P \tdx{subset_refl} A <= A \tdx{subset_trans} [| A<=B; B<=C |] ==> A<=C \tdx{equalityI} [| A <= B; B <= A |] ==> A = B \tdx{equalityD1} A = B ==> A<=B \tdx{equalityD2} A = B ==> B<=A \tdx{equalityE} [| A = B; [| A<=B; B<=A |] ==> P |] ==> P \tdx{equalityCE} [| A = B; [| c:A; c:B |] ==> P; [| ~ c:A; ~ c:B |] ==> P |] ==> P \subcaption{The subset and equality relations} \end{ttbox} \caption{Derived rules for set theory} \label{hol-set1} \end{figure} \begin{figure} \underscoreon \begin{ttbox} \tdx{emptyE} a : \{\} ==> P \tdx{insertI1} a : insert(a,B) \tdx{insertI2} a : B ==> a : insert(b,B) \tdx{insertE} [| a : insert(b,A); a=b ==> P; a:A ==> P |] ==> P \tdx{ComplI} [| c:A ==> False |] ==> c : Compl(A) \tdx{ComplD} [| c : Compl(A) |] ==> ~ c:A \tdx{UnI1} c:A ==> c : A Un B \tdx{UnI2} c:B ==> c : A Un B \tdx{UnCI} (~c:B ==> c:A) ==> c : A Un B \tdx{UnE} [| c : A Un B; c:A ==> P; c:B ==> P |] ==> P \tdx{IntI} [| c:A; c:B |] ==> c : A Int B \tdx{IntD1} c : A Int B ==> c:A \tdx{IntD2} c : A Int B ==> c:B \tdx{IntE} [| c : A Int B; [| c:A; c:B |] ==> P |] ==> P \tdx{UN_I} [| a:A; b: B(a) |] ==> b: (UN x:A. B(x)) \tdx{UN_E} [| b: (UN x:A. B(x)); !!x.[| x:A; b:B(x) |] ==> R |] ==> R \tdx{INT_I} (!!x. x:A ==> b: B(x)) ==> b : (INT x:A. B(x)) \tdx{INT_D} [| b: (INT x:A. B(x)); a:A |] ==> b: B(a) \tdx{INT_E} [| b: (INT x:A. B(x)); b: B(a) ==> R; ~ a:A ==> R |] ==> R \tdx{UnionI} [| X:C; A:X |] ==> A : Union(C) \tdx{UnionE} [| A : Union(C); !!X.[| A:X; X:C |] ==> R |] ==> R \tdx{InterI} [| !!X. X:C ==> A:X |] ==> A : Inter(C) \tdx{InterD} [| A : Inter(C); X:C |] ==> A:X \tdx{InterE} [| A : Inter(C); A:X ==> R; ~ X:C ==> R |] ==> R \tdx{PowI} A<=B ==> A: Pow(B) \tdx{PowD} A: Pow(B) ==> A<=B \end{ttbox} \caption{Further derived rules for set theory} \label{hol-set2} \end{figure} \subsection{Axioms and rules of set theory} Figure~\ref{hol-set-rules} presents the rules of theory \thydx{Set}. The axioms \tdx{mem_Collect_eq} and \tdx{Collect_mem_eq} assert that the functions {\tt Collect} and \hbox{\tt op :} are isomorphisms. Of course, \hbox{\tt op :} also serves as the membership relation. All the other axioms are definitions. They include the empty set, bounded quantifiers, unions, intersections, complements and the subset relation. They also include straightforward properties of functions: image~({\tt``}) and {\tt range}, and predicates concerning monotonicity, injectiveness and surjectiveness. The predicate \cdx{inj_onto} is used for simulating type definitions. The statement ${\tt inj_onto}(f,A)$ asserts that $f$ is injective on the set~$A$, which specifies a subset of its domain type. In a type definition, $f$ is the abstraction function and $A$ is the set of valid representations; we should not expect $f$ to be injective outside of~$A$. \begin{figure} \underscoreon \begin{ttbox} \tdx{Inv_f_f} inj(f) ==> Inv(f,f(x)) = x \tdx{f_Inv_f} y : range(f) ==> f(Inv(f,y)) = y %\tdx{Inv_injective} % [| Inv(f,x)=Inv(f,y); x: range(f); y: range(f) |] ==> x=y % \tdx{imageI} [| x:A |] ==> f(x) : f``A \tdx{imageE} [| b : f``A; !!x.[| b=f(x); x:A |] ==> P |] ==> P \tdx{rangeI} f(x) : range(f) \tdx{rangeE} [| b : range(f); !!x.[| b=f(x) |] ==> P |] ==> P \tdx{monoI} [| !!A B. A <= B ==> f(A) <= f(B) |] ==> mono(f) \tdx{monoD} [| mono(f); A <= B |] ==> f(A) <= f(B) \tdx{injI} [| !! x y. f(x) = f(y) ==> x=y |] ==> inj(f) \tdx{inj_inverseI} (!!x. g(f(x)) = x) ==> inj(f) \tdx{injD} [| inj(f); f(x) = f(y) |] ==> x=y \tdx{inj_ontoI} (!!x y. [| f(x)=f(y); x:A; y:A |] ==> x=y) ==> inj_onto(f,A) \tdx{inj_ontoD} [| inj_onto(f,A); f(x)=f(y); x:A; y:A |] ==> x=y \tdx{inj_onto_inverseI} (!!x. x:A ==> g(f(x)) = x) ==> inj_onto(f,A) \tdx{inj_onto_contraD} [| inj_onto(f,A); x~=y; x:A; y:A |] ==> ~ f(x)=f(y) \end{ttbox} \caption{Derived rules involving functions} \label{hol-fun} \end{figure} \begin{figure} \underscoreon \begin{ttbox} \tdx{Union_upper} B:A ==> B <= Union(A) \tdx{Union_least} [| !!X. X:A ==> X<=C |] ==> Union(A) <= C \tdx{Inter_lower} B:A ==> Inter(A) <= B \tdx{Inter_greatest} [| !!X. X:A ==> C<=X |] ==> C <= Inter(A) \tdx{Un_upper1} A <= A Un B \tdx{Un_upper2} B <= A Un B \tdx{Un_least} [| A<=C; B<=C |] ==> A Un B <= C \tdx{Int_lower1} A Int B <= A \tdx{Int_lower2} A Int B <= B \tdx{Int_greatest} [| C<=A; C<=B |] ==> C <= A Int B \end{ttbox} \caption{Derived rules involving subsets} \label{hol-subset} \end{figure} \begin{figure} \underscoreon \hfuzz=4pt%suppress "Overfull \hbox" message \begin{ttbox} \tdx{Int_absorb} A Int A = A \tdx{Int_commute} A Int B = B Int A \tdx{Int_assoc} (A Int B) Int C = A Int (B Int C) \tdx{Int_Un_distrib} (A Un B) Int C = (A Int C) Un (B Int C) \tdx{Un_absorb} A Un A = A \tdx{Un_commute} A Un B = B Un A \tdx{Un_assoc} (A Un B) Un C = A Un (B Un C) \tdx{Un_Int_distrib} (A Int B) Un C = (A Un C) Int (B Un C) \tdx{Compl_disjoint} A Int Compl(A) = \{x.False\} \tdx{Compl_partition} A Un Compl(A) = \{x.True\} \tdx{double_complement} Compl(Compl(A)) = A \tdx{Compl_Un} Compl(A Un B) = Compl(A) Int Compl(B) \tdx{Compl_Int} Compl(A Int B) = Compl(A) Un Compl(B) \tdx{Union_Un_distrib} Union(A Un B) = Union(A) Un Union(B) \tdx{Int_Union} A Int Union(B) = (UN C:B. A Int C) \tdx{Un_Union_image} (UN x:C. A(x) Un B(x)) = Union(A``C) Un Union(B``C) \tdx{Inter_Un_distrib} Inter(A Un B) = Inter(A) Int Inter(B) \tdx{Un_Inter} A Un Inter(B) = (INT C:B. A Un C) \tdx{Int_Inter_image} (INT x:C. A(x) Int B(x)) = Inter(A``C) Int Inter(B``C) \end{ttbox} \caption{Set equalities} \label{hol-equalities} \end{figure} Figures~\ref{hol-set1} and~\ref{hol-set2} present derived rules. Most are obvious and resemble rules of Isabelle's ZF set theory. Certain rules, such as \tdx{subsetCE}, \tdx{bexCI} and \tdx{UnCI}, are designed for classical reasoning; the rules \tdx{subsetD}, \tdx{bexI}, \tdx{Un1} and~\tdx{Un2} are not strictly necessary but yield more natural proofs. Similarly, \tdx{equalityCE} supports classical reasoning about extensionality, after the fashion of \tdx{iffCE}. See the file {\tt HOL/Set.ML} for proofs pertaining to set theory. Figure~\ref{hol-fun} presents derived inference rules involving functions. They also include rules for \cdx{Inv}, which is defined in theory~{\tt HOL}; note that ${\tt Inv}(f)$ applies the Axiom of Choice to yield an inverse of~$f$. They also include natural deduction rules for the image and range operators, and for the predicates {\tt inj} and {\tt inj_onto}. Reasoning about function composition (the operator~\sdx{o}) and the predicate~\cdx{surj} is done simply by expanding the definitions. See the file {\tt HOL/fun.ML} for a complete listing of the derived rules. Figure~\ref{hol-subset} presents lattice properties of the subset relation. Unions form least upper bounds; non-empty intersections form greatest lower bounds. Reasoning directly about subsets often yields clearer proofs than reasoning about the membership relation. See the file {\tt HOL/subset.ML}. Figure~\ref{hol-equalities} presents many common set equalities. They include commutative, associative and distributive laws involving unions, intersections and complements. The proofs are mostly trivial, using the classical reasoner; see file {\tt HOL/equalities.ML}. \begin{figure} \begin{constants} \it symbol & \it meta-type & & \it description \\ \cdx{Pair} & $[\alpha,\beta]\To \alpha\times\beta$ & & ordered pairs $\langle a,b\rangle$ \\ \cdx{fst} & $\alpha\times\beta \To \alpha$ & & first projection\\ \cdx{snd} & $\alpha\times\beta \To \beta$ & & second projection\\ \cdx{split} & $[[\alpha,\beta]\To\gamma, \alpha\times\beta] \To \gamma$ & & generalized projection\\ \cdx{Sigma} & $[\alpha\,set, \alpha\To\beta\,set]\To(\alpha\times\beta)set$ & & general sum of sets \end{constants} \begin{ttbox}\makeatletter \tdx{fst_def} fst(p) == @a. ? b. p = <a,b> \tdx{snd_def} snd(p) == @b. ? a. p = <a,b> \tdx{split_def} split(c,p) == c(fst(p),snd(p)) \tdx{Sigma_def} Sigma(A,B) == UN x:A. UN y:B(x). \{<x,y>\} \tdx{Pair_inject} [| <a, b> = <a',b'>; [| a=a'; b=b' |] ==> R |] ==> R \tdx{fst_conv} fst(<a,b>) = a \tdx{snd_conv} snd(<a,b>) = b \tdx{split} split(c, <a,b>) = c(a,b) \tdx{surjective_pairing} p = <fst(p),snd(p)> \tdx{SigmaI} [| a:A; b:B(a) |] ==> <a,b> : Sigma(A,B) \tdx{SigmaE} [| c: Sigma(A,B); !!x y.[| x:A; y:B(x); c=<x,y> |] ==> P |] ==> P \end{ttbox} \caption{Type $\alpha\times\beta$}\label{hol-prod} \end{figure} \begin{figure} \begin{constants} \it symbol & \it meta-type & & \it description \\ \cdx{Inl} & $\alpha \To \alpha+\beta$ & & first injection\\ \cdx{Inr} & $\beta \To \alpha+\beta$ & & second injection\\ \cdx{sum_case} & $[\alpha\To\gamma, \beta\To\gamma, \alpha+\beta] \To\gamma$ & & conditional \end{constants} \begin{ttbox}\makeatletter \tdx{sum_case_def} sum_case == (\%f g p. @z. (!x. p=Inl(x) --> z=f(x)) & (!y. p=Inr(y) --> z=g(y))) \tdx{Inl_not_Inr} ~ Inl(a)=Inr(b) \tdx{inj_Inl} inj(Inl) \tdx{inj_Inr} inj(Inr) \tdx{sumE} [| !!x::'a. P(Inl(x)); !!y::'b. P(Inr(y)) |] ==> P(s) \tdx{sum_case_Inl} sum_case(f, g, Inl(x)) = f(x) \tdx{sum_case_Inr} sum_case(f, g, Inr(x)) = g(x) \tdx{surjective_sum} sum_case(\%x::'a. f(Inl(x)), \%y::'b. f(Inr(y)), s) = f(s) \end{ttbox} \caption{Type $\alpha+\beta$}\label{hol-sum} \end{figure} \section{Generic packages and classical reasoning} HOL instantiates most of Isabelle's generic packages; see {\tt HOL/ROOT.ML} for details. \begin{itemize} \item Because it includes a general substitution rule, HOL instantiates the tactic {\tt hyp_subst_tac}, which substitutes for an equality throughout a subgoal and its hypotheses. \item It instantiates the simplifier, defining~\ttindexbold{HOL_ss} as the simplification set for higher-order logic. Equality~($=$), which also expresses logical equivalence, may be used for rewriting. See the file {\tt HOL/simpdata.ML} for a complete listing of the simplification rules. \item It instantiates the classical reasoner, as described below. \end{itemize} HOL derives classical introduction rules for $\disj$ and~$\exists$, as well as classical elimination rules for~$\imp$ and~$\bimp$, and the swap rule; recall Fig.\ts\ref{hol-lemmas2} above. The classical reasoner is set up as the structure {\tt Classical}. This structure is open, so {\ML} identifiers such as {\tt step_tac}, {\tt fast_tac}, {\tt best_tac}, etc., refer to it. HOL defines the following classical rule sets: \begin{ttbox} prop_cs : claset HOL_cs : claset set_cs : claset \end{ttbox} \begin{ttdescription} \item[\ttindexbold{prop_cs}] contains the propositional rules, namely those for~$\top$, $\bot$, $\conj$, $\disj$, $\neg$, $\imp$ and~$\bimp$, along with the rule~{\tt refl}. \item[\ttindexbold{HOL_cs}] extends {\tt prop_cs} with the safe rules {\tt allI} and~{\tt exE} and the unsafe rules {\tt allE} and~{\tt exI}, as well as rules for unique existence. Search using this classical set is incomplete: quantified formulae are used at most once. \item[\ttindexbold{set_cs}] extends {\tt HOL_cs} with rules for the bounded quantifiers, subsets, comprehensions, unions and intersections, complements, finite sets, images and ranges. \end{ttdescription} \noindent See \iflabelundefined{chap:classical}{the {\em Reference Manual\/}}% {Chap.\ts\ref{chap:classical}} for more discussion of classical proof methods. \section{Types} The basic higher-order logic is augmented with a tremendous amount of material, including support for recursive function and type definitions. A detailed discussion appears elsewhere~\cite{paulson-coind}. The simpler definitions are the same as those used the {\sc hol} system, but my treatment of recursive types differs from Melham's~\cite{melham89}. The present section describes product, sum, natural number and list types. \subsection{Product and sum types}\index{*"* type}\index{*"+ type} Theory \thydx{Prod} defines the product type $\alpha\times\beta$, with the ordered pair syntax {\tt<$a$,$b$>}. Theory \thydx{Sum} defines the sum type $\alpha+\beta$. These use fairly standard constructions; see Figs.\ts\ref{hol-prod} and~\ref{hol-sum}. Because Isabelle does not support abstract type definitions, the isomorphisms between these types and their representations are made explicitly. Most of the definitions are suppressed, but observe that the projections and conditionals are defined as descriptions. Their properties are easily proved using \tdx{select_equality}. \begin{figure} \index{*"< symbol} \index{*"* symbol} \index{*div symbol} \index{*mod symbol} \index{*"+ symbol} \index{*"- symbol} \begin{constants} \it symbol & \it meta-type & \it priority & \it description \\ \cdx{0} & $nat$ & & zero \\ \cdx{Suc} & $nat \To nat$ & & successor function\\ \cdx{nat_case} & $[\alpha, nat\To\alpha, nat] \To\alpha$ & & conditional\\ \cdx{nat_rec} & $[nat, \alpha, [nat, \alpha]\To\alpha] \To \alpha$ & & primitive recursor\\ \cdx{pred_nat} & $(nat\times nat) set$ & & predecessor relation\\ \tt * & $[nat,nat]\To nat$ & Left 70 & multiplication \\ \tt div & $[nat,nat]\To nat$ & Left 70 & division\\ \tt mod & $[nat,nat]\To nat$ & Left 70 & modulus\\ \tt + & $[nat,nat]\To nat$ & Left 65 & addition\\ \tt - & $[nat,nat]\To nat$ & Left 65 & subtraction \end{constants} \subcaption{Constants and infixes} \begin{ttbox}\makeatother \tdx{nat_case_def} nat_case == (\%a f n. @z. (n=0 --> z=a) & (!x. n=Suc(x) --> z=f(x))) \tdx{pred_nat_def} pred_nat == \{p. ? n. p = <n, Suc(n)>\} \tdx{less_def} m<n == <m,n>:pred_nat^+ \tdx{nat_rec_def} nat_rec(n,c,d) == wfrec(pred_nat, n, nat_case(\%g.c, \%m g. d(m,g(m)))) \tdx{add_def} m+n == nat_rec(m, n, \%u v.Suc(v)) \tdx{diff_def} m-n == nat_rec(n, m, \%u v. nat_rec(v, 0, \%x y.x)) \tdx{mult_def} m*n == nat_rec(m, 0, \%u v. n + v) \tdx{mod_def} m mod n == wfrec(trancl(pred_nat), m, \%j f. if(j<n,j,f(j-n))) \tdx{quo_def} m div n == wfrec(trancl(pred_nat), m, \%j f. if(j<n,0,Suc(f(j-n)))) \subcaption{Definitions} \end{ttbox} \caption{Defining {\tt nat}, the type of natural numbers} \label{hol-nat1} \end{figure} \begin{figure} \underscoreon \begin{ttbox} \tdx{nat_induct} [| P(0); !!k. [| P(k) |] ==> P(Suc(k)) |] ==> P(n) \tdx{Suc_not_Zero} Suc(m) ~= 0 \tdx{inj_Suc} inj(Suc) \tdx{n_not_Suc_n} n~=Suc(n) \subcaption{Basic properties} \tdx{pred_natI} <n, Suc(n)> : pred_nat \tdx{pred_natE} [| p : pred_nat; !!x n. [| p = <n, Suc(n)> |] ==> R |] ==> R \tdx{nat_case_0} nat_case(a, f, 0) = a \tdx{nat_case_Suc} nat_case(a, f, Suc(k)) = f(k) \tdx{wf_pred_nat} wf(pred_nat) \tdx{nat_rec_0} nat_rec(0,c,h) = c \tdx{nat_rec_Suc} nat_rec(Suc(n), c, h) = h(n, nat_rec(n,c,h)) \subcaption{Case analysis and primitive recursion} \tdx{less_trans} [| i<j; j<k |] ==> i<k \tdx{lessI} n < Suc(n) \tdx{zero_less_Suc} 0 < Suc(n) \tdx{less_not_sym} n<m --> ~ m<n \tdx{less_not_refl} ~ n<n \tdx{not_less0} ~ n<0 \tdx{Suc_less_eq} (Suc(m) < Suc(n)) = (m<n) \tdx{less_induct} [| !!n. [| ! m. m<n --> P(m) |] ==> P(n) |] ==> P(n) \tdx{less_linear} m<n | m=n | n<m \subcaption{The less-than relation} \end{ttbox} \caption{Derived rules for {\tt nat}} \label{hol-nat2} \end{figure} \subsection{The type of natural numbers, {\tt nat}} The theory \thydx{Nat} defines the natural numbers in a roundabout but traditional way. The axiom of infinity postulates an type~\tydx{ind} of individuals, which is non-empty and closed under an injective operation. The natural numbers are inductively generated by choosing an arbitrary individual for~0 and using the injective operation to take successors. As usual, the isomorphisms between~\tydx{nat} and its representation are made explicitly. The definition makes use of a least fixed point operator \cdx{lfp}, defined using the Knaster-Tarski theorem. This is used to define the operator \cdx{trancl}, for taking the transitive closure of a relation. Primitive recursion makes use of \cdx{wfrec}, an operator for recursion along arbitrary well-founded relations. The corresponding theories are called {\tt Lfp}, {\tt Trancl} and {\tt WF}\@. Elsewhere I have described similar constructions in the context of set theory~\cite{paulson-set-II}. Type~\tydx{nat} is postulated to belong to class~\cldx{ord}, which overloads $<$ and $\leq$ on the natural numbers. As of this writing, Isabelle provides no means of verifying that such overloading is sensible; there is no means of specifying the operators' properties and verifying that instances of the operators satisfy those properties. To be safe, the HOL theory includes no polymorphic axioms asserting general properties of $<$ and~$\leq$. Theory \thydx{Arith} develops arithmetic on the natural numbers. It defines addition, multiplication, subtraction, division, and remainder. Many of their properties are proved: commutative, associative and distributive laws, identity and cancellation laws, etc. The most interesting result is perhaps the theorem $a \bmod b + (a/b)\times b = a$. Division and remainder are defined by repeated subtraction, which requires well-founded rather than primitive recursion. See Figs.\ts\ref{hol-nat1} and~\ref{hol-nat2}. The predecessor relation, \cdx{pred_nat}, is shown to be well-founded. Recursion along this relation resembles primitive recursion, but is stronger because we are in higher-order logic; using primitive recursion to define a higher-order function, we can easily Ackermann's function, which is not primitive recursive \cite[page~104]{thompson91}. The transitive closure of \cdx{pred_nat} is~$<$. Many functions on the natural numbers are most easily expressed using recursion along~$<$. The tactic {\tt\ttindex{nat_ind_tac} "$n$" $i$} performs induction over the variable~$n$ in subgoal~$i$. \begin{figure} \index{#@{\tt\#} symbol} \index{"@@{\tt\at} symbol} \begin{constants} \it symbol & \it meta-type & \it priority & \it description \\ \cdx{Nil} & $\alpha list$ & & empty list\\ \tt \# & $[\alpha,\alpha list]\To \alpha list$ & Right 65 & list constructor \\ \cdx{null} & $\alpha list \To bool$ & & emptiness test\\ \cdx{hd} & $\alpha list \To \alpha$ & & head \\ \cdx{tl} & $\alpha list \To \alpha list$ & & tail \\ \cdx{ttl} & $\alpha list \To \alpha list$ & & total tail \\ \tt\at & $[\alpha list,\alpha list]\To \alpha list$ & Left 65 & append \\ \sdx{mem} & $[\alpha,\alpha list]\To bool$ & Left 55 & membership\\ \cdx{map} & $(\alpha\To\beta) \To (\alpha list \To \beta list)$ & & mapping functional\\ \cdx{filter} & $(\alpha \To bool) \To (\alpha list \To \alpha list)$ & & filter functional\\ \cdx{list_all}& $(\alpha \To bool) \To (\alpha list \To bool)$ & & forall functional\\ \cdx{list_rec} & $[\alpha list, \beta, [\alpha ,\alpha list, \beta]\To\beta] \To \beta$ & & list recursor \end{constants} \subcaption{Constants and infixes} \begin{center} \tt\frenchspacing \begin{tabular}{rrr} \it external & \it internal & \it description \\{} \sdx{[]} & Nil & \rm empty list \\{} [$x@1$, $\dots$, $x@n$] & $x@1$ \# $\cdots$ \# $x@n$ \# [] & \rm finite list \\{} [$x$:$l$. $P$] & filter($\lambda x{.}P$, $l$) & \rm list comprehension \end{tabular} \end{center} \subcaption{Translations} \begin{ttbox} \tdx{list_induct} [| P([]); !!x xs. [| P(xs) |] ==> P(x#xs)) |] ==> P(l) \tdx{Cons_not_Nil} (x # xs) ~= [] \tdx{Cons_Cons_eq} ((x # xs) = (y # ys)) = (x=y & xs=ys) \subcaption{Induction and freeness} \end{ttbox} \caption{The theory \thydx{List}} \label{hol-list} \end{figure} \begin{figure} \begin{ttbox}\makeatother \tdx{list_rec_Nil} list_rec([],c,h) = c \tdx{list_rec_Cons} list_rec(a#l, c, h) = h(a, l, list_rec(l,c,h)) \tdx{list_case_Nil} list_case(c, h, []) = c \tdx{list_case_Cons} list_case(c, h, x#xs) = h(x, xs) \tdx{map_Nil} map(f,[]) = [] \tdx{map_Cons} map(f, x \# xs) = f(x) \# map(f,xs) \tdx{null_Nil} null([]) = True \tdx{null_Cons} null(x#xs) = False \tdx{hd_Cons} hd(x#xs) = x \tdx{tl_Cons} tl(x#xs) = xs \tdx{ttl_Nil} ttl([]) = [] \tdx{ttl_Cons} ttl(x#xs) = xs \tdx{append_Nil} [] @ ys = ys \tdx{append_Cons} (x#xs) \at ys = x # xs \at ys \tdx{mem_Nil} x mem [] = False \tdx{mem_Cons} x mem (y#ys) = if(y=x, True, x mem ys) \tdx{filter_Nil} filter(P, []) = [] \tdx{filter_Cons} filter(P,x#xs) = if(P(x), x#filter(P,xs), filter(P,xs)) \tdx{list_all_Nil} list_all(P,[]) = True \tdx{list_all_Cons} list_all(P, x#xs) = (P(x) & list_all(P, xs)) \end{ttbox} \caption{Rewrite rules for lists} \label{hol-list-simps} \end{figure} \subsection{The type constructor for lists, {\tt list}} \index{*list type} HOL's definition of lists is an example of an experimental method for handling recursive data types. Figure~\ref{hol-list} presents the theory \thydx{List}: the basic list operations with their types and properties. The \sdx{case} construct is defined by the following translation: {\dquotes \begin{eqnarray*} \begin{array}{r@{\;}l@{}l} "case " e " of" & "[]" & " => " a\\ "|" & x"\#"xs & " => " b \end{array} & \equiv & "list_case"(a, \lambda x\;xs.b, e) \end{eqnarray*}}% The theory includes \cdx{list_rec}, a primitive recursion operator for lists. It is derived from well-founded recursion, a general principle that can express arbitrary total recursive functions. The simpset \ttindex{list_ss} contains, along with additional useful lemmas, the basic rewrite rules that appear in Fig.\ts\ref{hol-list-simps}. The tactic {\tt\ttindex{list_ind_tac} "$xs$" $i$} performs induction over the variable~$xs$ in subgoal~$i$. \section{Datatype declarations} \index{*datatype|(} \underscoreon It is often necessary to extend a theory with \ML-like datatypes. This extension consists of the new type, declarations of its constructors and rules that describe the new type. The theory definition section {\tt datatype} represents a compact way of doing this. \subsection{Foundations} A datatype declaration has the following general structure: \[ \mbox{\tt datatype}~ (\alpha_1,\dots,\alpha_n)t ~=~ C_1(\tau_{11},\dots,\tau_{1k_1}) ~\mid~ \dots ~\mid~ C_m(\tau_{m1},\dots,\tau_{mk_m}) \] where $\alpha_i$ are type variables, $C_i$ are distinct constructor names and $\tau_{ij}$ are one of the following: \begin{itemize} \item type variables $\alpha_1,\dots,\alpha_n$, \item types $(\beta_1,\dots,\beta_l)s$ where $s$ is a previously declared type or type synonym and $\{\beta_1,\dots,\beta_l\} \subseteq \{\alpha_1,\dots,\alpha_n\}$, \item the newly defined type $(\alpha_1,\dots,\alpha_n)t$ \footnote{This makes it a recursive type. To ensure that the new type is not empty at least one constructor must consist of only non-recursive type components.} \end{itemize} If you would like one of the $\tau_{ij}$ to be a complex type expression $\tau$ you need to declare a new type synonym $syn = \tau$ first and use $syn$ in place of $\tau$. Of course this does not work if $\tau$ mentions the recursive type itself, thus ruling out problematic cases like \[ \mbox{\tt datatype}~ t ~=~ C(t \To t) \] together with unproblematic ones like \[ \mbox{\tt datatype}~ t ~=~ C(t~list). \] The constructors are automatically defined as functions of their respective type: \[ C_j : [\tau_{j1},\dots,\tau_{jk_j}] \To (\alpha_1,\dots,\alpha_n)t \] These functions have certain {\em freeness} properties: \begin{description} \item[\tt distinct] They are distinct: \[ C_i(x_1,\dots,x_{k_i}) \neq C_j(y_1,\dots,y_{k_j}) \qquad \mbox{for all}~ i \neq j. \] \item[\tt inject] They are injective: \[ (C_j(x_1,\dots,x_{k_j}) = C_j(y_1,\dots,y_{k_j})) = (x_1 = y_1 \land \dots \land x_{k_j} = y_{k_j}) \] \end{description} Because the number of inequalities is quadratic in the number of constructors, a different method is used if their number exceeds a certain value, currently 4. In that case every constructor is mapped to a natural number \[ \begin{array}{lcl} \mbox{\it t\_ord}(C_1(x_1,\dots,x_{k_1})) & = & 0 \\ & \vdots & \\ \mbox{\it t\_ord}(C_m(x_1,\dots,x_{k_m})) & = & m-1 \end{array} \] and distinctness of constructors is expressed by: \[ \mbox{\it t\_ord}(x) \neq \mbox{\it t\_ord}(y) \Imp x \neq y. \] In addition a structural induction axiom {\tt induct} is provided: \[ \infer{P(x)} {\begin{array}{lcl} \Forall x_1\dots x_{k_1}. \List{P(x_{r_{11}}); \dots; P(x_{r_{1l_1}})} & \Imp & P(C_1(x_1,\dots,x_{k_1})) \\ & \vdots & \\ \Forall x_1\dots x_{k_m}. \List{P(x_{r_{m1}}); \dots; P(x_{r_{ml_m}})} & \Imp & P(C_m(x_1,\dots,x_{k_m})) \end{array}} \] where $\{r_{j1},\dots,r_{jl_j}\} = \{i \in \{1,\dots k_j\} ~\mid~ \tau_{ji} = (\alpha_1,\dots,\alpha_n)t \}$, i.e.\ the property $P$ can be assumed for all arguments of the recursive type. The type also comes with an \ML-like \sdx{case}-construct: \[ \begin{array}{rrcl} \mbox{\tt case}~e~\mbox{\tt of} & C_1(x_{11},\dots,x_{1k_1}) & \To & e_1 \\ \vdots \\ \mid & C_m(x_{m1},\dots,x_{mk_m}) & \To & e_m \end{array} \] In contrast to \ML, {\em all} constructors must be present, their order is fixed, and nested patterns are not supported. \subsection{Defining datatypes} A datatype is defined in a theory definition file using the keyword {\tt datatype}. The definition following {\tt datatype} must conform to the syntax of {\em typedecl} specified in Fig.~\ref{datatype-grammar} and must obey the rules in the previous section. As a result the theory is extended with the new type, the constructors, and the theorems listed in the previous section. \begin{figure} \begin{rail} typedecl : typevarlist id '=' (cons + '|') ; cons : (id | string) ( () | '(' (typ + ',') ')' ) ( () | mixfix ) ; typ : typevarlist id | tid ; typevarlist : () | tid | '(' (tid + ',') ')' ; \end{rail} \caption{Syntax of datatype declarations} \label{datatype-grammar} \end{figure} Reading the theory file produces a structure which, in addition to the usual components, contains a structure named $t$ for each datatype $t$ defined in the file.\footnote{Otherwise multiple datatypes in the same theory file would lead to name clashes.} Each structure $t$ contains the following elements: \begin{ttbox} val distinct : thm list val inject : thm list val induct : thm val cases : thm list val simps : thm list val induct_tac : string -> int -> tactic \end{ttbox} {\tt distinct}, {\tt inject} and {\tt induct} contain the theorems described above. For convenience {\tt distinct} contains inequalities in both directions. \begin{warn} If there are five or more constructors, the {\em t\_ord} scheme is used for {\tt distinct}. In this case the theory {\tt Arith} must be contained in the current theory, if necessary by including it explicitly. \end{warn} The reduction rules of the {\tt case}-construct are in {\tt cases}. All theorems from {\tt distinct}, {\tt inject} and {\tt cases} are combined in {\tt simps} for use with the simplifier. The tactic {\verb$induct_tac$~{\em var i}\/} applies structural induction over variable {\em var} to subgoal {\em i}. \subsection{Examples} \subsubsection{The datatype $\alpha~list$} We want to define the type $\alpha~list$.\footnote{Of course there is a list type in HOL already. This is only an example.} To do this we have to build a new theory that contains the type definition. We start from {\tt HOL}. \begin{ttbox} MyList = HOL + datatype 'a list = Nil | Cons ('a, 'a list) end \end{ttbox} After loading the theory (\verb$use_thy "MyList"$), we can prove $Cons(x,xs)\neq xs$. First we build a suitable simpset for the simplifier: \begin{ttbox} val mylist_ss = HOL_ss addsimps MyList.list.simps; goal MyList.thy "!x. Cons(x,xs) ~= xs"; {\out Level 0} {\out ! x. Cons(x, xs) ~= xs} {\out 1. ! x. Cons(x, xs) ~= xs} \end{ttbox} This can be proved by the structural induction tactic: \begin{ttbox} by (MyList.list.induct_tac "xs" 1); {\out Level 1} {\out ! x. Cons(x, xs) ~= xs} {\out 1. ! x. Cons(x, Nil) ~= Nil} {\out 2. !!a list.} {\out ! x. Cons(x, list) ~= list ==>} {\out ! x. Cons(x, Cons(a, list)) ~= Cons(a, list)} \end{ttbox} The first subgoal can be proved with the simplifier and the distinctness axioms which are part of \verb$mylist_ss$. \begin{ttbox} by (simp_tac mylist_ss 1); {\out Level 2} {\out ! x. Cons(x, xs) ~= xs} {\out 1. !!a list.} {\out ! x. Cons(x, list) ~= list ==>} {\out ! x. Cons(x, Cons(a, list)) ~= Cons(a, list)} \end{ttbox} Using the freeness axioms we can quickly prove the remaining goal. \begin{ttbox} by (asm_simp_tac mylist_ss 1); {\out Level 3} {\out ! x. Cons(x, xs) ~= xs} {\out No subgoals!} \end{ttbox} Because both subgoals were proved by almost the same tactic we could have done that in one step using \begin{ttbox} by (ALLGOALS (asm_simp_tac mylist_ss)); \end{ttbox} \subsubsection{The datatype $\alpha~list$ with mixfix syntax} In this example we define the type $\alpha~list$ again but this time we want to write {\tt []} instead of {\tt Nil} and we want to use the infix operator \verb|#| instead of {\tt Cons}. To do this we simply add mixfix annotations after the constructor declarations as follows: \begin{ttbox} MyList = HOL + datatype 'a list = "[]" ("[]") | "#" ('a, 'a list) (infixr 70) end \end{ttbox} Now the theorem in the previous example can be written \verb|x#xs ~= xs|. The proof is the same. \subsubsection{A datatype for weekdays} This example shows a datatype that consists of more than four constructors: \begin{ttbox} Days = Arith + datatype days = Mo | Tu | We | Th | Fr | Sa | So end \end{ttbox} Because there are more than four constructors, the theory must be based on {\tt Arith}. Inequality is defined via a function \verb|days_ord|. Although the expression \verb|Mo ~= Tu| is not directly contained in {\tt distinct}, it can be proved by the simplifier if \verb$arith_ss$ is used: \begin{ttbox} val days_ss = arith_ss addsimps Days.days.simps; goal Days.thy "Mo ~= Tu"; by (simp_tac days_ss 1); \end{ttbox} Note that usually it is not necessary to derive these inequalities explicitly because the simplifier will dispose of them automatically. \subsection{Primitive recursive functions} \index{primitive recursion|(} \index{*primrec|(} Datatypes come with a uniform way of defining functions, {\bf primitive recursion}. Although it is possible to define primitive recursive functions by asserting their reduction rules as new axioms, e.g.\ \begin{ttbox} Append = MyList + consts app :: "['a list,'a list] => 'a list" rules app_Nil "app([],ys) = ys" app_Cons "app(x#xs, ys) = x#app(xs,ys)" end \end{ttbox} this carries with it the danger of accidentally asserting an inconsistency, as in \verb$app([],ys) = us$. Therefore primitive recursive functions on datatypes can be defined with a special syntax: \begin{ttbox} Append = MyList + consts app :: "['a list,'a list] => 'a list" primrec app MyList.list app_Nil "app([],ys) = ys" app_Cons "app(x#xs, ys) = x#app(xs,ys)" end \end{ttbox} The system will now check that the two rules \verb$app_Nil$ and \verb$app_Cons$ do indeed form a primitive recursive definition, thus ensuring that consistency is maintained. For example \begin{ttbox} primrec app MyList.list app_Nil "app([],ys) = us" \end{ttbox} is rejected: \begin{ttbox} Extra variables on rhs \end{ttbox} \bigskip The general form of a primitive recursive definition is \begin{ttbox} primrec {\it function} {\it type} {\it reduction rules} \end{ttbox} where \begin{itemize} \item {\it function} is the name of the function, either as an {\it id} or a {\it string}. The function must already have been declared. \item {\it type} is the name of the datatype, either as an {\it id} or in the long form {\it Thy.t}, where {\it Thy} is the name of the parent theory the datatype was declared in, and $t$ the name of the datatype. The long form is required if the {\tt datatype} and the {\tt primrec} sections are in different theories. \item {\it reduction rules} specify one or more named equations of the form {\it id\/}~{\it string}, where the identifier gives the name of the rule in the result structure, and {\it string} is a reduction rule of the form \[ f(x_1,\dots,x_m,C(y_1,\dots,y_k),z_1,\dots,z_n) = r \] such that $C$ is a constructor of the datatype, $r$ contains only the free variables on the left-hand side, and all recursive calls in $r$ are of the form $f(\dots,y_i,\dots)$ for some $i$. There must be exactly one reduction rule for each constructor. \end{itemize} A theory file may contain any number of {\tt primrec} sections which may be intermixed with other declarations. For the consistency-sensitive user it may be reassuring to know that {\tt primrec} does not assert the reduction rules as new axioms but derives them as theorems from an explicit definition of the recursive function in terms of a recursion operator on the datatype. The primitive recursive function can also use infix or mixfix syntax: \begin{ttbox} Append = MyList + consts "@" :: "['a list,'a list] => 'a list" (infixr 60) primrec "op @" MyList.list app_Nil "[] @ ys = ys" app_Cons "(x#xs) @ ys = x#(xs @ ys)" end \end{ttbox} The reduction rules become part of the ML structure \verb$Append$ and can be used to prove theorems about the function: \begin{ttbox} val append_ss = HOL_ss addsimps [Append.app_Nil,Append.app_Cons]; goal Append.thy "(xs @ ys) @ zs = xs @ (ys @ zs)"; by (MyList.list.induct_tac "xs" 1); by (ALLGOALS(asm_simp_tac append_ss)); \end{ttbox} %Note that underdefined primitive recursive functions are allowed: %\begin{ttbox} %Tl = MyList + %consts tl :: "'a list => 'a list" %primrec tl MyList.list % tl_Cons "tl(x#xs) = xs" %end %\end{ttbox} %Nevertheless {\tt tl} is total, although we do not know what the result of %\verb$tl([])$ is. \index{primitive recursion|)} \index{*primrec|)} \index{*datatype|)} \section{Inductive and coinductive definitions} \index{*inductive|(} \index{*coinductive|(} An {\bf inductive definition} specifies the least set closed under given rules. For example, a structural operational semantics is an inductive definition of an evaluation relation. Dually, a {\bf coinductive definition} specifies the greatest set consistent with given rules. An important example is using bisimulation relations to formalize equivalence of processes and infinite data structures. A theory file may contain any number of inductive and coinductive definitions. They may be intermixed with other declarations; in particular, the (co)inductive sets {\bf must} be declared separately as constants, and may have mixfix syntax or be subject to syntax translations. Each (co)inductive definition adds definitions to the theory and also proves some theorems. Each definition creates an ML structure, which is a substructure of the main theory structure. This package is derived from the ZF one, described in a separate paper,\footnote{It appeared in CADE~\cite{paulson-CADE} and a longer version is distributed with Isabelle.} which you should refer to in case of difficulties. The package is simpler than ZF's, thanks to HOL's automatic type-checking. The type of the (co)inductive determines the domain of the fixedpoint definition, and the package does not use inference rules for type-checking. \subsection{The result structure} Many of the result structure's components have been discussed in the paper; others are self-explanatory. \begin{description} \item[\tt thy] is the new theory containing the recursive sets. \item[\tt defs] is the list of definitions of the recursive sets. \item[\tt mono] is a monotonicity theorem for the fixedpoint operator. \item[\tt unfold] is a fixedpoint equation for the recursive set (the union of the recursive sets, in the case of mutual recursion). \item[\tt intrs] is the list of introduction rules, now proved as theorems, for the recursive sets. The rules are also available individually, using the names given them in the theory file. \item[\tt elim] is the elimination rule. \item[\tt mk\_cases] is a function to create simplified instances of {\tt elim}, using freeness reasoning on some underlying datatype. \end{description} For an inductive definition, the result structure contains two induction rules, {\tt induct} and \verb|mutual_induct|. For a coinductive definition, it contains the rule \verb|coinduct|. Figure~\ref{def-result-fig} summarizes the two result signatures, specifying the types of all these components. \begin{figure} \begin{ttbox} sig val thy : theory val defs : thm list val mono : thm val unfold : thm val intrs : thm list val elim : thm val mk_cases : thm list -> string -> thm {\it(Inductive definitions only)} val induct : thm val mutual_induct: thm {\it(Coinductive definitions only)} val coinduct : thm end \end{ttbox} \hrule \caption{The result of a (co)inductive definition} \label{def-result-fig} \end{figure} \subsection{The syntax of a (co)inductive definition} An inductive definition has the form \begin{ttbox} inductive {\it inductive sets} intrs {\it introduction rules} monos {\it monotonicity theorems} con_defs {\it constructor definitions} \end{ttbox} A coinductive definition is identical, except that it starts with the keyword {\tt coinductive}. The {\tt monos} and {\tt con\_defs} sections are optional. If present, each is specified as a string, which must be a valid ML expression of type {\tt thm list}. It is simply inserted into the {\tt .thy.ML} file; if it is ill-formed, it will trigger ML error messages. You can then inspect the file on your directory. \begin{itemize} \item The {\it inductive sets} are specified by one or more strings. \item The {\it introduction rules} specify one or more introduction rules in the form {\it ident\/}~{\it string}, where the identifier gives the name of the rule in the result structure. \item The {\it monotonicity theorems} are required for each operator applied to a recursive set in the introduction rules. There {\bf must} be a theorem of the form $A\subseteq B\Imp M(A)\subseteq M(B)$, for each premise $t\in M(R_i)$ in an introduction rule! \item The {\it constructor definitions} contain definitions of constants appearing in the introduction rules. In most cases it can be omitted. \end{itemize} The package has a few notable restrictions: \begin{itemize} \item The theory must separately declare the recursive sets as constants. \item The names of the recursive sets must be identifiers, not infix operators. \item Side-conditions must not be conjunctions. However, an introduction rule may contain any number of side-conditions. \item Side-conditions of the form $x=t$, where the variable~$x$ does not occur in~$t$, will be substituted through the rule \verb|mutual_induct|. \end{itemize} \subsection{Example of an inductive definition} Two declarations, included in a theory file, define the finite powerset operator. First we declare the constant~{\tt Fin}. Then we declare it inductively, with two introduction rules: \begin{ttbox} consts Fin :: "'a set => 'a set set" inductive "Fin(A)" intrs emptyI "{} : Fin(A)" insertI "[| a: A; b: Fin(A) |] ==> insert(a,b) : Fin(A)" \end{ttbox} The resulting theory structure contains a substructure, called~{\tt Fin}. It contains the {\tt Fin}$(A)$ introduction rules as the list {\tt Fin.intrs}, and also individually as {\tt Fin.emptyI} and {\tt Fin.consI}. The induction rule is {\tt Fin.induct}. For another example, here is a theory file defining the accessible part of a relation. The main thing to note is the use of~{\tt Pow} in the sole introduction rule, and the corresponding mention of the rule \verb|Pow_mono| in the {\tt monos} list. The paper discusses a ZF version of this example in more detail. \begin{ttbox} Acc = WF + consts pred :: "['b, ('a * 'b)set] => 'a set" (*Set of predecessors*) acc :: "('a * 'a)set => 'a set" (*Accessible part*) defs pred_def "pred(x,r) == {y. <y,x>:r}" inductive "acc(r)" intrs pred "pred(a,r): Pow(acc(r)) ==> a: acc(r)" monos "[Pow_mono]" end \end{ttbox} The HOL distribution contains many other inductive definitions, such as the theory {\tt HOL/ex/PropLog.thy} and the directory {\tt HOL/IMP}. The theory {\tt HOL/ex/LList.thy} contains coinductive definitions. \index{*coinductive|)} \index{*inductive|)} \underscoreoff \section{The examples directories} Directory {\tt HOL/Subst} contains Martin Coen's mechanisation of a theory of substitutions and unifiers. It is based on Paulson's previous mechanisation in {\LCF}~\cite{paulson85} of Manna and Waldinger's theory~\cite{mw81}. Directory {\tt HOL/IMP} contains a mechanised version of a semantic equivalence proof taken from Winskel~\cite{winskel93}. It formalises the denotational and operational semantics of a simple while-language, then proves the two equivalent. It contains several datatype and inductive definitions, and demonstrates their use. Directory {\tt HOL/ex} contains other examples and experimental proofs in HOL. Here is an overview of the more interesting files. \begin{itemize} \item File {\tt cla.ML} demonstrates the classical reasoner on over sixty predicate calculus theorems, ranging from simple tautologies to moderately difficult problems involving equality and quantifiers. \item File {\tt meson.ML} contains an experimental implementation of the {\sc meson} proof procedure, inspired by Plaisted~\cite{plaisted90}. It is much more powerful than Isabelle's classical reasoner. But it is less useful in practice because it works only for pure logic; it does not accept derived rules for the set theory primitives, for example. \item File {\tt mesontest.ML} contains test data for the {\sc meson} proof procedure. These are mostly taken from Pelletier \cite{pelletier86}. \item File {\tt set.ML} proves Cantor's Theorem, which is presented in \S\ref{sec:hol-cantor} below, and the Schr\"oder-Bernstein Theorem. \item Theories {\tt InSort} and {\tt Qsort} prove correctness properties of insertion sort and quick sort. \item The definition of lazy lists demonstrates methods for handling infinite data structures and coinduction in higher-order logic~\cite{paulson-coind}. Theory \thydx{LList} defines an operator for corecursion on lazy lists, which is used to define a few simple functions such as map and append. Corecursion cannot easily define operations such as filter, which can compute indefinitely before yielding the next element (if any!) of the lazy list. A coinduction principle is defined for proving equations on lazy lists. \item Theory {\tt PropLog} proves the soundness and completeness of classical propositional logic, given a truth table semantics. The only connective is $\imp$. A Hilbert-style axiom system is specified, and its set of theorems defined inductively. A similar proof in ZF is described elsewhere~\cite{paulson-set-II}. \item Theory {\tt Term} develops an experimental recursive type definition; the recursion goes through the type constructor~\tydx{list}. \item Theory {\tt Simult} constructs mutually recursive sets of trees and forests, including induction and recursion rules. \item Theory {\tt MT} contains Jacob Frost's formalization~\cite{frost93} of Milner and Tofte's coinduction example~\cite{milner-coind}. This substantial proof concerns the soundness of a type system for a simple functional language. The semantics of recursion is given by a cyclic environment, which makes a coinductive argument appropriate. \end{itemize} \goodbreak \section{Example: Cantor's Theorem}\label{sec:hol-cantor} Cantor's Theorem states that every set has more subsets than it has elements. It has become a favourite example in higher-order logic since it is so easily expressed: \[ \forall f::[\alpha,\alpha]\To bool. \exists S::\alpha\To bool. \forall x::\alpha. f(x) \not= S \] % Viewing types as sets, $\alpha\To bool$ represents the powerset of~$\alpha$. This version states that for every function from $\alpha$ to its powerset, some subset is outside its range. The Isabelle proof uses HOL's set theory, with the type $\alpha\,set$ and the operator \cdx{range}. The set~$S$ is given as an unknown instead of a quantified variable so that we may inspect the subset found by the proof. \begin{ttbox} goal Set.thy "~ ?S : range(f :: 'a=>'a set)"; {\out Level 0} {\out ~ ?S : range(f)} {\out 1. ~ ?S : range(f)} \end{ttbox} The first two steps are routine. The rule \tdx{rangeE} replaces $\Var{S}\in {\tt range}(f)$ by $\Var{S}=f(x)$ for some~$x$. \begin{ttbox} by (resolve_tac [notI] 1); {\out Level 1} {\out ~ ?S : range(f)} {\out 1. ?S : range(f) ==> False} \ttbreak by (eresolve_tac [rangeE] 1); {\out Level 2} {\out ~ ?S : range(f)} {\out 1. !!x. ?S = f(x) ==> False} \end{ttbox} Next, we apply \tdx{equalityCE}, reasoning that since $\Var{S}=f(x)$, we have $\Var{c}\in \Var{S}$ if and only if $\Var{c}\in f(x)$ for any~$\Var{c}$. \begin{ttbox} by (eresolve_tac [equalityCE] 1); {\out Level 3} {\out ~ ?S : range(f)} {\out 1. !!x. [| ?c3(x) : ?S; ?c3(x) : f(x) |] ==> False} {\out 2. !!x. [| ~ ?c3(x) : ?S; ~ ?c3(x) : f(x) |] ==> False} \end{ttbox} Now we use a bit of creativity. Suppose that~$\Var{S}$ has the form of a comprehension. Then $\Var{c}\in\{x.\Var{P}(x)\}$ implies $\Var{P}(\Var{c})$. Destruct-resolution using \tdx{CollectD} instantiates~$\Var{S}$ and creates the new assumption. \begin{ttbox} by (dresolve_tac [CollectD] 1); {\out Level 4} {\out ~ \{x. ?P7(x)\} : range(f)} {\out 1. !!x. [| ?c3(x) : f(x); ?P7(?c3(x)) |] ==> False} {\out 2. !!x. [| ~ ?c3(x) : \{x. ?P7(x)\}; ~ ?c3(x) : f(x) |] ==> False} \end{ttbox} Forcing a contradiction between the two assumptions of subgoal~1 completes the instantiation of~$S$. It is now the set $\{x. x\not\in f(x)\}$, which is the standard diagonal construction. \begin{ttbox} by (contr_tac 1); {\out Level 5} {\out ~ \{x. ~ x : f(x)\} : range(f)} {\out 1. !!x. [| ~ x : \{x. ~ x : f(x)\}; ~ x : f(x) |] ==> False} \end{ttbox} The rest should be easy. To apply \tdx{CollectI} to the negated assumption, we employ \ttindex{swap_res_tac}: \begin{ttbox} by (swap_res_tac [CollectI] 1); {\out Level 6} {\out ~ \{x. ~ x : f(x)\} : range(f)} {\out 1. !!x. [| ~ x : f(x); ~ False |] ==> ~ x : f(x)} \ttbreak by (assume_tac 1); {\out Level 7} {\out ~ \{x. ~ x : f(x)\} : range(f)} {\out No subgoals!} \end{ttbox} How much creativity is required? As it happens, Isabelle can prove this theorem automatically. The classical set \ttindex{set_cs} contains rules for most of the constructs of HOL's set theory. We must augment it with \tdx{equalityCE} to break up set equalities, and then apply best-first search. Depth-first search would diverge, but best-first search successfully navigates through the large search space. \index{search!best-first} \begin{ttbox} choplev 0; {\out Level 0} {\out ~ ?S : range(f)} {\out 1. ~ ?S : range(f)} \ttbreak by (best_tac (set_cs addSEs [equalityCE]) 1); {\out Level 1} {\out ~ \{x. ~ x : f(x)\} : range(f)} {\out No subgoals!} \end{ttbox} \index{higher-order logic|)}