\chapter{How to program a proof tool}\label{tool}

Users of \HOL\ can create their own theorem proving tools by combining
predefined rules and tactics. The \ML\ type-discipline
ensures that only logically sound methods can be used to create values
of type \ml{thm}.
In this chapter, a simple but real\footnote{The example
is `real' in that the need for it came up last week.} example is described. 

Several implementations of the tool are given to illustrate various styles
of proof programming. The first implementation is the obvious one, but
is very slow because of the `brute force' method used. The second
implementation produces a much more streamlined proof, but still has a
brute force component, namely the use of a tautology checker from the
library \ml{taut}. The third implementation replaces the general
tautology checker with a special purpose derived inference rule. The
fourth and final implementation uses an optimised implementation of
the special purpose rule; understanding it is left as an exercise in
using \DESCRIPTION.

The timings in this chapter are based on Version 1.12. Later versions
of \HOL{} have an optimised tautology checker library due to Richard
Boulton. This new tautology checker is actually faster than the
special purpose derived rule described in
Section~\ref{bogus-optimization}.  Thus with the new tautology checker
the so called ``even more efficient implementation'' is actually
slower than the program it replaces! This was only discovered (by
Juanito Camilleri) during the preparation of Version 2 of the
tutorial. Rather than completely rewriting the chapter, it was decided
to leave it essentially as it was (except for the addition of this
 paragraph). The methods
that are described are still useful, and there is an important lesson
here: optimizations can become obsolete.  The really dedicated reader
could learn a lot by studying the old and new tautology checker
({\small\verb%contrib/icl-taut%} and
{\small\verb%Library/taut%}, respectively) to find out how they work.
Besides improving the tautology library, Richard Boulton also
reimplemented rewriting using ideas from Tom Melham and Roger Fleming.
As a result, in versions later than 1.12 the various rewriting tools
are quite a bit faster and generate fewer intermediate theorems.


It is sometimes claimed that `\LCF-style' systems can never be
practical, because the efficiency needed to handle real examples can
only be obtained with decision procedures coded as primitive rules. It
is hoped that this chapter, as well as the \ml{taut} library, shows
that the truth of such claims is not obvious. Research is currently in
progress to see if a variety of practical decision algorithms can be
implemented as efficient derived rules.

The tool described here is a tactic that puts conjunctions into the
normal form obtained by right associating, sorting the conjuncts into
a canonical order and then removing repetitions. This canonical order
uses the built-in polymorphic infix \ml{<<}, which orders any pair of
\ML\ values with the same type.

\section{A simple implementation}

A first implementation uses `brute-force' rewriting with
the equations:

\begin{hol}\begin{verbatim}
   |- (t1 /\ t2) /\ t3 = t1 /\ (t2 /\ t3)     % Associativity          %

   |- t1 /\ t2 = t2 /\ t1                     % Symmetry (if t2 << t1) %
   |- t1 /\ (t2 /\ t3) = t2 /\ (t1 /\ t3)     % Symmetry (if t2 << t1) %

   |- t /\ t = t                              % Cancel repeated terms  %
   |- t1 /\ (t1 /\ t2) = t1 /\ t2             % Cancel repeated terms  %
\end{verbatim}\end{hol}

\noindent These equations are easily proved using the 
library \ml{taut}. Note that \HOL\ Version 1.12 is used in
this chapter. Versions of \HOL\ later than 1.12 contain improved
rewriting tools and a new version of the library \ml{taut} (the old version
of the library is preserved in the directory
{\small\verb%contrib/icl-taut%}).


\setcounter{sessioncount}{1}
\begin{session}\begin{verbatim}
scaup% hol
          _  _    __    _      __    __
   |___   |__|   |  |   |     |__|  |__|
   |      |  |   |__|   |__   |__|  |__|
   
          Version 1.12 (Sun3/Franz), built on Feb 23 1991

#load_library `taut`;;
Loading library `taut` ...
........................
Library `taut` loaded.
() : void
\end{verbatim}\end{session}

\noindent The library \ml{taut} defines \ml{TAUT\_RULE}\footnote{The function \ml{TAUT\_RULE} has been replaced by a function called \ml{TAUT\_PROVE} 
in the new version of the \ml{taut} library available in versions of 
\HOL\ later than 1.12}
which converts a term to the corresponding theorem, if the term is a tautology.
\vfill
\newpage
\begin{session}\begin{verbatim}
#let ASSOC = TAUT_RULE "(t1 /\ t2) /\ t3 = t1 /\ t2 /\ t3";;
ASSOC = |- (t1 /\ t2) /\ t3 = t1 /\ t2 /\ t3

#let SYM1 = TAUT_RULE "t1 /\ t2 = t2 /\ t1";;
SYM1 = |- t1 /\ t2 = t2 /\ t1

#let SYM2 = TAUT_RULE "t1 /\ t2 /\ t3 = t2 /\ t1 /\ t3";;
SYM2 = |- t1 /\ t2 /\ t3 = t2 /\ t1 /\ t3

#let CANCEL1 = TAUT_RULE "t /\ t = t";;
CANCEL1 = |- t /\ t = t

#let CANCEL2 = TAUT_RULE "t1 /\ t1 /\ t2 = t1 /\ t2";;
CANCEL2 = |- t1 /\ t1 /\ t2 = t1 /\ t2
\end{verbatim}\end{session}

\noindent One cannot just use \ml{REWRITE\_TAC} with \ml{SYM1} and
\ml{SYM2}, because it would loop.  What is needed is a special
rewriting tool that will only apply symmetry when terms are out of
order. Such a tool can be implemented as a {\it conversion\/}.

Conversions are described in detail in \DESCRIPTION. The idea, which
is due to Larry Paulson \cite{lcp_rewrite}, is that a conversion is an
\ML\ function that maps a term $t_1$ to an equation:

\medskip
{\small\verb%|- %}$t_1${\small\verb% = %}$t_2$.  
\medskip

\noindent The intention is that a conversion will only apply to a
subset of terms: on members of this subset it will generate an
equation, on all other terms it will fail. Because conversions are so
central to theorem-proving in \HOL, the \ML\ type
{\small\verb%term->thm%} is abbreviated to {\small\verb%conv%}.
Conversions are applied using the function:

\begin{hol}\begin{verbatim}
   REWR_CONV : thm -> conv
\end{verbatim}\end{hol}

\noindent This takes an equation {\small\verb%|- %}$t_1${\small\verb% = %}$t_2$
and generates a conversion (\ie\ \ML\ function of type {\small\verb%term->thm%}) 
that maps any term $u$ that matches $t_1$ to the theorem
{\small\verb%|- %}$u${\small\verb% = %}$v$, where $v$ is 
obtained by applying the substitution obtained by matching $u$ with $t_1$ to $t_2$.
If $u$ doesn't match $t_1$ then the application of \ml{REWR\_CONV} fails.


\begin{session}\begin{verbatim}
#REWR_CONV ASSOC "(A /\ B) /\ C";;
|- (A /\ B) /\ C = A /\ B /\ C

#REWR_CONV ASSOC "A /\ (B /\ C)";;
evaluation failed     REWR_CONV: lhs of theorem doesn't match term

#REWR_CONV SYM1 "B /\ A";;
|- B /\ A = A /\ B

#REWR_CONV SYM1 "A \/ B";;
evaluation failed     REWR_CONV: lhs of theorem doesn't match term
\end{verbatim}\end{session}

\noindent For our application, the required conversion should map
a conjunction 

\medskip
$t_1${\small\verb% /\ (%}$t_{2_1}${\small\verb% /\ %}$t_{2_2}${\small\verb%)%} 
\medskip

\noindent in which 
$t_{2_1}${\small\verb% << %}$t_1$ to the equational theorem:

\medskip

{\small\verb%|- %}$t_1${\small\verb% /\ (%}$t_{2_1}${\small\verb% /\ %}$t_{2_2}${\small\verb%)  =  %} $t_{2_1}${\small\verb% /\ (%}$t_1${\small\verb% /\ %}$t_{2_2}${\small\verb%)%} 

\medskip

\noindent If $t_1${\small\verb% << %}$t_{2_1}$ then the conversion fails
(in the \ML\ sense) when applied to
$t_1${\small\verb% /\ (%}$t_{2_1}${\small\verb% /\ %}$t_{2_2}${\small\verb%)%}.
In addition, if the right conjunct is not itself a conjunction, then
the conversion should reorder if necessary. More precisely, if the conversion
is applied to $t_1${\small\verb% /\ %}$t_2$ where $t_2$ is not a conjunction and
$t_2${\small\verb% << %}$t_1$, then it should generate the equation:

\medskip
{\small\verb%|- %}$t_1${\small\verb% /\ %}$t_2${\small\verb%  =  %}$t_2${\small\verb% /\ %}$t_1$
\medskip

\noindent Such a conversion is easily implemented in \ML\ using
\ml{SYM1} and \ml{SYM2} proved above, together with the \ML\ syntax
processing functions \ml{is\_conj} and \ml{dest\_conj}, where:

\begin{hol}\begin{verbatim}
   is_conj   : term -> bool 
   dest_conj : term -> (term # term)
\end{verbatim}\end{hol}

\noindent These are functions that test whether a term is a conjunction, and
splits a term into its two conjuncts, respectively. For example:

\begin{session}\begin{verbatim}
#is_conj "A /\ B";;
true : bool

#is_conj "A \/ B";;
false : bool

#dest_conj "A /\ B";;
("A", "B") : (term # term)

#dest_conj "A \/ B";;
evaluation failed     dest_conj
\end{verbatim}\end{session}

The implementation of the special purpose conversion, 
\ml{CONJ\_ORD\_CONV}, is now straightforward.


\begin{session}\begin{verbatim}
#let CONJ_ORD_CONV t =
# let t1,t2 = dest_conj t
# in
# if is_conj t2
#   then (let t21,t22 = dest_conj t2
#         in
#         if t21 << t1 then REWR_CONV SYM2 t else fail)
#   else (if t2  << t1 then REWR_CONV SYM1 t else fail);;
CONJ_ORD_CONV = - : conv
\end{verbatim}\end{session}

\noindent This is illustrated by:

\begin{session}\begin{verbatim}
#"A:bool" << "B:bool";;
true : bool

#"B:bool" << "C:bool";;
true : bool

#CONJ_ORD_CONV "B /\ A";;
|- B /\ A = A /\ B

#CONJ_ORD_CONV "A /\ B";;
evaluation failed     fail
\end{verbatim}\end{session}

The process of normalizing a conjunction can be split into four phases:

\begin{enumerate}
\item Right associate the conjunction by repeatedly applying:
\begin{quote}
\ml{REWR\_CONV\ ASSOC}
\end{quote}
\item Put the conjuncts in canonical order by repeatedly applying:
\begin{quote}
\ml{CONJ\_ORD\_CONV}
\end{quote}
\item Remove repetitions of $t$ of the form $t${\small\verb% /\ %}$t$ 
by repeatedly applying:
\begin{quote}
\ml{REWR\_CONV\ CANCEL1}
\end{quote}
\item Remove repetitions of $t_1$ in
$t_1${\small\verb% /\ (%}$t_1${\small\verb% /\ %}$t_2${\small\verb%)%}
by repeatedly applying:
\begin{quote}
\ml{REWR\_CONV\ CANCEL2}
\end{quote}
\end{enumerate}


To implement this, a method of repeatedly applying a conversion to
subterms of a term is needed. This is provided by the operator

\begin{hol}\begin{verbatim}
   TOP_DEPTH_CONV : conv -> conv
\end{verbatim}\end{hol}

\noindent If $c$ is a conversion then \ml{TOP\_DEPTH\_CONV}~$c$ is a
conversion that repeatedly applies $c$ to all subterms until $c$ is no
longer applicable to any subterms. The function \ml{TOP\_DEPTH\_CONV}
is one of a family of operators that apply conversions throughout 
terms. Members of this family differ in the order in which subterms
are visited and the amount of repetition that is done. For more
details, see the chapter on conversions in \DESCRIPTION.

\begin{session}\begin{verbatim}
#let ex1 = "A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D";;
ex1 = "A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D" : term

#REWR_CONV ASSOC ex1;;
evaluation failed     REWR_CONV: lhs of theorem doesn't match term

#TOP_DEPTH_CONV (REWR_CONV ASSOC) ex1;;
|- A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D =
   A /\ B /\ C /\ A /\ C /\ A /\ D /\ D
\end{verbatim}\end{session}

\noindent The right hand side of this theorem is \ml{ex1} in right-associated
form. The conclusion of a theorem can be extracted with the \ML\ function
\ml{concl} and the right hand side of an equation can be extracted with
\ml{rhs}. Thus, continuing the session:

\begin{session}\begin{verbatim}
#let ex2 = rhs(concl it);;
ex2 = "A /\ B /\ C /\ A /\ C /\ A /\ D /\ D" : term

#TOP_DEPTH_CONV CONJ_ORD_CONV ex2;;
|- A /\ B /\ C /\ A /\ C /\ A /\ D /\ D =
   A /\ A /\ A /\ B /\ C /\ C /\ D /\ D
\end{verbatim}\end{session}

\noindent The right hand side of this is the result of canonicalizing
the order of the conjuncts in the left hand side. Next, the repetitions
can be eliminated using \ml{CANCEL1} and \ml{CANCEL2}.

\begin{session}\begin{verbatim}
#let ex3 = rhs(concl it);;
ex3 = "A /\ A /\ A /\ B /\ C /\ C /\ D /\ D" : term

#TOP_DEPTH_CONV (REWR_CONV CANCEL1) ex3;;
|- A /\ A /\ A /\ B /\ C /\ C /\ D /\ D =
   A /\ A /\ A /\ B /\ C /\ C /\ D
\end{verbatim}\end{session}

\begin{session}\begin{verbatim}
#let ex4 = rhs(concl it);;
ex4 = "A /\ A /\ A /\ B /\ C /\ C /\ D" : term

#TOP_DEPTH_CONV (REWR_CONV CANCEL2) ex4;;
|- A /\ A /\ A /\ B /\ C /\ C /\ D = A /\ B /\ C /\ D
\end{verbatim}\end{session}


To make the conjunction normalizer, the four stages just described
must be performed in sequence. Conversions can be applied in sequence using
the infixed function:

\begin{hol}\begin{verbatim}
   THENC : conv -> conv -> conv
\end{verbatim}\end{hol}


\noindent If $c_1\ t_1$ evaluates to $\ml{ |- }t_1\ml{=}t_2$ and
$c_2\ t_2$ evaluates to $\ml{ |- }t_2\ml{=}t_3$, then
$\ml{(}c_1\ \ml{THENC}\ c_2\ml{)}\ t_1$ evaluates to
$\ml{\ |-\ }t_1\ml{=}t_3$. If the
evaluation of $c_1\ t_1$ or the evaluation of $c_2\ t_2$ fails,
then so does the evaluation of $c_1\ \ml{THENC}\ c_2$. \ml{THENC} is
justified by the transitivity of equality.

Using \ml{THENC}, the normalizer is defined by

\begin{session}\begin{verbatim}
#let CONJ_NORM_CONV =
# TOP_DEPTH_CONV(REWR_CONV ASSOC)   THENC
# TOP_DEPTH_CONV CONJ_ORD_CONV         THENC
# TOP_DEPTH_CONV(REWR_CONV CANCEL1) THENC
# TOP_DEPTH_CONV(REWR_CONV CANCEL2);;

CONJ_NORM_CONV = - : conv

#CONJ_NORM_CONV ex1;;
|- A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D = A /\ B /\ C /\ D
\end{verbatim}\end{session}

This conversion can now be converted to a rule or tactic using the functions
\ml{CONV\_RULE} or \ml{CONV\_TAC}, respectively.


\begin{hol}
\begin{verbatim}
   CONV_RULE : conv -> thm -> thm
   CONV_TAC  : conv -> tactic
\end{verbatim}
\end{hol}

\noindent $\ml{CONV\_RULE}\ c\ \ml{(|- }t\ml{)}$ returns $\ml{|- }t'$, where
$c\ t$ evaluates to the equation
$\ml{|-}\ t\ml{=}t'$. 
$\ml{CONV\_TAC}\ c$ is a tactic that
converts the conclusion of a goal using $c$. For more details see \DESCRIPTION.

\begin{session}\begin{verbatim}
#let CONJ_NORM_TAC = CONV_TAC CONJ_NORM_CONV;;
CONJ_NORM_TAC = - : tactic
\end{verbatim}\end{session}

Here is an example. It uses {\it antiquotation\/}: if $x$ is an \ML\
indentifier bound to term, then occurrences of
{\small\verb%^%}$x$ inside a quotation
denotes the term bound to $x$.

\begin{session}\begin{verbatim}
#g "^ex1 ==> B";;
"A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D ==> B"

() : void

#e CONJ_NORM_TAC;;
OK..
"A /\ B /\ C /\ D ==> B"
\end{verbatim}\end{session}

To summarize, here is the \ML\ code implementing the normalizer:

\begin{hol}\begin{verbatim}
   load_library `taut`;;

   let ASSOC   = TAUT_RULE "(t1 /\ t2) /\ t3 = t1 /\ t2 /\ t3"
   and SYM1    = TAUT_RULE "t1 /\ t2 = t2 /\ t1"
   and SYM2    = TAUT_RULE "t1 /\ t2 /\ t3 = t2 /\ t1 /\ t3"
   and CANCEL1 = TAUT_RULE "t /\ t = t"
   and CANCEL2 = TAUT_RULE "t1 /\ t1 /\ t2 = t1 /\ t2";;

   let CONJ_ORD_CONV t =
    let t1,t2 = dest_conj t
    in
    if is_conj t2
      then (let t21,t22 = dest_conj t2
            in
            if t21 << t1 then REWR_CONV SYM2 t else fail)
      else (if t2  << t1 then REWR_CONV SYM1 t else fail);;

   let CONJ_NORM_CONV =
    TOP_DEPTH_CONV(REWR_CONV ASSOC)   THENC
    TOP_DEPTH_CONV CONJ_ORD_CONV         THENC
    TOP_DEPTH_CONV(REWR_CONV CANCEL1) THENC
    TOP_DEPTH_CONV(REWR_CONV CANCEL2);;

   let CONJ_NORM_TAC = CONV_TAC CONJ_NORM_CONV;;
\end{verbatim}\end{hol} 

\section{A more efficient implementation}

The normalizer just given is rather slow. This can be shown by switching on the
system timer using the function:

\begin{hol}\begin{verbatim}
   timer : bool -> bool
\end{verbatim}\end{hol}

\noindent Evaluating \ml{timer~true} switches on timing; evaluating
\ml{timer~false} switches it off (the previous value of the timing flag
is returned). Garbage collection times are also shown, together with a
count of the number of intermediate theorems that are generated (which
gives an estimate of the number of primitive inferences done).

\begin{session}\begin{verbatim}
#timer true;;
false : bool
Run time: 0.0s

#CONJ_NORM_CONV ex1;;
|- A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D = A /\ B /\ C /\ D
Run time: 1.1s
Garbage collection time: 0.5s
Intermediate theorems generated: 73
\end{verbatim}\end{session}

\noindent Here is a bigger example:

\begin{session}\begin{verbatim}
#CONJ_NORM_CONV "^ex1 /\ (^ex1 /\ (^ex1 /\ ^ex1 /\ ^ex1) /\ ^ex1)";;
|- (A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
   (A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
   ((A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
    (A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
    A /\
    (B /\ C /\ A) /\
    (C /\ A /\ D) /\
    D) /\
   A /\
   (B /\ C /\ A) /\
   (C /\ A /\ D) /\
   D =
   A /\ B /\ C /\ D
Run time: 38.3s
Garbage collection time: 11.5s
Intermediate theorems generated: 16761
\end{verbatim}\end{session}

The reason that \ml{CONJ\_CANON\_CONV} is slow is because of the
repeated pattern matching done during rewriting. A much more efficient
approach is to normalize the conjunction by \ML\ programming outside
the logic, and then to prove that the normalized term is equal to the
original one. An even more efficient approach, which is not explored
here, would be to avoid having to do this proof by verifing the
normalization code by some sort of meta-theoretic
reasoning about \ML. How to do this in
\HOL\ is not clear, but work on this approach has been done in the
context of {\small FOL} \cite{FOL}, the Boyer-Moore prover \cite{BoyerMoore}
and Nuprl \cite{Nuprl}. These approaches all use logically
sophisticated extra axioms, called reflection principles, that enable
metatheorems to be `reflected' into the logic as object level
theorems.

To normalize the term by \ML\ programming, the conjuncts are extracted,
repeated elements are deleted and the resulting list is sorted.

\HOL\ already has a predefined function:

\begin{hol}\begin{verbatim}
   conjuncts : term -> term list
\end{verbatim}\end{hol}

\noindent for extracting conjuncts.
\HOL\ also has a predefined \ML\ function for removing repeated elements of
a list:


\begin{hol}\begin{verbatim}
   setify : * list -> * list
\end{verbatim}\end{hol}

\noindent Both \ml{conjuncts} and \ml{setify} are illustrated below:

\begin{session}\begin{verbatim}
#timer false;;
true : bool

#conjuncts ex1;;
["A"; "B"; "C"; "A"; "C"; "A"; "D"; "D"] : term list

#setify it;;
["B"; "C"; "A"; "D"] : term list

#let ex1_list = it;;
ex1_list = ["B"; "C"; "A"; "D"] : term list
\end{verbatim}\end{session}

There is a predefined sorting function in \ML:

\begin{session}\begin{verbatim}
#sort;; 
sort = - : (((* # *) -> bool) -> * list -> * list)

#sort $< [3;2;5;6;1;1;7;9;3];;
[1; 1; 2; 3; 3; 5; 6; 7; 9] : int list

#sort $<< ex1_list;;
["A"; "B"; "C"; "D"] : term list
\end{verbatim}\end{session}

Using this function, the list of conjuncts of the normalization of a
term is easily computed.  The predefined \ML\ function:

\begin{hol}\begin{verbatim}
   list_mk_conj : term list -> term
\end{verbatim}\end{hol}

\noindent can then be used to build the normalized conjunction.


\begin{session}\begin{verbatim}
#ex1;;
"A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D" : term

#let ex1_norm = list_mk_conj(sort $<< (setify(conjuncts ex1)));;
ex1_norm = "A /\ B /\ C /\ D" : term
\end{verbatim}\end{session}

\noindent The calculation of \ml{ex1\_norm} from \ml{ex1} has been
done by (unverified) \ML\ code. What is required is the theorem
asserting that they are equal. This can be proved using the tautology
checker.

\begin{session}\begin{verbatim}
#TAUT_RULE "^ex1 = ^ex1_norm";;
|- A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D = A /\ B /\ C /\ D
\end{verbatim}\end{session}

\noindent A conversion that normalizes conjunctions is thus:

\begin{session}\begin{verbatim}
#let CONJ_NORM_CONV2 t =
# if is_conj t
#  then TAUT_RULE "^t = ^(list_mk_conj(sort $<< (setify(conjuncts t))))"
#  else fail;;
CONJ_NORM_CONV2 = - : conv

#CONJ_NORM_CONV2 ex1;;
|- A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D = A /\ B /\ C /\ D
\end{verbatim}\end{session}

\noindent \ml{CONJ\_CANON\_CONV2} is more than an order of magnitude faster 
than \ml{CONJ\_CANON\_CONV}:


\begin{session}\begin{verbatim}
#timer true;;
false : bool
Run time: 0.0s

#CONJ_NORM_CONV2 "^ex1 /\ (^ex1 /\ (^ex1 /\ ^ex1 /\ ^ex1) /\ ^ex1)";;
|- (A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
   (A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
   ((A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
    (A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
    A /\
    (B /\ C /\ A) /\
    (C /\ A /\ D) /\
    D) /\
   A /\
   (B /\ C /\ A) /\
   (C /\ A /\ D) /\
   D =
   A /\ B /\ C /\ D
Run time: 1.9s
Garbage collection time: 0.5s
Intermediate theorems generated: 1273
\end{verbatim}\end{session}

\section{An even more efficient implementation}\label{bogus-optimization}

Although the implementation just given is much faster than the first
naive one, it can be improved further by replacing the call to the
general tautology checker with a special purpose conjunction-equivalence
prover.

To see how this works, the equivalence of \ml{ex1} and \ml{ex1\_norm} will first
be proved manually. The general form of this proof will then be abstracted into
a derived rule.

The goal is to prove that \ml{ex1} and \ml{ex1\_norm} are equal.

\begin{session}\begin{verbatim}
#timer false;;
true : bool

#g "^ex1 = ^ex1_norm";;
"A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D = A /\ B /\ C /\ D"

() : void
\end{verbatim}\end{session}

\noindent The predefined tactic \ml{EQ\_TAC} splits an equation into two
implications (see Section~\ref{EQTAC}).

\begin{session}\begin{verbatim}
#e EQ_TAC;;
OK..
2 subgoals
"A /\ B /\ C /\ D ==> A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D"

"A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D ==> A /\ B /\ C /\ D"

() : void
\end{verbatim}\end{session}

\noindent Each of these can be solved by:
\begin{enumerate}
\item moving the antecedent of the
implication to the assumption list (using \ml{DISCH\_TAC}, see
Section~\ref{DISCHTAC});
\item breaking up the remaining
goal (the consequent of the implication) into one subgoal per conjunct (using
\ml{CONJ\_TAC}, see Section~\ref{CONJTAC});
\item  solving each of these
conjuncts using the antecedent (which is now an assumption)
\end{enumerate}

\noindent Step 1--3 are now done interactively.

\begin{session}\begin{verbatim}
#e DISCH_TAC;;
OK..
"A /\ B /\ C /\ D"
    [ "A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D" ]

() : void
\end{verbatim}\end{session}

\noindent \ml{CONJ\_TAC} is repeated using the tactical \ml{REPEAT}
described in Section~\ref{THEN}.

\begin{session}\begin{verbatim}
#e (REPEAT CONJ_TAC);;
OK..
4 subgoals
"D"
    [ "A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D" ]

"C"
    [ "A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D" ]

"B"
    [ "A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D" ]

"A"
    [ "A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D" ]

() : void
\end{verbatim}\end{session}

\noindent The final step is to use the assumption
{\small\verb%"A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D"%} to solve each goal.
To do this, the assumption is grabbed using the tactical:

\begin{hol}\begin{verbatim}
   POP_ASSUM : (thm -> tactic) -> tactic
\end{verbatim}\end{hol}

\noindent Given a function \ml{$f$ : thm -> tactic}, the tactic
\ml{POP\_ASSUM}\ $f$ applies $f$ to the (assumed) first
assumption of a goal
and then applies the tactic created thereby to the original goal
minus its top assumption:

\begin{hol}\begin{alltt}
   POP_ASSUM \(f\) ([\(t\sb{1}\);\(\ldots\);\(t\sb{n}\)],\(t\)) = \(f\) (ASSUME \(t\sb{1}\)) ([\(t\sb{2}\);\(\ldots\);\(t\sb{n}\)],\(t\))
\end{alltt}\end{hol}

\noindent \ML\ functions such as $f$,
with type \ml{thm -> tactic} are abbreviated to \ml{thm\_tactic} (see
\DESCRIPTION\ for further details).

After grabbing the assumption, it is split into its individual conjunctions
using the predefined derived rule:

\begin{hol}\begin{verbatim}
   CONJUNCTS : thm -> thm list
\end{verbatim}\end{hol}

\noindent For example:


\begin{session}\begin{verbatim}
#CONJUNCTS(ASSUME "A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D");;
[. |- A; . |- B; . |- C; . |- A; . |- C; . |- A; . |- D; . |- D]
: thm list
\end{verbatim}\end{session}

\noindent Among the individual conjuncts is the goal, which can thus be
solved immediately using \ml{ACCEPT\_TAC} (see Section~\ref{ACCEPTTAC}).
The appropriate assumption can be chosen with the predefined tactical
\ml{MAP\_FIRST}, which
is characterized by:

\begin{hol}\begin{alltt}
   MAP_FIRST \(f\) [\(x\sb{1}\); \(\ldots\) ;\(x\sb{n}\)]  =  \(f\)(\(x\sb{1}\)) ORELSE \(\ldots\) ORELSE \(f\)(\(x\sb{n}\))
\end{alltt}\end{hol}

\noindent Returning to the proof: the final step is now performed by
popping the assumption and applying to it the function obtained by
composing \ml{CONJUNCTS} and \ml{MAP\_FIRST} using the \ML\ infixed
function composition operator \ml{o} 
(where \ml{(}$f$~\ml{o}~$g$\ml{)}$x$~\ml{=}~$g$\ml{(}$f$\ml{(}$x$\ml{))}).

\begin{session}\begin{verbatim}
#e(POP_ASSUM(MAP_FIRST ACCEPT_TAC o CONJUNCTS));;
OK..
goal proved
. |- A

Previous subproof:
3 subgoals
"D"
    [ "A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D" ]

"C"
    [ "A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D" ]

"B"
    [ "A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D" ]

() : void
\end{verbatim}\end{session}


\noindent The remaining subgoals are solved identically. Stitching together
the tactics just used results in:

\begin{hol}\begin{verbatim}
   EQ_TAC          THEN 
   DISCH_TAC       THEN
   REPEAT CONJ_TAC THEN 
   POP_ASSUM(MAP_FIRST ACCEPT_TAC o CONJUNCTS)
\end{verbatim}\end{hol}

\noindent With this, the entire proof can be done in one step.

\begin{session}\begin{verbatim}
#g "^ex1 = ^ex1_norm";;
"A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D = A /\ B /\ C /\ D"

() : void

#e(EQ_TAC          THEN 
#  DISCH_TAC       THEN
#  REPEAT CONJ_TAC THEN 
#  POP_ASSUM(MAP_FIRST ACCEPT_TAC o CONJUNCTS));;
OK..
goal proved
|- A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D = A /\ B /\ C /\ D

Previous subproof:
goal proved
() : void
\end{verbatim}\end{session}

Using this tactic, a derived rule \ml{CONJ\_EQ} can be defined that proves
two conjunctions equal. This is what is needed to replace the call to
\ml{TAUT\_RULE}.
\ml{CONJ\_EQ} is defined with the predefined function:

\begin{hol}\begin{verbatim}
   PROVE : term # tactic -> theorem
\end{verbatim}\end{hol}

\noindent \ml{PROVE}\ml{(}$t$\ml{,}$T$\ml{)} applies the tactic $T$ to
the goal \ml{([],}$t$\ml{)}; if this goal is proved by $T$ then the
resulting justification is applied to \ml{[]} to obtain the theorem
\ml{|-}~$t$, which is returned. If $T$ does not solve the goal, then
the application of \ml{PROVE} fails. Using \ml{PROVE}, the definition
of \ml{CONJ\_EQ} is:

\begin{hol}\begin{verbatim}
   let CONJ_EQ t1 t2 = 
    PROVE ("^t1 = ^t2", 
           EQ_TAC          THEN 
           DISCH_TAC       THEN
           REPEAT CONJ_TAC THEN 
           POP_ASSUM(MAP_FIRST ACCEPT_TAC o CONJUNCTS))
\end{verbatim}\end{hol}


\noindent Replacing the call to \ml{TAUT\_RULE} in the definition
of \ml{CONJ\_NORM\_CONV2} results in:

\begin{hol}\begin{verbatim}
   let CONJ_NORM_CONV3 t =
    if is_conj t
     then CONJ_EQ t (list_mk_conj(sort $<< (setify(conjuncts t))))
     else fail
\end{verbatim}\end{hol}

\noindent Continuing the session:

\begin{session}\begin{verbatim}
#let CONJ_EQ t1 t2 = 
# PROVE ("^t1 = ^t2", 
#        EQ_TAC          THEN 
#        DISCH_TAC       THEN
#        REPEAT CONJ_TAC THEN 
#        POP_ASSUM(MAP_FIRST ACCEPT_TAC o CONJUNCTS));;
CONJ_EQ = - : (term -> conv)

#let CONJ_NORM_CONV3 t =
# if is_conj t
#  then CONJ_EQ t (list_mk_conj(sort $<< (setify(conjuncts t))))
#  else fail;;
CONJ_NORM_CONV3 = - : conv
\end{verbatim}\end{session}

\noindent \ml{CONJ\_NORM\_CONV3} is almost twice
as efficient as \ml{CONJ\_NORM\_CONV2}. To show this, the timer is switched 
back on.

\begin{session}\begin{verbatim}
#timer true;;
false : bool
Run time: 0.0s
\end{verbatim}\end{session}

\noindent Here is the big example with \ml{CONJ\_NORM\_CONV3}:

\begin{session}\begin{verbatim}
#CONJ_NORM_CONV3 "^ex1 /\ (^ex1 /\ (^ex1 /\ ^ex1 /\ ^ex1) /\ ^ex1)";;
|- (A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
   (A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
   ((A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
    (A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
    A /\
    (B /\ C /\ A) /\
    (C /\ A /\ D) /\
    D) /\
   A /\
   (B /\ C /\ A) /\
   (C /\ A /\ D) /\
   D =
   A /\ B /\ C /\ D
Run time: 1.0s
Garbage collection time: 0.5s
Intermediate theorems generated: 775
\end{verbatim}\end{session}

\section{Further optimizations}

Further improvements are still possible. As an exercise the reader
might want to decipher the following highly optimized definition of
\ml{CONJ\_EQ}.

The function \ml{PROVE\_CONJ}, defined below, 
converts a term $t$ to the theorem \ml{|-}~$t$
if that theorem occurs in a supplied list of theorems (\ml{ths} in the
code below), or $t$ is a conjunction each of whose conjuncts occurs in
the list. The definition of \ml{PROVE\_CONJ} uses the following
predefined \ML\ functions:

\begin{itemize}
\item \ml{uncurry}~$f$~\ml{(}$x$\ml{,}$y$\ml{)}~~\ml{=}~~$f$~$x$~$y$

\item \ml{(}$f${\small\verb% # %}$g$\ml{)}\ml{(}$x$\ml{,}$y$\ml{)}~~\ml{=}~~\ml{(}$f\ x$~\ml{,}~$g\ y$\ml{)}

\item \ml{find}~$p$~\ml{[}$x_1\ml{;}\ldots\ml{;}x_n$\ml{]}~~=~~{\it the first $x_i$ for which $p\ x_i$ is true\/}

\end{itemize}

\noindent and the inference rule \ml{CONJ}:


\[ \Gamma_1\turn
t_1\qquad\qquad\qquad\Gamma_2\turn t_2\over \Gamma_1\cup\Gamma_2 \turn t_1\conj
t_2 \]


\noindent Here is the definition of \ml{PROVE\_CONJ}:

\begin{hol}\begin{verbatim}
   letrec PROVE_CONJ ths tm =
    (uncurry CONJ ((PROVE_CONJ ths # PROVE_CONJ ths) (dest_conj tm))) ?
    find (\th. concl th = tm) ths
\end{verbatim}\end{hol}

\noindent Using this, the optimized \ml{CONJ\_EQ}, called
\ml{CONJ\_EQ2}, is defined using \ml{IMP\_ANTISYM\_RULE} (a predefined rule):


\[ \Gamma_1 \turn t_1 \imp t_2 \qquad\qquad \Gamma_2\turn t_2 \imp t_1\over
\Gamma_1 \cup \Gamma_2 \turn t_1 = t_2\]

\noindent The definition is:

\begin{hol}\begin{verbatim}
   let CONJ_EQ2 t1 t2 =
    let imp1 = DISCH t1 (PROVE_CONJ (CONJUNCTS(ASSUME t1)) t2)
    and imp2 = DISCH t2 (PROVE_CONJ (CONJUNCTS(ASSUME t2)) t1) 
    in IMP_ANTISYM_RULE imp1 imp2
\end{verbatim}\end{hol}

\noindent Loading these \ML\ function definitions into \HOL:

\begin{session}\begin{verbatim}
#letrec PROVE_CONJ ths tm =
# (uncurry CONJ ((PROVE_CONJ ths # PROVE_CONJ ths) (dest_conj tm))) ?
# find (\th. concl th = tm) ths;;
PROVE_CONJ = - : (thm list -> conv)
Run time: 0.0s

#let CONJ_EQ2 t1 t2 =
# let imp1 = DISCH t1 (PROVE_CONJ (CONJUNCTS(ASSUME t1)) t2)
# and imp2 = DISCH t2 (PROVE_CONJ (CONJUNCTS(ASSUME t2)) t1) 
# in IMP_ANTISYM_RULE imp1 imp2;;
CONJ_EQ2 = - : (term -> conv)
Run time: 0.0s
\end{verbatim}\end{session}


\noindent A version of \ml{CONJ\_NORM\_CONV} that
uses \ml{CONJ\_EQ2} is defined by:

\begin{hol}\begin{verbatim}
   let CONJ_NORM_CONV4 t =
    if is_conj t
     then CONJ_EQ2 t (list_mk_conj(sort $<< (setify(conjuncts t))))
     else fail
\end{verbatim}\end{hol}


\noindent Loading this into \ML:

\begin{session}\begin{verbatim}
#let CONJ_NORM_CONV4 t =
# if is_conj t
#  then CONJ_EQ2 t (list_mk_conj(sort $<< (setify(conjuncts t))))
#  else fail;;
CONJ_NORM_CONV4 = - : conv
Run time: 0.0s
\end{verbatim}\end{session}

\noindent This is even faster than \ml{CONJ\_NORM\_CONV3}:

\begin{session}\begin{verbatim}
#CONJ_NORM_CONV4 "^ex1 /\ (^ex1 /\ (^ex1 /\ ^ex1 /\ ^ex1) /\ ^ex1)";;
|- (A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
   (A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
   ((A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
    (A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\
    A /\
    (B /\ C /\ A) /\
    (C /\ A /\ D) /\
    D) /\
   A /\
   (B /\ C /\ A) /\
   (C /\ A /\ D) /\
   D =
   A /\ B /\ C /\ D
Run time: 0.4s
Intermediate theorems generated: 155
\end{verbatim}\end{session}

\section{Normalizing all subterms}

There is an important difference in the functionality of
\ml{CONJ\_NORM\_CONV} and the various optimised versions of it. The
difference is that \ml{CONJ\_NORM\_CONV} applies to any term,
normalizing all subterms that are conjunctions. However the functions
\ml{CONJ\_NORM\_CONV}{\small $n$} (where {\small $n = 2,3,4$}) all 
fail on non-conjunctions.

\begin{session}\begin{verbatim}
#CONJ_NORM_CONV "^ex1 ==> ^ex1";;
|- A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D ==>
   A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D =
   A /\ B /\ C /\ D ==> A /\ B /\ C /\ D
Run time: 2.0s
Garbage collection time: 0.6s
Intermediate theorems generated: 1307

#CONJ_NORM_CONV4 "^ex1 => ^ex1";;
need 2 nd branch to conditional
skipping: ex1 " ;; parse failed     

#CONJ_NORM_CONV4 "^ex1 ==> ^ex1";;
evaluation failed     fail
\end{verbatim}\end{session}

What is needed is a function that will apply a conversion to all
conjunctive subterms of a term. Such a function is \ml{TOP\_DEPTH\_CONV}, however

\begin{hol}\begin{verbatim}
   TOP_DEPTH_CONV CONJ_NORM_CONV4
\end{verbatim}\end{hol}

\noindent would loop, because \ml{CONJ\_NORM\_CONV4} never fails on
conjunctions, so \ml{TOP\_DEPTH\_CONV} would keep applying it forever!
This is easily got around using:

\begin{hol}\begin{verbatim}
   CHANGED_CONV : conv -> conv
\end{verbatim}\end{hol}

\noindent \ml{CHANGED\_CONV}~$c$ behaves like $c$, except that if $c$
has no effect, then \ml{CHANGED\_CONV}~$c$ fails.

\begin{session}\begin{verbatim}
#TOP_DEPTH_CONV(CHANGED_CONV CONJ_NORM_CONV4) "^ex1 ==> ^ex1";;
|- A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D ==>
   A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D =
   A /\ B /\ C /\ D ==> A /\ B /\ C /\ D
Run time: 0.5s
Intermediate theorems generated: 292
\end{verbatim}\end{session}

Although this works, the scanning through subterms done by
\ml{TOP\_DEPTH\_CONV} is a bit `brute force'. Further efficiency can
be obtained by writing a special scanning function that
just applies a conversion to maximal conjunctive subterms.
This is provided by the code below. 
The understanding of this is a fairly hard exercise for the reader. The
section on conversions in \DESCRIPTION\ should be helpful.

First, an auxiliary derived rule for combining two equations into
a single equation by conjoining  the left hand sides and  the
right hand sides.

\begin{session}\begin{verbatim}
#let MK_CONJ th1 th2 = MK_COMB(AP_TERM "$/\" th1, th2);;
MK_CONJ = - : (thm -> thm -> thm)
Run time: 0.0s
\end{verbatim}\end{session}

\noindent Next a function that conjoins the left hand sides and right
hand sides of lists of equations.

\begin{session}\begin{verbatim}
#letrec MK_CONJL l =
# if null l     then fail
# if null(tl l) then hd l
#               else MK_CONJ (hd l) (MK_CONJL(tl l));;
MK_CONJL = - : proof
Run time: 0.0s
\end{verbatim}\end{session}

\noindent Next, a function that applies a conversion $c$ to all
conjunctive subterms of a term. This uses the \ML\ function:

\bigskip
\ml{map}~$f$~\ml{[}$x_1\ml{;}\ldots\ml{;}x_n$\ml{]}~~=~~\ml{[}$f\ x_1\ml{;}\ldots\ml{;}f\ x_n$\ml{]}

\bigskip

\noindent and the rules \ml{MK\_COMB}:


\[ \Gamma_1 \turn f = g \qquad\qquad \Gamma_2\turn x = y \over
\Gamma_1 \cup \Gamma_2 \turn f\ x = g\ y\]

\noindent and \ml{MK\_ABS}:


\[ \Gamma \turn \forall x.\ t_1 = t_2 \over
\Gamma \turn (\lambda x.\ t_1) = (\lambda x.\ t_2)\]

\noindent and \ml{GEN}:

$$\Gamma\turn t\over\Gamma\turn\uquant{x} t$$
\begin{itemize}
\item Where $x$ is not free in $\Gamma$.
\end{itemize}


\noindent and \ml{REFL}: 

$$ \over\turn t = t$$

\begin{itemize}
\item\ml{REFL}~$t$~~\ml{=}~~ $\turn t = t$.
\end{itemize}

\noindent The definition of \ml{CONJ\_DEPTH\_CONV} also uses:

\begin{hol}\begin{verbatim}
   is_comb   : term -> bool
   dest_comb : term -> (term # term)

   is_abs    : term -> bool
   dest_abs  : term -> (term # term)
\end{verbatim}\end{hol}

\noindent which are the tests and destructors for combinations and
abstractions, respectively.

\begin{session}\begin{verbatim}
#letrec CONJ_DEPTH_CONV c tm =
# if is_conj tm 
#  then (c THENC (MK_CONJL o map (CONJ_DEPTH_CONV c) o conjuncts)) tm
# if is_comb tm
#  then (let rator,rand = dest_comb tm in
#         MK_COMB (CONJ_DEPTH_CONV c rator, CONJ_DEPTH_CONV c rand))
# if is_abs tm 
#  then (let bv,body = dest_abs tm in
#         let bodyth = CONJ_DEPTH_CONV c body in
#         MK_ABS (GEN bv bodyth))
#   else (REFL tm);;
CONJ_DEPTH_CONV = - : (conv -> conv)
Run time: 0.0s
\end{verbatim}\end{session}

\noindent The next session shows that \ml{CONJ\_DEPTH\_CONV} is an
improvement over \ml{TOP\_DEPTH\_CONV}.

\begin{session}\begin{verbatim}
#CONJ_DEPTH_CONV CONJ_NORM_CONV4 "^ex1 ==> ^ex1";;
|- A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D ==>
   A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D =
   A /\ B /\ C /\ D ==> A /\ B /\ C /\ D
Run time: 0.4s
Intermediate theorems generated: 95
\end{verbatim}\end{session}

\noindent However, the figures show that we are getting to a point of
diminishing returns.

Finally, the tactic for normalizing all conjunctions in a goal is:

\begin{session}\begin{verbatim}
#let CONJ_NORM_TAC = CONV_TAC (CONJ_DEPTH_CONV CONJ_NORM_CONV4);;
CONJ_NORM_TAC = - : tactic
Run time: 0.0s
\end{verbatim}\end{session}

\noindent This is illustrated by:

\begin{session}\begin{verbatim}
#g "^ex1 ==> ^ex1 /\ ^ex1_norm";;
"A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D ==>
 (A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\ A /\ B /\ C /\ D"

() : void
Run time: 0.1s

#e CONJ_NORM_TAC;;
OK..
"A /\ B /\ C /\ D ==> A /\ B /\ C /\ D"

() : void
Run time: 0.3s
Intermediate theorems generated: 110
\end{verbatim}\end{session}

\noindent To show how much faster the optimized version is, here is
the last step repeated with the first version of the tool. The \ML\
function \ml{b} backs up to the last goal.

\begin{session}\begin{verbatim}
#b();;
"A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D ==>
 (A /\ (B /\ C /\ A) /\ (C /\ A /\ D) /\ D) /\ A /\ B /\ C /\ D"

() : void
Run time: 0.1s
\end{verbatim}\end{session}

\noindent Expanding with the slow tactic:

\begin{session}\begin{verbatim}
#e(CONV_TAC CONJ_NORM_CONV);;
OK..
"A /\ B /\ C /\ D ==> A /\ B /\ C /\ D"

() : void
Run time: 3.5s
Garbage collection time: 1.0s
Intermediate theorems generated: 1932
\end{verbatim}\end{session}

\noindent it is 10 times slower and generates almost 20 times as many
primitive inference steps!


Here is the complete \ML\ program for the optimized normalizer.

\begin{hol}\begin{verbatim}
   letrec insert ord x l =
    if null l 
     then [x]
    if ord(x,hd l)
     then x.l
     else hd l.(insert ord x (tl l));;

   letrec sort ord l =
    if null l
     then []
     else insert ord (hd l) (sort ord (tl l));;
\end{verbatim}\end{hol}

\begin{hol}\begin{verbatim}
   letrec PROVE_CONJ ths tm =
    (uncurry CONJ ((PROVE_CONJ ths # PROVE_CONJ ths) (dest_conj tm))) ?
    find (\th. concl th = tm) ths;;

   let CONJ_EQ t1 t2 =
    let imp1 = DISCH t1 (PROVE_CONJ (CONJUNCTS(ASSUME t1)) t2)
    and imp2 = DISCH t2 (PROVE_CONJ (CONJUNCTS(ASSUME t2)) t1) 
    in IMP_ANTISYM_RULE imp1 imp2;;
\end{verbatim}\end{hol}

\begin{hol}\begin{verbatim}
   let CONJ_NORM_CONV t =
    if is_conj t
     then CONJ_EQ t (list_mk_conj(sort $<< (setify(conjuncts t))))
     else fail;;
\end{verbatim}\end{hol}

\begin{hol}\begin{verbatim}
   let MK_CONJ th1 th2 = MK_COMB(AP_TERM "$/\" th1, th2);;

   letrec MK_CONJL l =
    if null l     then fail
    if null(tl l) then hd l
                  else MK_CONJ (hd l) (MK_CONJL(tl l));;
\end{verbatim}\end{hol}

\begin{hol}\begin{verbatim}
   letrec CONJ_DEPTH_CONV c tm =
    if is_conj tm 
     then (c THENC (MK_CONJL o map (CONJ_DEPTH_CONV c) o conjuncts)) tm
    if is_comb tm
     then (let rator,rand = dest_comb tm in
            MK_COMB (CONJ_DEPTH_CONV c rator, CONJ_DEPTH_CONV c rand))
    if is_abs tm 
     then (let bv,body = dest_abs tm in
            let bodyth = CONJ_DEPTH_CONV c body in
            MK_ABS (GEN bv bodyth))
     else (REFL tm);;
\end{verbatim}\end{hol}

\begin{hol}\begin{verbatim}
   let CONJ_NORM_TAC = CONV_TAC (CONJ_DEPTH_CONV CONJ_NORM_CONV);;
\end{verbatim}\end{hol}


Although the optimized implementation is much more efficient, it uses
less general methods. An advantage of the simple implementation based
on rewriting is that essentially the same algorithm can be used to
normalize terms built out of any associative, commutative and
idenpotent operation. The two exercises that follow (whose solutions are not
supplied) suggest that the reader try to extract general principles from the
conjunction normalizer and use these to implement generic tools.

\subsection{Exercise 1}

Implement a normalizer for any associative and commutative operator.

\begin{hol}\begin{verbatim}
   AC_CANON_CONV : thm # thm -> conv
\end{verbatim}\end{hol}

\noindent The two theorem arguments should be the
associative and commutative laws for the operator. For example:

\begin{hol}\begin{verbatim}
   AC_CANON_CONV(ASSOC,SYM1)
\end{verbatim}\end{hol}

\noindent would be a canonicalizer for conjunctions.
Use the `brute force' rewriting method described at the beginning of this chapter.

\subsection{Exercise 2}


Implement an optimized canonicalizer:

\begin{hol}\begin{verbatim}
   FAST_AC_CANON_CONV : thm # thm -> conv \end{verbatim}\end{hol}
\noindent This should use tuned rewriting (\eg\ a generalization of
\ml{CONJ\_DEPTH\_CONV}) and be as fast as possible. Try to think up
tricks to minimise the amount of general matching and to make every
inference count.


