\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}{0} \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.