Paper.thy
author Christian Urban <christian dot urban at kcl dot ac dot uk>
Fri, 04 Jan 2013 22:49:02 +0000
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(*<*)
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theory Paper
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imports UTM
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begin
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declare [[show_question_marks = false]]
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(*>*)
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section {* Introduction *}
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text {*
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\noindent
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We formalised in earlier work the correctness proofs for two
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algorithms in Isabelle/HOL---one about type-checking in
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LF~\cite{UrbanCheneyBerghofer11} and another about deciding requests
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in access control~\cite{WuZhangUrban12}.  The formalisations
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uncovered a gap in the informal correctness proof of the former and
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made us realise that important details were left out in the informal
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model for the latter. However, in both cases we were unable to
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formalise in Isabelle/HOL computability arguments about the
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algorithms. The reason is that both algorithms are formulated in terms
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of inductive predicates. Suppose @{text "P"} stands for one such
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predicate.  Decidability of @{text P} usually amounts to showing
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whether \mbox{@{term "P \<or> \<not>P"}} holds. But this does \emph{not} work
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in Isabelle/HOL, since it is a theorem prover based on classical logic
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where the law of excluded middle ensures that \mbox{@{term "P \<or> \<not>P"}}
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is always provable no matter whether @{text P} is constructed by
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computable means. The same problem would arise if we had formulated
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the algorithms as recursive functions, because internally in
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Isabelle/HOL, like in all HOL-based theorem provers, functions are
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represented as inductively defined predicates too.
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The only satisfying way out of this problem in a theorem prover based on classical
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logic is to formalise a theory of computability. Norrish provided such
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a formalisation for the HOL4 theorem prover. He choose the
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$\lambda$-calculus as the starting point for his formalisation
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of computability theory,
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because of its ``simplicity'' \cite[Page 297]{Norrish11}.  Part of his
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formalisation is a clever infrastructure for reducing
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$\lambda$-terms. He also established the computational equivalence
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between the $\lambda$-calculus and recursive functions.  Nevertheless he
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concluded that it would be ``appealing'' to have formalisations for more
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operational models of computations, such as Turing machines or register
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machines.  One reason is that many proofs in the literature use 
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them.  He noted however that in the context of theorem provers
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\cite[Page 310]{Norrish11}:
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\begin{quote}
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\it``If register machines are unappealing because of their 
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general fiddliness, Turing machines are an even more 
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daunting prospect.''
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\end{quote}
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\noindent
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In this paper we took on this daunting prospect and provide a
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formalisation of Turing machines, as well as abacus machines (a kind
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of register machines) and recursive functions. To see the difficulties
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involved with this work, one has to understand that interactive
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theorem provers, like Isabelle/HOL, are at their best when the
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data-structures at hand are ``structurally'' defined, like lists,
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natural numbers, regular expressions, etc. Such data-structures come
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in theorem provers with convenient reasoning infrastructures (for
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example induction principles, recursion combinators and so on).  But
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this is \emph{not} the case with Turing machines (and also not with
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register machines): underlying their definition is a set of states
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together with a transition function, both of which are not
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structurally defined.  This means we have to implement our own
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reasoning infrastructure in order to prove properties about them. This
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leads to annoyingly lengthy and detailed formalisations.  We noticed
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first the difference between both structural and non-structural
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``worlds'' when formalising the Myhill-Nerode theorem, where regular
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expressions fared much better than automata \cite{WuZhangUrban11}.
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However, with Turing machines there seems to be no alternative if one
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wants to formalise the great many proofs that use them. We give as
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example one proof---undecidability of Wang tilings---in Section
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\ref{Wang}. The standard proof of this property uses the notion of
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\emph{universal Turing machines}.
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We are not the first who formalised Turing machines in a theorem
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prover: we are aware of the preliminary work by Asperti and Ricciotti
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\cite{AspertiRicciotti12}. They describe a formalisation of Turing
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machines in the Matita theorem prover. They report 
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that the informal proofs from which they started are not 
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``sufficiently accurate to be directly used as a guideline for 
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formalization'' \cite[Page 2]{AspertiRicciotti12}. For our formalisation 
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we followed the proofs from the textbook \cite{Boolos87} and found that the description
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is quite detailed. Some details are left out however: for 
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example, it is only shown how the universal
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Turing machine is constructed for Turing machines computing unary 
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functions. We had to figure out a way to generalize this result to
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$n$-ary functions. Similarly, when compiling recursive functions to 
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abacus machines, the textbook again only shows how it can be done for 
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2- and 3-ary functions, but in the formalisation we need arbitrary 
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function. But the general ideas for how to do this are clear enough in 
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\cite{Boolos87}.
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The main difference between our formalisation and the one by Asperti and
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Ricciotti is 
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that their universal machines 
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\begin{quote}
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``In particular, the fact that the universal machine operates with a
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different alphabet with respect to the machines it simulates is
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annoying.'' 
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\end{quote}
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\noindent
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{\bf Contributions:} 
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*}
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section {* Formalisation *}
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text {*
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*}
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section {* Wang Tiles\label{Wang} *}
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text {*
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  Used in texture mapings - graphics
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*}
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section {* Related Work *}
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text {*
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  The most closely related work is by Norrish. He bases his approach on 
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  lambda-terms. For this he introduced a clever rewriting technology
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  based on combinators and de-Bruijn indices for
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  rewriting modulo $\beta$-equivalence (to keep it manageable)
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*}
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(*
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Questions:
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Can this be done: Ackerman function is not primitive 
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recursive (Nora Szasz)
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Tape is represented as two lists (finite - usually infinite tape)?
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*)
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(*<*)
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end
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(*>*)