doc-src/IsarAdvanced/Codegen/Thy/Introduction.thy
changeset 30228 2aaf339fb7c1
parent 30224 79136ce06bdb
parent 30227 853abb4853cc
child 30229 9861257b18e6
child 30243 09d5944e224e
--- a/doc-src/IsarAdvanced/Codegen/Thy/Introduction.thy	Tue Mar 03 17:05:18 2009 +0100
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,206 +0,0 @@
-theory Introduction
-imports Setup
-begin
-
-chapter {* Code generation from @{text "Isabelle/HOL"} theories *}
-
-section {* Introduction and Overview *}
-
-text {*
-  This tutorial introduces a generic code generator for the
-  @{text Isabelle} system.
-  Generic in the sense that the
-  \qn{target language} for which code shall ultimately be
-  generated is not fixed but may be an arbitrary state-of-the-art
-  functional programming language (currently, the implementation
-  supports @{text SML} \cite{SML}, @{text OCaml} \cite{OCaml} and @{text Haskell}
-  \cite{haskell-revised-report}).
-
-  Conceptually the code generator framework is part
-  of Isabelle's @{theory Pure} meta logic framework; the logic
-  @{theory HOL} which is an extension of @{theory Pure}
-  already comes with a reasonable framework setup and thus provides
-  a good working horse for raising code-generation-driven
-  applications.  So, we assume some familiarity and experience
-  with the ingredients of the @{theory HOL} distribution theories.
-  (see also \cite{isa-tutorial}).
-
-  The code generator aims to be usable with no further ado
-  in most cases while allowing for detailed customisation.
-  This manifests in the structure of this tutorial: after a short
-  conceptual introduction with an example (\secref{sec:intro}),
-  we discuss the generic customisation facilities (\secref{sec:program}).
-  A further section (\secref{sec:adaption}) is dedicated to the matter of
-  \qn{adaption} to specific target language environments.  After some
-  further issues (\secref{sec:further}) we conclude with an overview
-  of some ML programming interfaces (\secref{sec:ml}).
-
-  \begin{warn}
-    Ultimately, the code generator which this tutorial deals with
-    is supposed to replace the existing code generator
-    by Stefan Berghofer \cite{Berghofer-Nipkow:2002}.
-    So, for the moment, there are two distinct code generators
-    in Isabelle.  In case of ambiguity, we will refer to the framework
-    described here as @{text "generic code generator"}, to the
-    other as @{text "SML code generator"}.
-    Also note that while the framework itself is
-    object-logic independent, only @{theory HOL} provides a reasonable
-    framework setup.    
-  \end{warn}
-
-*}
-
-subsection {* Code generation via shallow embedding \label{sec:intro} *}
-
-text {*
-  The key concept for understanding @{text Isabelle}'s code generation is
-  \emph{shallow embedding}, i.e.~logical entities like constants, types and
-  classes are identified with corresponding concepts in the target language.
-
-  Inside @{theory HOL}, the @{command datatype} and
-  @{command definition}/@{command primrec}/@{command fun} declarations form
-  the core of a functional programming language.  The default code generator setup
-  allows to turn those into functional programs immediately.
-  This means that \qt{naive} code generation can proceed without further ado.
-  For example, here a simple \qt{implementation} of amortised queues:
-*}
-
-datatype %quote 'a queue = AQueue "'a list" "'a list"
-
-definition %quote empty :: "'a queue" where
-  "empty = AQueue [] []"
-
-primrec %quote enqueue :: "'a \<Rightarrow> 'a queue \<Rightarrow> 'a queue" where
-  "enqueue x (AQueue xs ys) = AQueue (x # xs) ys"
-
-fun %quote dequeue :: "'a queue \<Rightarrow> 'a option \<times> 'a queue" where
-    "dequeue (AQueue [] []) = (None, AQueue [] [])"
-  | "dequeue (AQueue xs (y # ys)) = (Some y, AQueue xs ys)"
-  | "dequeue (AQueue xs []) =
-      (case rev xs of y # ys \<Rightarrow> (Some y, AQueue [] ys))"
-
-text {* \noindent Then we can generate code e.g.~for @{text SML} as follows: *}
-
-export_code %quote empty dequeue enqueue in SML
-  module_name Example file "examples/example.ML"
-
-text {* \noindent resulting in the following code: *}
-
-text %quote {*@{code_stmts empty enqueue dequeue (SML)}*}
-
-text {*
-  \noindent The @{command export_code} command takes a space-separated list of
-  constants for which code shall be generated;  anything else needed for those
-  is added implicitly.  Then follows a target language identifier
-  (@{text SML}, @{text OCaml} or @{text Haskell}) and a freely chosen module name.
-  A file name denotes the destination to store the generated code.  Note that
-  the semantics of the destination depends on the target language:  for
-  @{text SML} and @{text OCaml} it denotes a \emph{file}, for @{text Haskell}
-  it denotes a \emph{directory} where a file named as the module name
-  (with extension @{text ".hs"}) is written:
-*}
-
-export_code %quote empty dequeue enqueue in Haskell
-  module_name Example file "examples/"
-
-text {*
-  \noindent This is how the corresponding code in @{text Haskell} looks like:
-*}
-
-text %quote {*@{code_stmts empty enqueue dequeue (Haskell)}*}
-
-text {*
-  \noindent This demonstrates the basic usage of the @{command export_code} command;
-  for more details see \secref{sec:further}.
-*}
-
-subsection {* Code generator architecture \label{sec:concept} *}
-
-text {*
-  What you have seen so far should be already enough in a lot of cases.  If you
-  are content with this, you can quit reading here.  Anyway, in order to customise
-  and adapt the code generator, it is inevitable to gain some understanding
-  how it works.
-
-  \begin{figure}[h]
-    \begin{tikzpicture}[x = 4.2cm, y = 1cm]
-      \tikzstyle entity=[rounded corners, draw, thick, color = black, fill = white];
-      \tikzstyle process=[ellipse, draw, thick, color = green, fill = white];
-      \tikzstyle process_arrow=[->, semithick, color = green];
-      \node (HOL) at (0, 4) [style=entity] {@{text "Isabelle/HOL"} theory};
-      \node (eqn) at (2, 2) [style=entity] {code equations};
-      \node (iml) at (2, 0) [style=entity] {intermediate language};
-      \node (seri) at (1, 0) [style=process] {serialisation};
-      \node (SML) at (0, 3) [style=entity] {@{text SML}};
-      \node (OCaml) at (0, 2) [style=entity] {@{text OCaml}};
-      \node (further) at (0, 1) [style=entity] {@{text "\<dots>"}};
-      \node (Haskell) at (0, 0) [style=entity] {@{text Haskell}};
-      \draw [style=process_arrow] (HOL) .. controls (2, 4) ..
-        node [style=process, near start] {selection}
-        node [style=process, near end] {preprocessing}
-        (eqn);
-      \draw [style=process_arrow] (eqn) -- node (transl) [style=process] {translation} (iml);
-      \draw [style=process_arrow] (iml) -- (seri);
-      \draw [style=process_arrow] (seri) -- (SML);
-      \draw [style=process_arrow] (seri) -- (OCaml);
-      \draw [style=process_arrow, dashed] (seri) -- (further);
-      \draw [style=process_arrow] (seri) -- (Haskell);
-    \end{tikzpicture}
-    \caption{Code generator architecture}
-    \label{fig:arch}
-  \end{figure}
-
-  The code generator employs a notion of executability
-  for three foundational executable ingredients known
-  from functional programming:
-  \emph{code equations}, \emph{datatypes}, and
-  \emph{type classes}.  A code equation as a first approximation
-  is a theorem of the form @{text "f t\<^isub>1 t\<^isub>2 \<dots> t\<^isub>n \<equiv> t"}
-  (an equation headed by a constant @{text f} with arguments
-  @{text "t\<^isub>1 t\<^isub>2 \<dots> t\<^isub>n"} and right hand side @{text t}).
-  Code generation aims to turn code equations
-  into a functional program.  This is achieved by three major
-  components which operate sequentially, i.e. the result of one is
-  the input
-  of the next in the chain,  see diagram \ref{fig:arch}:
-
-  \begin{itemize}
-
-    \item Out of the vast collection of theorems proven in a
-      \qn{theory}, a reasonable subset modelling
-      code equations is \qn{selected}.
-
-    \item On those selected theorems, certain
-      transformations are carried out
-      (\qn{preprocessing}).  Their purpose is to turn theorems
-      representing non- or badly executable
-      specifications into equivalent but executable counterparts.
-      The result is a structured collection of \qn{code theorems}.
-
-    \item Before the selected code equations are continued with,
-      they can be \qn{preprocessed}, i.e. subjected to theorem
-      transformations.  This \qn{preprocessor} is an interface which
-      allows to apply
-      the full expressiveness of ML-based theorem transformations
-      to code generation;  motivating examples are shown below, see
-      \secref{sec:preproc}.
-      The result of the preprocessing step is a structured collection
-      of code equations.
-
-    \item These code equations are \qn{translated} to a program
-      in an abstract intermediate language.  Think of it as a kind
-      of \qt{Mini-Haskell} with four \qn{statements}: @{text data}
-      (for datatypes), @{text fun} (stemming from code equations),
-      also @{text class} and @{text inst} (for type classes).
-
-    \item Finally, the abstract program is \qn{serialised} into concrete
-      source code of a target language.
-
-  \end{itemize}
-
-  \noindent From these steps, only the two last are carried out outside the logic;  by
-  keeping this layer as thin as possible, the amount of code to trust is
-  kept to a minimum.
-*}
-
-end