Preface.v

(** * Preface *)

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(** * Welcome *)

(** This is the entry point in a series of electronic textbooks on
    various aspects of _Software Foundations_ -- the mathematical
    underpinnings of reliable software.  Topics in the series include
    basic concepts of logic, computer-assisted theorem proving, the
    Coq proof assistant, functional programming, operational
    semantics, logics for reasoning about programs, and static type
    systems.  The exposition is intended for a broad range of readers,
    from advanced undergraduates to PhD students and researchers.  No
    specific background in logic or programming languages is assumed,
    though a degree of mathematical maturity will be helpful.

    The principal novelty of the series is that it is one hundred
    percent formalized and machine-checked: each text is literally a
    script for Coq.  The books are intended to be read alongside (or
    inside) an interactive session with Coq.  All the details in the
    text are fully formalized in Coq, and most of the exercises are
    designed to be worked using Coq.

    The files in each book are organized into a sequence of core
    chapters, covering about one semester's worth of material and
    organized into a coherent linear narrative, plus a number of
    "offshoot" chapters covering additional topics.  All the core
    chapters are suitable for both upper-level undergraduate and
    graduate students.

    This book, _Logical Foundations_, lays groundwork for the others,
    introducing the reader to the basic ideas of functional
    programming, constructive logic, and the Coq proof assistant. *)


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(** * Overview *)

(** Building reliable software is really hard.  The scale and
    complexity of modern systems, the number of people involved, and
    the range of demands placed on them make it extremely difficult to
    build software that is even more-or-less correct, much less 100%%
    correct.  At the same time, the increasing degree to which
    information processing is woven into every aspect of society
    greatly amplifies the cost of bugs and insecurities.

    Computer scientists and software engineers have responded to these
    challenges by developing a whole host of techniques for improving
    software reliability, ranging from recommendations about managing
    software projects teams (e.g., extreme programming) to design
    philosophies for libraries (e.g., model-view-controller,
    publish-subscribe, etc.) and programming languages (e.g.,
    object-oriented programming, aspect-oriented programming,
    functional programming, ...) to mathematical techniques for
    specifying and reasoning about properties of software and tools
    for helping validate these properties.  The _Software Foundations_
    series is focused on this last set of techniques.

    The text is constructed around three conceptual threads:

    (1) basic tools from _logic_ for making and justifying precise
        claims about programs;

    (2) the use of _proof assistants_ to construct rigorous logical
        arguments;

    (3) _functional programming_, both as a method of programming that
        simplifies reasoning about programs and as a bridge between
        programming and logic.

    Some suggestions for further reading can be found in the
    [Postscript] chapter.  Bibliographic information for all
    cited works can be found in the file [Bib]. *)

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(** ** Logic *)

(** Logic is the field of study whose subject matter is _proofs_ --
    unassailable arguments for the truth of particular propositions.
    Volumes have been written about the central role of logic in
    computer science.  Manna and Waldinger called it "the calculus of
    computer science," while Halpern et al.'s paper _On the Unusual
    Effectiveness of Logic in Computer Science_ catalogs scores of
    ways in which logic offers critical tools and insights.  Indeed,
    they observe that, "As a matter of fact, logic has turned out to
    be significiantly more effective in computer science than it has
    been in mathematics.  This is quite remarkable, especially since
    much of the impetus for the development of logic during the past
    one hundred years came from mathematics."

    In particular, the fundamental tools of _inductive proof_ are
    ubiquitous in all of computer science.  You have surely seen them
    before, perhaps in a course on discrete math or analysis of
    algorithms, but in this course we will examine them more deeply
    than you have probably done so far. *)

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(** ** Proof Assistants *)

(** The flow of ideas between logic and computer science has not been
    unidirectional: CS has also made important contributions to logic.
    One of these has been the development of software tools for
    helping construct proofs of logical propositions.  These tools
    fall into two broad categories:

       - _Automated theorem provers_ provide "push-button" operation:
         you give them a proposition and they return either _true_ or
         _false_ (or, sometimes, _don't know: ran out of time_).
         Although their capabilities are still limited to specific
         domains, they have matured tremendously in recent years and
         are used now in a multitude of settings.  Examples of such
         tools include SAT solvers, SMT solvers, and model checkers.

       - _Proof assistants_ are hybrid tools that automate the more
         routine aspects of building proofs while depending on human
         guidance for more difficult aspects.  Widely used proof
         assistants include Isabelle, Agda, Twelf, ACL2, PVS, and Coq,
         among many others.

    This course is based around Coq, a proof assistant that has been
    under development since 1983 and that in recent years has
    attracted a large community of users in both research and
    industry.  Coq provides a rich environment for interactive
    development of machine-checked formal reasoning.  The kernel of
    the Coq system is a simple proof-checker, which guarantees that
    only correct deduction steps are ever performed.  On top of this
    kernel, the Coq environment provides high-level facilities for
    proof development, including a large library of common definitions
    and lemmas, powerful tactics for constructing complex proofs
    semi-automatically, and a special-purpose programming language for
    defining new proof-automation tactics for specific situations.

    Coq has been a critical enabler for a huge variety of work across
    computer science and mathematics:

    - As a _platform for modeling programming languages_, it has
      become a standard tool for researchers who need to describe and
      reason about complex language definitions.  It has been used,
      for example, to check the security of the JavaCard platform,
      obtaining the highest level of common criteria certification,
      and for formal specifications of the x86 and LLVM instruction
      sets and programming languages such as C.

    - As an _environment for developing formally certified software
      and hardware_, Coq has been used, for example, to build
      CompCert, a fully-verified optimizing compiler for C, and
      CertiKos, a fully verified hypervisor, for proving the
      correctness of subtle algorithms involving floating point
      numbers, and as the basis for CertiCrypt, an environment for
      reasoning about the security of cryptographic algorithms.  It is
      also being used to build verified implementations of the
      open-source RISC-V processor.

    - As a _realistic environment for functional programming with
      dependent types_, it has inspired numerous innovations.  For
      example, the Ynot system embeds "relational Hoare reasoning" (an
      extension of the _Hoare Logic_ we will see later in this course)
      in Coq.

    - As a _proof assistant for higher-order logic_, it has been used
      to validate a number of important results in mathematics.  For
      example, its ability to include complex computations inside
      proofs made it possible to develop the first formally verified
      proof of the 4-color theorem.  This proof had previously been
      controversial among mathematicians because part of it included
      checking a large number of configurations using a program. In
      the Coq formalization, everything is checked, including the
      correctness of the computational part.  More recently, an even
      more massive effort led to a Coq formalization of the
      Feit-Thompson Theorem -- the first major step in the
      classification of finite simple groups.

   By the way, in case you're wondering about the name, here's what
   the official Coq web site at INRIA (the French national research
   lab where Coq has mostly been developed) says about it: "Some
   French computer scientists have a tradition of naming their
   software as animal species: Caml, Elan, Foc or Phox are examples of
   this tacit convention. In French, 'coq' means rooster, and it
   sounds like the initials of the Calculus of Constructions (CoC) on
   which it is based."  The rooster is also the national symbol of
   France, and C-o-q are the first three letters of the name of
   Thierry Coquand, one of Coq's early developers. *)

(* ================================================================= *)
(** ** Functional Programming *)

(** The term _functional programming_ refers both to a collection of
    programming idioms that can be used in almost any programming
    language and to a family of programming languages designed to
    emphasize these idioms, including Haskell, OCaml, Standard ML,
    F##, Scala, Scheme, Racket, Common Lisp, Clojure, Erlang, and Coq.

    Functional programming has been developed over many decades --
    indeed, its roots go back to Church's lambda-calculus, which was
    invented in the 1930s, well before the first computers (at least
    the first electronic ones)!  But since the early '90s it has
    enjoyed a surge of interest among industrial engineers and
    language designers, playing a key role in high-value systems at
    companies like Jane St. Capital, Microsoft, Facebook, and
    Ericsson.

    The most basic tenet of functional programming is that, as much as
    possible, computation should be _pure_, in the sense that the only
    effect of execution should be to produce a result: it should be
    free from _side effects_ such as I/O, assignments to mutable
    variables, redirecting pointers, etc.  For example, whereas an
    _imperative_ sorting function might take a list of numbers and
    rearrange its pointers to put the list in order, a pure sorting
    function would take the original list and return a _new_ list
    containing the same numbers in sorted order.

    A significant benefit of this style of programming is that it
    makes programs easier to understand and reason about.  If every
    operation on a data structure yields a new data structure, leaving
    the old one intact, then there is no need to worry about how that
    structure is being shared and whether a change by one part of the
    program might break an invariant that another part of the program
    relies on.  These considerations are particularly critical in
    concurrent systems, where every piece of mutable state that is
    shared between threads is a potential source of pernicious bugs.
    Indeed, a large part of the recent interest in functional
    programming in industry is due to its simpler behavior in the
    presence of concurrency.

    Another reason for the current excitement about functional
    programming is related to the first: functional programs are often
    much easier to parallelize than their imperative counterparts.  If
    running a computation has no effect other than producing a result,
    then it does not matter _where_ it is run.  Similarly, if a data
    structure is never modified destructively, then it can be copied
    freely, across cores or across the network.  Indeed, the
    "Map-Reduce" idiom, which lies at the heart of massively
    distributed query processors like Hadoop and is used by Google to
    index the entire web is a classic example of functional
    programming.

    For purposes of this course, functional programming has yet
    another significant attraction: it serves as a bridge between
    logic and computer science.  Indeed, Coq itself can be viewed as a
    combination of a small but extremely expressive functional
    programming language plus a set of tools for stating and proving
    logical assertions.  Moreover, when we come to look more closely,
    we find that these two sides of Coq are actually aspects of the
    very same underlying machinery -- i.e., _proofs are programs_.  *)


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(** ** Further Reading *)

(** This text is intended to be self contained, but readers looking
    for a deeper treatment of particular topics will find some
    suggestions for further reading in the [Postscript]
    chapter. *)

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(** * Practicalities *)

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(** ** Chapter Dependencies *)

(** A diagram of the dependencies between chapters and some suggested
    paths through the material can be found in the file [deps.html]. *)

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(** ** System Requirements *)

(** Coq runs on Windows, Linux, and macOS.  You will need:

       - A current installation of Coq, available from the Coq home
         page.  These files have been tested with Coq 8.7.1.

       - An IDE for interacting with Coq.  Currently, there are two
         choices:

           - Proof General is an Emacs-based IDE.  It tends to be
             preferred by users who are already comfortable with
             Emacs.  It requires a separate installation (google
             "Proof General").

             Adventurous users of Coq within Emacs may also want to
             check out extensions such as [company-coq] and
             [control-lock].

           - CoqIDE is a simpler stand-alone IDE.  It is distributed
             with Coq, so it should be available once you have Coq
             installed.  It can also be compiled from scratch, but on
             some platforms this may involve installing additional
             packages for GUI libraries and such. *)

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(** ** Exercises *)

(** Each chapter includes numerous exercises.  Each is marked with a
    "star rating," which can be interpreted as follows:

       - One star: easy exercises that underscore points in the text
         and that, for most readers, should take only a minute or two.
         Get in the habit of working these as you reach them.

       - Two stars: straightforward exercises (five or ten minutes).

       - Three stars: exercises requiring a bit of thought (ten
         minutes to half an hour).

       - Four and five stars: more difficult exercises (half an hour
         and up).

    Also, some exercises are marked "advanced," and some are marked
    "optional."  Doing just the non-optional, non-advanced exercises
    should provide good coverage of the core material.  Optional
    exercises provide a bit of extra practice with key concepts and
    introduce secondary themes that may be of interest to some
    readers.  Advanced exercises are for readers who want an extra
    challenge and a deeper cut at the material.

    _Please do not post solutions to the exercises in a public place_. 
    Software Foundations is widely used both for self-study and for
    university courses.  Having solutions easily available makes it
    much less useful for courses, which typically have graded homework
    assignments.  We especially request that readers not post
    solutions to the exercises anyplace where they can be found by
    search engines. *)

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(** ** Downloading the Coq Files *)

(** A tar file containing the full sources for the "release version"
    of this book (as a collection of Coq scripts and HTML files) is
    available at http://www.cis.upenn.edu/~bcpierce/sf.

    (If you are using the book as part of a class, your professor may
    give you access to a locally modified version of the files, which
    you should use instead of the release version.) *)

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(** ** Lecture Videos *)

(** Lectures for an intensive summer course based on _Logical
    Foundations_ (part of the DeepSpec summer school in 2017) can be
    found at https://deepspec.org/event/dsss17/coq_intensive.html.
    The video quality is poor at the beginning but gets better in the
    later lectures. *)

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(** * Note for Instructors *)

(** If you plan to use these materials in your own course, you will
    undoubtedly find things you'd like to change, improve, or add.
    Your contributions are welcome!

    In order to keep the legalities simple and to have a single
    point of responsibility in case the need should ever arise to
    adjust the license terms, sublicense, etc., we ask all
    contributors (i.e., everyone with access to the developers'
    repository) to assign copyright in their contributions to the
    appropriate "author of record," as follows:

      - I hereby assign copyright in my past and future contributions
        to the Software Foundations project to the Author of Record of
        each volume or component, to be licensed under the same terms
        as the rest of Software Foundations.  I understand that, at
        present, the Authors of Record are as follows: For Volumes 1
        and 2, known until 2016 as "Software Foundations" and from
        2016 as (respectively) "Logical Foundations" and "Programming
        Foundations," the Author of Record is Benjamin Pierce.  For
        Volume 3, "Verified Functional Algorithms", the Author of
        Record is Andrew W. Appel. For components outside of
        designated Volumes (e.g., typesetting and grading tools and
        other software infrastructure), the Author of Record is
        Benjamin Pierce.

    To get started, please send an email to Benjamin Pierce, describing
    yourself and how you plan to use the materials and including
       (1) the above copyright transfer text and
       (2) the result of doing "htpasswd -s -n NAME"
    where NAME is your preferred user name.

    We'll set you up with access to the subversion repository and
    developers' mailing lists.  In the repository you'll find a
    file [INSTRUCTORS] with further instructions. *)

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(** * Translations *)

(** Thanks to the efforts of a team of volunteer translators,
    _Software Foundations_ can be enjoyed in Japanese at
    http://proofcafe.org/sf.  A Chinese translation is also underway;
    you can preview it at https://coq-zh.github.io/SF-zh/. *)

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(** * Thanks *)

(** Development of the _Software Foundations_ series has been
    supported, in part, by the National Science Foundation under the
    NSF Expeditions grant 1521523, _The Science of Deep
    Specification_. *)