Computational Duality and the Sequent Calculus

Total Page:16

File Type:pdf, Size:1020Kb

Computational Duality and the Sequent Calculus Computational duality and the sequent calculus Paul Downen University of Oregon [email protected] Abstract totally different form, yet the two are still strongly related through The correspondence between proving theorems and writing pro- their mutual opposition. Duality appears in proof theory: “true” grams, known as the Curry-Howard isomorphism or the proofs-as- and “false” are dual, “and” and “or” are dual. Duality appears in programs paradigm, has spurred the development of new tools like category theory: the opposite of a category is found by reversing its proof assistants, new fields like certified programming, and new ad- arrows, sums naturally arise as the dual of products. However, even vanced type features like dependent types. The isomorphism gives though the theory of programming languages is closely connected us a correspondence between Gentzen’s natural deduction, a system to logic and categories, this kind of duality does not appear to for formalizing common mathematical reasoning, and Church’s λ- arise so readily in the practice of programming. For example, sum calculus, one of the first models of computation and the foundation types (disjoint unions) and pair types (structures) are related to for functional programming languages. However, concepts found dual concepts in logic and category theory. But in the realm of in modern programming, such as the provision of computational programming languages, the duality between these two concepts effects, combination of different programming paradigms and eval- is not readily apparent, and languages typically present the two as uation strategies, and definition of infinite objects still lack a strong unrelated features and often with different levels of expressiveness. foundation. The situation is even worse for more complicated language fea- In the hopes of gaining a better understanding of these issues, tures, where we have two concepts connected by duality that are we will look at an alternate form of logic, called the sequent calcu- both important in the theory and practice of programming, but lus, through the Curry-Howard lens. Doing so leads us to a method one is well understood while the other is enigmatic and under- of computation that heavily emphasizes the concept of duality and developed. In the case of recursion and looping, inductive data types (like lists and trees of arbitrary, but finite, size) are known the interaction between opposites — production interacts with con- 1 sumption; construction interacts with deconstruction. The symme- to be dual to co-inductive infinite processes (like streams of input try of this framework naturally explains more complicated features or servers that are indefinitely available) [58]. However, whereas of programming languages through relatively familiar concepts — the programming languages behind proof assistants like Coq [67] binding a value to a variable is dual to manipulation over the flow of have a sophisticated notion of induction, a lack of understanding control in a program; case analysis over data structures in the func- about the computational foundations of co-induction is problem- tional paradigm is dual to dynamic dispatch in the object-oriented atic. McBride [107] notes how the poor foundation for the compu- paradigm. tational interpretation of co-induction is a road block for the goal In this report, we survey the background of the connections be- of program verification and correctness: tween proofs and programs along with more modern advances. We We are obsessed with foundations partly because we are begin by reviewing the traditional form of the Curry-Howard iso- aware of a number of significant foundational problems that morphism that connect proof theory, category theory, and type the- we’ve got to get right before we can do anything realis- ory, and has roots in the beginnings of computer science. We intro- tic. The thing I would think of in particular in that respect duce the sequent calculus as an alternative form of logic, and show is co-induction and reasoning about co-recursive processes. how the Curry-Howard isomorphism still applies and presents a That’s currently, in all major implementations of type the- different basis for expressing computation. We then show how the ory, a disaster. And if we’re going to talk about real systems, fundamental dilemma in the sequent calculus gives rise to a dual- we’ve got to actually have something sensible to say about ity between evaluation strategies: strict languages are dual to lazy that. languages. Next, we discuss concepts that were developed in the setting of proof search, polarization and focalization, which give Not only is this mismatch between the foundations of the two a foundation for data structures and pattern matching in program- features aesthetically unpleasing, but it has real consequences on ming languages. Taking a step back, we give a retrospective look at the application of theory for solving practical problems. Perhaps the history of these developments, and illustrate a generalized the- the reason for this disparity and disconnect between related features ory that unifies the different systems for the sequent calculus and is a symptom of the fact that they are not considered with the right more closely matches actual programming languages. Finally, we frame of mind. consider the long road ahead for using the sequent calculus as a Our main philosophy for approaching these questions is known basis for understanding programming, and discuss various future as the Curry-Howard isomorphism [25, 30, 65] or proofs-as- directions remaining in this line of work. programs paradigm. The Curry-Howard isomorphism reveals a deep and profound connection between three different fields of study — logic, category theory, and programming languages — 1. Introduction where quite literally mathematical proofs are algorithmic pro- As Alcmaeon (510BC) once said, most things come in pairs: left and right, even and odd, true and false, good and bad. Duality is a 1 In general, adding the prefix “co-” to a term or concept means “the dual of guiding force that reveals the existence of a counter entity with a that thing.” 1 2014/1/23 grams. The canonical example of the isomorphism is the corre- false. This problem, and its negative answer, prompted for a rigor- spondence between Gentzen’s natural deduction [47], a system ous definition of “effectively computable” from Church [20], Tur- for formalizing common mathematical reasoning, and Church’s ing [110], and Godel¨ [55]. Later on, a much deeper connection be- λ-calculus [19], one of the first models of computation and the tween models of computation and formalized logic was indepen- foundation for functional programming languages. However, the dently discovered many times [25, 30, 65]. The most typical form λ-calculus not an ideal setting for studying duality in computation. of this connection, now known as the Curry-Howard isomorphism, Dualities that are simple in other settings, like the De Morgan du- gives a structural isomorphism between Church’s λ-calculus [19], a als in logic or products and sums in category theory, are far from system for computing with functions, and Gentzen’s natural deduc- obvious in the λ-calculus. The problem is related to the lack of tion [47], a system for formalizing mathematical logic and reason- symmetry in natural deduction: in natural deduction all the empha- ing. Additionally, this correspondence also includes an algebraic sis is on concluding true statements and in the λ-calculus all the structure known as cartesian closed categories [77]. To illustrate emphasis is on producing results. the connection between logic, programming, and categories, we In contrast, the sequent calculus, introduced by Gentzen [47] will review the three systems and show how they reveal core con- simultaneously with natural deduction, is a system logic about du- cepts in different ways. In particular, we will see how two princi- alities. In these formal systems of logic, equal attention is given to ples important for characterizing the meaning of various structures, falsity and truth, to assumptions and conclusions, such that there which we will call β and η, arise independently in each field of is perfect symmetry. These symmetries are even more apparent in study. the related system of linear logic by Girard [51]. When interpreted as a programming language, the sequent calculus reveals hidden 2.1 Logic dualities in programming — input and output, production and con- In 1935, Gentzen [47] formalized an intuitive model of logical sumption, construction and deconstruction, structure and pattern — reasoning called natural deduction, as it aimed to symbolically and makes them a prominent part of the computational model. Fun- model the “natural” way that mathematicians reason about proofs. damentally, the sequent calculus expresses computation as an inter- A proof in natural deduction is a tree-like structure made up of action between two opposed entities: a producer which is represen- several inferences: tative of a program that creates information, and a consumer which . is representative of an environment or context that observes infor- . mation. Computation then occurs as a protocol of communication H1 H2 ::: Hn that allows a producer and consumer to speak to one another, and J as a negotiation for resolving conflicts between the two. This two- party, protocol-based style of computation lends itself to naturally where we conclude the deduction J from proofs of the premises describe a lower-level view of computation than expressed by the H1;H2;:::;H3. The conclusion J and premises Hi are all judg- λ-calculus. In particular, programs in the sequent calculus can also ments that make statement about logical propositions, such as “0 be seen as configurations of an abstract machine, in which the eval- is greater than 1.” For example, if we let A; B; C; : : : range over uation context is reified as a syntactic object that may be directly the set of propositions, then we may make the basic judgment that manipulated.
Recommended publications
  • GHC Reading Guide
    GHC Reading Guide - Exploring entrances and mental models to the source code - Takenobu T. Rev. 0.01.1 WIP NOTE: - This is not an official document by the ghc development team. - Please refer to the official documents in detail. - Don't forget “semantics”. It's very important. - This is written for ghc 9.0. Contents Introduction 1. Compiler - Compilation pipeline - Each pipeline stages - Intermediate language syntax - Call graph 2. Runtime system 3. Core libraries Appendix References Introduction Introduction Official resources are here GHC source repository : The GHC Commentary (for developers) : https://gitlab.haskell.org/ghc/ghc https://gitlab.haskell.org/ghc/ghc/-/wikis/commentary GHC Documentation (for users) : * master HEAD https://ghc.gitlab.haskell.org/ghc/doc/ * latest major release https://downloads.haskell.org/~ghc/latest/docs/html/ * version specified https://downloads.haskell.org/~ghc/9.0.1/docs/html/ The User's Guide Core Libraries GHC API Introduction The GHC = Compiler + Runtime System (RTS) + Core Libraries Haskell source (.hs) GHC compiler RuntimeSystem Core Libraries object (.o) (libHsRts.o) (GHC.Base, ...) Linker Executable binary including the RTS (* static link case) Introduction Each division is located in the GHC source tree GHC source repository : https://gitlab.haskell.org/ghc/ghc compiler/ ... compiler sources rts/ ... runtime system sources libraries/ ... core library sources ghc/ ... compiler main includes/ ... include files testsuite/ ... test suites nofib/ ... performance tests mk/ ... build system hadrian/ ... hadrian build system docs/ ... documents : : 1. Compiler 1. Compiler Compilation pipeline 1. compiler The GHC compiler Haskell language GHC compiler Assembly language (native or llvm) 1. compiler GHC compiler comprises pipeline stages GHC compiler Haskell language Parser Renamer Type checker Desugarer Core to Core Core to STG STG to Cmm Assembly language Cmm to Asm (native or llvm) 1.
    [Show full text]
  • Sequent Calculus and the Specification of Computation
    Sequent Calculus and the Specification of Computation Lecture Notes Draft: 5 September 2001 These notes are being used with lectures for CSE 597 at Penn State in Fall 2001. These notes had been prepared to accompany lectures given at the Marktoberdorf Summer School, 29 July – 10 August 1997 for a course titled “Proof Theoretic Specification of Computation”. An earlier draft was used in courses given between 27 January and 11 February 1997 at the University of Siena and between 6 and 21 March 1997 at the University of Genoa. A version of these notes was also used at Penn State for CSE 522 in Fall 2000. For the most recent version of these notes, contact the author. °c Dale Miller 321 Pond Lab Computer Science and Engineering Department The Pennsylvania State University University Park, PA 16802-6106 USA Office: +(814)865-9505 [email protected] http://www.cse.psu.edu/»dale Contents 1 Overview and Motivation 5 1.1 Roles for logic in the specification of computations . 5 1.2 Desiderata for declarative programming . 6 1.3 Relating algorithm and logic . 6 2 First-Order Logic 8 2.1 Types and signatures . 8 2.2 First-order terms and formulas . 8 2.3 Sequent calculus . 10 2.4 Classical, intuitionistic, and minimal logics . 10 2.5 Permutations of inference rules . 12 2.6 Cut-elimination . 12 2.7 Consequences of cut-elimination . 13 2.8 Additional readings . 13 2.9 Exercises . 13 3 Logic Programming Considered Abstractly 15 3.1 Problems with proof search . 15 3.2 Interpretation as goal-directed search .
    [Show full text]
  • Chapter 1 Preliminaries
    Chapter 1 Preliminaries 1.1 First-order theories In this section we recall some basic definitions and facts about first-order theories. Most proofs are postponed to the end of the chapter, as exercises for the reader. 1.1.1 Definitions Definition 1.1 (First-order theory) —A first-order theory T is defined by: A first-order language L , whose terms (notation: t, u, etc.) and formulas (notation: φ, • ψ, etc.) are constructed from a fixed set of function symbols (notation: f , g, h, etc.) and of predicate symbols (notation: P, Q, R, etc.) using the following grammar: Terms t ::= x f (t1,..., tk) | Formulas φ, ψ ::= t1 = t2 P(t1,..., tk) φ | | > | ⊥ | ¬ φ ψ φ ψ φ ψ x φ x φ | ⇒ | ∧ | ∨ | ∀ | ∃ (assuming that each use of a function symbol f or of a predicate symbol P matches its arity). As usual, we call a constant symbol any function symbol of arity 0. A set of closed formulas of the language L , written Ax(T ), whose elements are called • the axioms of the theory T . Given a closed formula φ of the language of T , we say that φ is derivable in T —or that φ is a theorem of T —and write T φ when there are finitely many axioms φ , . , φ Ax(T ) such ` 1 n ∈ that the sequent φ , . , φ φ (or the formula φ φ φ) is derivable in a deduction 1 n ` 1 ∧ · · · ∧ n ⇒ system for classical logic. The set of all theorems of T is written Th(T ). Conventions 1.2 (1) In this course, we only work with first-order theories with equality.
    [Show full text]
  • Theorem Proving in Classical Logic
    MEng Individual Project Imperial College London Department of Computing Theorem Proving in Classical Logic Supervisor: Dr. Steffen van Bakel Author: David Davies Second Marker: Dr. Nicolas Wu June 16, 2021 Abstract It is well known that functional programming and logic are deeply intertwined. This has led to many systems capable of expressing both propositional and first order logic, that also operate as well-typed programs. What currently ties popular theorem provers together is their basis in intuitionistic logic, where one cannot prove the law of the excluded middle, ‘A A’ – that any proposition is either true or false. In classical logic this notion is provable, and the_: corresponding programs turn out to be those with control operators. In this report, we explore and expand upon the research about calculi that correspond with classical logic; and the problems that occur for those relating to first order logic. To see how these calculi behave in practice, we develop and implement functional languages for propositional and first order logic, expressing classical calculi in the setting of a theorem prover, much like Agda and Coq. In the first order language, users are able to define inductive data and record types; importantly, they are able to write computable programs that have a correspondence with classical propositions. Acknowledgements I would like to thank Steffen van Bakel, my supervisor, for his support throughout this project and helping find a topic of study based on my interests, for which I am incredibly grateful. His insight and advice have been invaluable. I would also like to thank my second marker, Nicolas Wu, for introducing me to the world of dependent types, and suggesting useful resources that have aided me greatly during this report.
    [Show full text]
  • Propositional Calculus
    CSC 438F/2404F Notes Winter, 2014 S. Cook REFERENCES The first two references have especially influenced these notes and are cited from time to time: [Buss] Samuel Buss: Chapter I: An introduction to proof theory, in Handbook of Proof Theory, Samuel Buss Ed., Elsevier, 1998, pp1-78. [B&M] John Bell and Moshe Machover: A Course in Mathematical Logic. North- Holland, 1977. Other logic texts: The first is more elementary and readable. [Enderton] Herbert Enderton: A Mathematical Introduction to Logic. Academic Press, 1972. [Mendelson] E. Mendelson: Introduction to Mathematical Logic. Wadsworth & Brooks/Cole, 1987. Computability text: [Sipser] Michael Sipser: Introduction to the Theory of Computation. PWS, 1997. [DSW] M. Davis, R. Sigal, and E. Weyuker: Computability, Complexity and Lan- guages: Fundamentals of Theoretical Computer Science. Academic Press, 1994. Propositional Calculus Throughout our treatment of formal logic it is important to distinguish between syntax and semantics. Syntax is concerned with the structure of strings of symbols (e.g. formulas and formal proofs), and rules for manipulating them, without regard to their meaning. Semantics is concerned with their meaning. 1 Syntax Formulas are certain strings of symbols as specified below. In this chapter we use formula to mean propositional formula. Later the meaning of formula will be extended to first-order formula. (Propositional) formulas are built from atoms P1;P2;P3;:::, the unary connective :, the binary connectives ^; _; and parentheses (,). (The symbols :; ^ and _ are read \not", \and" and \or", respectively.) We use P; Q; R; ::: to stand for atoms. Formulas are defined recursively as follows: Definition of Propositional Formula 1) Any atom P is a formula.
    [Show full text]
  • Focusing in Linear Meta-Logic: Extended Report Vivek Nigam, Dale Miller
    Focusing in linear meta-logic: extended report Vivek Nigam, Dale Miller To cite this version: Vivek Nigam, Dale Miller. Focusing in linear meta-logic: extended report. [Research Report] Maybe this file need a better style. Specially the proofs., 2008. inria-00281631 HAL Id: inria-00281631 https://hal.inria.fr/inria-00281631 Submitted on 24 May 2008 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Focusing in linear meta-logic: extended report Vivek Nigam and Dale Miller INRIA & LIX/Ecole´ Polytechnique, Palaiseau, France nigam at lix.polytechnique.fr dale.miller at inria.fr May 24, 2008 Abstract. It is well known how to use an intuitionistic meta-logic to specify natural deduction systems. It is also possible to use linear logic as a meta-logic for the specification of a variety of sequent calculus proof systems. Here, we show that if we adopt different focusing annotations for such linear logic specifications, a range of other proof systems can also be specified. In particular, we show that natural deduction (normal and non-normal), sequent proofs (with and without cut), tableaux, and proof systems using general elimination and general introduction rules can all be derived from essentially the same linear logic specification by altering focusing annotations.
    [Show full text]
  • On Synthetic Undecidability in Coq, with an Application to the Entscheidungsproblem
    On Synthetic Undecidability in Coq, with an Application to the Entscheidungsproblem Yannick Forster Dominik Kirst Gert Smolka Saarland University Saarland University Saarland University Saarbrücken, Germany Saarbrücken, Germany Saarbrücken, Germany [email protected] [email protected] [email protected] Abstract like decidability, enumerability, and reductions are avail- We formalise the computational undecidability of validity, able without reference to a concrete model of computation satisfiability, and provability of first-order formulas follow- such as Turing machines, general recursive functions, or ing a synthetic approach based on the computation native the λ-calculus. For instance, representing a given decision to Coq’s constructive type theory. Concretely, we consider problem by a predicate p on a type X, a function f : X ! B Tarski and Kripke semantics as well as classical and intu- with 8x: p x $ f x = tt is a decision procedure, a function itionistic natural deduction systems and provide compact д : N ! X with 8x: p x $ ¹9n: д n = xº is an enumer- many-one reductions from the Post correspondence prob- ation, and a function h : X ! Y with 8x: p x $ q ¹h xº lem (PCP). Moreover, developing a basic framework for syn- for a predicate q on a type Y is a many-one reduction from thetic computability theory in Coq, we formalise standard p to q. Working formally with concrete models instead is results concerning decidability, enumerability, and reducibil- cumbersome, given that every defined procedure needs to ity without reference to a concrete model of computation. be shown representable by a concrete entity of the model.
    [Show full text]
  • Haskell-Like S-Expression-Based Language Designed for an IDE
    Department of Computing Imperial College London MEng Individual Project Haskell-Like S-Expression-Based Language Designed for an IDE Author: Supervisor: Michal Srb Prof. Susan Eisenbach June 2015 Abstract The state of the programmers’ toolbox is abysmal. Although substantial effort is put into the development of powerful integrated development environments (IDEs), their features often lack capabilities desired by programmers and target primarily classical object oriented languages. This report documents the results of designing a modern programming language with its IDE in mind. We introduce a new statically typed functional language with strong metaprogramming capabilities, targeting JavaScript, the most popular runtime of today; and its accompanying browser-based IDE. We demonstrate the advantages resulting from designing both the language and its IDE at the same time and evaluate the resulting environment by employing it to solve a variety of nontrivial programming tasks. Our results demonstrate that programmers can greatly benefit from the combined application of modern approaches to programming tools. I would like to express my sincere gratitude to Susan, Sophia and Tristan for their invaluable feedback on this project, my family, my parents Michal and Jana and my grandmothers Hana and Jaroslava for supporting me throughout my studies, and to all my friends, especially to Harry whom I met at the interview day and seem to not be able to get rid of ever since. ii Contents Abstract i Contents iii 1 Introduction 1 1.1 Objectives ........................................ 2 1.2 Challenges ........................................ 3 1.3 Contributions ...................................... 4 2 State of the Art 6 2.1 Languages ........................................ 6 2.1.1 Haskell ....................................
    [Show full text]
  • The Sequent Calculus
    Chapter udf The Sequent Calculus This chapter presents Gentzen's standard sequent calculus LK for clas- sical first-order logic. It could use more examples and exercises. To include or exclude material relevant to the sequent calculus as a proof system, use the \prfLK" tag. seq.1 Rules and Derivations fol:seq:rul: For the following, let Γ; ∆, Π; Λ represent finite sequences of sentences. sec Definition seq.1 (Sequent). A sequent is an expression of the form Γ ) ∆ where Γ and ∆ are finite (possibly empty) sequences of sentences of the lan- guage L. Γ is called the antecedent, while ∆ is the succedent. The intuitive idea behind a sequent is: if all of the sentences in the an- explanation tecedent hold, then at least one of the sentences in the succedent holds. That is, if Γ = h'1;:::;'mi and ∆ = h 1; : : : ; ni, then Γ ) ∆ holds iff ('1 ^ · · · ^ 'm) ! ( 1 _···_ n) holds. There are two special cases: where Γ is empty and when ∆ is empty. When Γ is empty, i.e., m = 0, ) ∆ holds iff 1 _···_ n holds. When ∆ is empty, i.e., n = 0, Γ ) holds iff :('1 ^ · · · ^ 'm) does. We say a sequent is valid iff the corresponding sentence is valid. If Γ is a sequence of sentences, we write Γ; ' for the result of appending ' to the right end of Γ (and '; Γ for the result of appending ' to the left end of Γ ). If ∆ is a sequence of sentences also, then Γ; ∆ is the concatenation of the two sequences. 1 Definition seq.2 (Initial Sequent).
    [Show full text]
  • Sequent Calculus for Predicate Logic
    CHAPTER 13 Sequent calculus for predicate logic 1. Classical sequent calculus The axioms and rules of the classical sequent calculus are: Γ;' ) ∆;' for atomic ' Axioms Γ; ?) ∆ Left Right ^ Γ,α1,α2)∆ Γ)β1;∆ Γ)β2;∆ Γ,α1^α2)∆ Γ)β1^β2;∆ Γ,β1)∆ Γ,β2)∆ Γ)α1,α2;∆ _ Γ,β1_β2)∆ Γ)α1_α2;∆ ! Γ)∆,β1 Γ,β2)∆ Γ,α1)α2;∆ Γ,β1!β2)∆ Γ)α1!α2;∆ Γ;'[t=x])∆ Γ)∆;'[y=x] 8 Γ;8x ')∆ Γ)∆;8x ' Γ;'[y=x])∆ Γ)∆;'[t=x] 9 Γ;9x ')∆ Γ)∆;9x ' The side condition in 9L and 8R is that the variable y may not occur in Γ; ∆ or ' (this variable is sometimes called an eigenvariable). In addition, we have the following cut rule: Γ ) '; ∆ Γ;' ) ∆ Γ ) ∆ We outline a proof of cut elimination. First a definition: Definition 1.1. The logical depth dp(') of a formula is defined inductively as follows: the logical depth of an atomic formula is 0, while the logical depth of ' is max(dp('); dp( ))+1. Finally, the logical depth of 8x ' or 9x ' is dp(') + 1. The rank rk(') of a formula ' will be defined as dp(') + 1. If there is an application of the cut rule Γ ) '; ∆ Γ;' ) ∆ ; Γ ) ∆ then we call ' a cut formula. If π is a derivation, then we define its cut rank to be 0, if it contains no cut formulas (i.e., is cut free). If, on the other hand, it contains applications of the 1 2 13. SEQUENT CALCULUS FOR PREDICATE LOGIC cut rule, then we define the cut rank of π to be the rank of any cut formula in π which has greatest possible rank.
    [Show full text]
  • A Formal Methodology for Deriving Purely Functional Programs from Z Specifications Via the Intermediate Specification Language Funz
    Louisiana State University LSU Digital Commons LSU Historical Dissertations and Theses Graduate School 1995 A Formal Methodology for Deriving Purely Functional Programs From Z Specifications via the Intermediate Specification Language FunZ. Linda Bostwick Sherrell Louisiana State University and Agricultural & Mechanical College Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_disstheses Recommended Citation Sherrell, Linda Bostwick, "A Formal Methodology for Deriving Purely Functional Programs From Z Specifications via the Intermediate Specification Language FunZ." (1995). LSU Historical Dissertations and Theses. 5981. https://digitalcommons.lsu.edu/gradschool_disstheses/5981 This Dissertation is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Historical Dissertations and Theses by an authorized administrator of LSU Digital Commons. For more information, please contact [email protected]. INFORMATION TO USERS This manuscript has been reproduced from the microfilm master. UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of computer printer. H ie quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandardm argins, and improper alignment can adversely affect reproduction. In the unlikely, event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand comer and continuing from left to right in equal sections with small overlaps.
    [Show full text]
  • The Logic of Demand in Haskell
    Under consideration for publication in J. Functional Programming 1 The Logic of Demand in Haskell WILLIAM L. HARRISON Department of Computer Science University of Missouri Columbia, Missouri RICHARD B. KIEBURTZ Pacific Software Research Center OGI School of Science & Engineering Oregon Health & Science University Abstract Haskell is a functional programming language whose evaluation is lazy by default. However, Haskell also provides pattern matching facilities which add a modicum of eagerness to its otherwise lazy default evaluation. This mixed or “non-strict” semantics can be quite difficult to reason with. This paper introduces a programming logic, P-logic, which neatly formalizes the mixed evaluation in Haskell pattern-matching as a logic, thereby simplifying the task of specifying and verifying Haskell programs. In P-logic, aspects of demand are reflected or represented within both the predicate language and its model theory, allowing for expressive and comprehensible program verification. 1 Introduction Although Haskell is known as a lazy functional language because of its default eval- uation strategy, it contains a number of language constructs that force exceptions to that strategy. Among these features are pattern-matching, data type strictness annotations and the seq primitive. The semantics of pattern-matching are further enriched by irrefutable pattern annotations, which may be embedded within pat- terns. The interaction between Haskell’s default lazy evaluation and its pattern- matching is surprisingly complicated. Although it offers the programmer a facility for fine control of demand (Harrison et al., 2002), it is perhaps the aspect of the Haskell language least well understood by its community of users. In this paper, we characterize the control of demand first in a denotational semantics and then in a verification logic called “P-logic”.
    [Show full text]