An Extension of System F with Subtyping
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Proving Termination of Evaluation for System F with Control Operators
Proving termination of evaluation for System F with control operators Małgorzata Biernacka Dariusz Biernacki Sergue¨ıLenglet Institute of Computer Science Institute of Computer Science LORIA University of Wrocław University of Wrocław Universit´ede Lorraine [email protected] [email protected] [email protected] Marek Materzok Institute of Computer Science University of Wrocław [email protected] We present new proofs of termination of evaluation in reduction semantics (i.e., a small-step opera- tional semantics with explicit representation of evaluation contexts) for System F with control oper- ators. We introduce a modified version of Girard’s proof method based on reducibility candidates, where the reducibility predicates are defined on values and on evaluation contexts as prescribed by the reduction semantics format. We address both abortive control operators (callcc) and delimited- control operators (shift and reset) for which we introduce novel polymorphic type systems, and we consider both the call-by-value and call-by-name evaluation strategies. 1 Introduction Termination of reductions is one of the crucial properties of typed λ-calculi. When considering a λ- calculus as a deterministic programming language, one is usually interested in termination of reductions according to a given evaluation strategy, such as call by value or call by name, rather than in more general normalization properties. A convenient format to specify such strategies is reduction semantics, i.e., a form of operational semantics with explicit representation of evaluation (reduction) contexts [14], where the evaluation contexts represent continuations [10]. Reduction semantics is particularly convenient for expressing non-local control effects and has been most successfully used to express the semantics of control operators such as callcc [14], or shift and reset [5]. -
Lecture Notes on Types for Part II of the Computer Science Tripos
Q Lecture Notes on Types for Part II of the Computer Science Tripos Prof. Andrew M. Pitts University of Cambridge Computer Laboratory c 2016 A. M. Pitts Contents Learning Guide i 1 Introduction 1 2 ML Polymorphism 6 2.1 Mini-ML type system . 6 2.2 Examples of type inference, by hand . 14 2.3 Principal type schemes . 16 2.4 A type inference algorithm . 18 3 Polymorphic Reference Types 25 3.1 The problem . 25 3.2 Restoring type soundness . 30 4 Polymorphic Lambda Calculus 33 4.1 From type schemes to polymorphic types . 33 4.2 The Polymorphic Lambda Calculus (PLC) type system . 37 4.3 PLC type inference . 42 4.4 Datatypes in PLC . 43 4.5 Existential types . 50 5 Dependent Types 53 5.1 Dependent functions . 53 5.2 Pure Type Systems . 57 5.3 System Fw .............................................. 63 6 Propositions as Types 67 6.1 Intuitionistic logics . 67 6.2 Curry-Howard correspondence . 69 6.3 Calculus of Constructions, lC ................................... 73 6.4 Inductive types . 76 7 Further Topics 81 References 84 Learning Guide These notes and slides are designed to accompany 12 lectures on type systems for Part II of the Cambridge University Computer Science Tripos. The course builds on the techniques intro- duced in the Part IB course on Semantics of Programming Languages for specifying type systems for programming languages and reasoning about their properties. The emphasis here is on type systems for functional languages and their connection to constructive logic. We pay par- ticular attention to the notion of parametric polymorphism (also known as generics), both because it has proven useful in practice and because its theory is quite subtle. -
The System F of Variable Types, Fifteen Years Later
Theoretical Computer Science 45 (1986) 159-192 159 North-Holland THE SYSTEM F OF VARIABLE TYPES, FIFTEEN YEARS LATER Jean-Yves GIRARD Equipe de Logique Mathdmatique, UA 753 du CNRS, 75251 Paris Cedex 05, France Communicated by M. Nivat Received December 1985 Revised March 1986 Abstract. The semantic study of system F stumbles on the problem of variable types for which there was no convincing interpretation; we develop here a semantics based on the category-theoretic idea of direct limit, so that the behaviour of a variable type on any domain is determined by its behaviour on finite ones, thus getting rid of the circularity of variable types. To do so, one has first to simplify somehow the extant semantic ideas, replacing Scott domains by the simpler and more finitary qualitative domains. The interpretation obtained is extremely compact, as shown on simple examples. The paper also contains the definitions of a very small 'universal model' of lambda-calculus, and investigates the concept totality. Contents Introduction ................................... 159 1. Qualitative domains and A-structures ........................ 162 2. Semantics of variable types ............................ 168 3. The system F .................................. 174 3.1. The semantics of F: Discussion ........................ 177 3.2. Case of irrt ................................. 182 4. The intrinsic model of A-calculus .......................... 183 4.1. Discussion about t* ............................. 183 4.2. Final remarks ............................... -
Cross-Platform Language Design
Cross-Platform Language Design THIS IS A TEMPORARY TITLE PAGE It will be replaced for the final print by a version provided by the service academique. Thèse n. 1234 2011 présentée le 11 Juin 2018 à la Faculté Informatique et Communications Laboratoire de Méthodes de Programmation 1 programme doctoral en Informatique et Communications École Polytechnique Fédérale de Lausanne pour l’obtention du grade de Docteur ès Sciences par Sébastien Doeraene acceptée sur proposition du jury: Prof James Larus, président du jury Prof Martin Odersky, directeur de thèse Prof Edouard Bugnion, rapporteur Dr Andreas Rossberg, rapporteur Prof Peter Van Roy, rapporteur Lausanne, EPFL, 2018 It is better to repent a sin than regret the loss of a pleasure. — Oscar Wilde Acknowledgments Although there is only one name written in a large font on the front page, there are many people without which this thesis would never have happened, or would not have been quite the same. Five years is a long time, during which I had the privilege to work, discuss, sing, learn and have fun with many people. I am afraid to make a list, for I am sure I will forget some. Nevertheless, I will try my best. First, I would like to thank my advisor, Martin Odersky, for giving me the opportunity to fulfill a dream, that of being part of the design and development team of my favorite programming language. Many thanks for letting me explore the design of Scala.js in my own way, while at the same time always being there when I needed him. -
An Introduction to Logical Relations Proving Program Properties Using Logical Relations
An Introduction to Logical Relations Proving Program Properties Using Logical Relations Lau Skorstengaard [email protected] Contents 1 Introduction 2 1.1 Simply Typed Lambda Calculus (STLC) . .2 1.2 Logical Relations . .3 1.3 Categories of Logical Relations . .5 2 Normalization of the Simply Typed Lambda Calculus 5 2.1 Strong Normalization of STLC . .5 2.2 Exercises . 10 3 Type Safety for STLC 11 3.1 Type safety - the classical treatment . 11 3.2 Type safety - using logical predicate . 12 3.3 Exercises . 15 4 Universal Types and Relational Substitutions 15 4.1 System F (STLC with universal types) . 16 4.2 Contextual Equivalence . 19 4.3 A Logical Relation for System F . 20 4.4 Exercises . 28 5 Existential types 29 6 Recursive Types and Step Indexing 34 6.1 A motivating introduction to recursive types . 34 6.2 Simply typed lambda calculus extended with µ ............ 36 6.3 Step-indexing, logical relations for recursive types . 37 6.4 Exercises . 41 1 1 Introduction The term logical relations stems from Gordon Plotkin’s memorandum Lambda- definability and logical relations written in 1973. However, the spirit of the proof method can be traced back to Wiliam W. Tait who used it to show strong nor- malization of System T in 1967. Names are a curious thing. When I say “chair”, you immediately get a picture of a chair in your head. If I say “table”, then you picture a table. The reason you do this is because we denote a chair by “chair” and a table by “table”, but we might as well have said “giraffe” for chair and “Buddha” for table. -
Blossom: a Language Built to Grow
Macalester College DigitalCommons@Macalester College Mathematics, Statistics, and Computer Science Honors Projects Mathematics, Statistics, and Computer Science 4-26-2016 Blossom: A Language Built to Grow Jeffrey Lyman Macalester College Follow this and additional works at: https://digitalcommons.macalester.edu/mathcs_honors Part of the Computer Sciences Commons, Mathematics Commons, and the Statistics and Probability Commons Recommended Citation Lyman, Jeffrey, "Blossom: A Language Built to Grow" (2016). Mathematics, Statistics, and Computer Science Honors Projects. 45. https://digitalcommons.macalester.edu/mathcs_honors/45 This Honors Project - Open Access is brought to you for free and open access by the Mathematics, Statistics, and Computer Science at DigitalCommons@Macalester College. It has been accepted for inclusion in Mathematics, Statistics, and Computer Science Honors Projects by an authorized administrator of DigitalCommons@Macalester College. For more information, please contact [email protected]. In Memory of Daniel Schanus Macalester College Department of Mathematics, Statistics, and Computer Science Blossom A Language Built to Grow Jeffrey Lyman April 26, 2016 Advisor Libby Shoop Readers Paul Cantrell, Brett Jackson, Libby Shoop Contents 1 Introduction 4 1.1 Blossom . .4 2 Theoretic Basis 6 2.1 The Potential of Types . .6 2.2 Type basics . .6 2.3 Subtyping . .7 2.4 Duck Typing . .8 2.5 Hindley Milner Typing . .9 2.6 Typeclasses . 10 2.7 Type Level Operators . 11 2.8 Dependent types . 11 2.9 Hoare Types . 12 2.10 Success Types . 13 2.11 Gradual Typing . 14 2.12 Synthesis . 14 3 Language Description 16 3.1 Design goals . 16 3.2 Type System . 17 3.3 Hello World . -
Lightweight Linear Types in System F°
University of Pennsylvania ScholarlyCommons Departmental Papers (CIS) Department of Computer & Information Science 1-23-2010 Lightweight linear types in System F° Karl Mazurak University of Pennsylvania Jianzhou Zhao University of Pennsylvania Stephan A. Zdancewic University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/cis_papers Part of the Computer Sciences Commons Recommended Citation Karl Mazurak, Jianzhou Zhao, and Stephan A. Zdancewic, "Lightweight linear types in System F°", . January 2010. Karl Mazurak, Jianzhou Zhao, and Steve Zdancewic. Lightweight linear types in System Fo. In ACM SIGPLAN International Workshop on Types in Languages Design and Implementation (TLDI), pages 77-88, 2010. doi>10.1145/1708016.1708027 © ACM, 2010. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM SIGPLAN International Workshop on Types in Languages Design and Implementation, {(2010)} http://doi.acm.org/10.1145/1708016.1708027" Email [email protected] This paper is posted at ScholarlyCommons. https://repository.upenn.edu/cis_papers/591 For more information, please contact [email protected]. Lightweight linear types in System F° Abstract We present Fo, an extension of System F that uses kinds to distinguish between linear and unrestricted types, simplifying the use of linearity for general-purpose programming. We demonstrate through examples how Fo can elegantly express many useful protocols, and we prove that any protocol representable as a DFA can be encoded as an Fo type. We supply mechanized proofs of Fo's soundness and parametricity properties, along with a nonstandard operational semantics that formalizes common intuitions about linearity and aids in reasoning about protocols. -
CS 6110 S18 Lecture 32 Dependent Types 1 Typing Lists with Lengths
CS 6110 S18 Lecture 32 Dependent Types When we added kinding last time, part of the motivation was to complement the functions from types to terms that we had in System F with functions from types to types. Of course, all of these languages have plain functions from terms to terms. So it's natural to wonder what would happen if we added functions from values to types. The result is a language with \compile-time" types that can depend on \run-time" values. While this arrangement might seem paradoxical, it is a very powerful way to express the correctness of programs; and via the propositions-as-types principle, it also serves as the foundation for a modern crop of interactive theorem provers. The language feature is called dependent types (i.e., types depend on terms). Prominent dependently-typed languages include Coq, Nuprl, Agda, Lean, F*, and Idris. Some of these languages, like Coq and Nuprl, are more oriented toward proving things using propositions as types, and others, like F* and Idris, are more oriented toward writing \normal programs" with strong correctness guarantees. 1 Typing Lists with Lengths Dependent types can help avoid out-of-bounds errors by encoding the lengths of arrays as part of their type. Consider a plain recursive IList type that represents a list of any length. Using type operators, we might use a general type List that can be instantiated as List int, so its kind would be type ) type. But let's use a fixed element type for now. With dependent types, however, we can make IList a type constructor that takes a natural number as an argument, so IList n is a list of length n. -
Distributive Disjoint Polymorphism for Compositional Programming
Distributive Disjoint Polymorphism for Compositional Programming Xuan Bi1, Ningning Xie1, Bruno C. d. S. Oliveira1, and Tom Schrijvers2 1 The University of Hong Kong, Hong Kong, China fxbi,nnxie,[email protected] 2 KU Leuven, Leuven, Belgium [email protected] Abstract. Popular programming techniques such as shallow embeddings of Domain Specific Languages (DSLs), finally tagless or object algebras are built on the principle of compositionality. However, existing program- ming languages only support simple compositional designs well, and have limited support for more sophisticated ones. + This paper presents the Fi calculus, which supports highly modular and compositional designs that improve on existing techniques. These im- provements are due to the combination of three features: disjoint inter- section types with a merge operator; parametric (disjoint) polymorphism; and BCD-style distributive subtyping. The main technical challenge is + Fi 's proof of coherence. A naive adaptation of ideas used in System F's + parametricity to canonicity (the logical relation used by Fi to prove co- herence) results in an ill-founded logical relation. To solve the problem our canonicity relation employs a different technique based on immediate substitutions and a restriction to predicative instantiations. Besides co- herence, we show several other important meta-theoretical results, such as type-safety, sound and complete algorithmic subtyping, and decidabil- ity of the type system. Remarkably, unlike F<:'s bounded polymorphism, + disjoint polymorphism in Fi supports decidable type-checking. 1 Introduction Compositionality is a desirable property in programming designs. Broadly de- fined, it is the principle that a system should be built by composing smaller sub- systems. -
System F and Existential Types 15-312: Foundations of Programming Languages
Recitation 6: System F and Existential Types 15-312: Foundations of Programming Languages Serena Wang, Charles Yuan February 21, 2018 We saw how to use inductive and coinductive types last recitation. We can also add polymorphic types to our type system, which leads us to System F. With polymorphic types, we can have functions that work the same regardless of the types of some parts of the expression.1 1 System F Inductive and coinductive types expand the expressivity of T considerably. The power of type operators allows us to genericly manipulate data of heterogeneous types, building new types from old ones. But to write truly \generic" programs, we want truly polymorphic expressions| functions that operate on containers of some arbitrary type, for example. To gain this power, we add parametric polymorphism to the language, which results in System F, introduced by Girand (1972) and Reynolds (1974). Typ τ ::= t type variable τ1 ! τ2 function 8(t.τ) universal type Exp e ::= x variable λ (x : τ) e abstraction e1(e2) application Λ(t) e type abstraction e[τ] type application Take stock of what we've added since last time, and what we've removed. The familiar type variables are now baked into the language, along with the universal type. We also have a new form of lambda expression, one that works over type variables rather than expression variables. What's missing? Nearly every other construct we've come to know and love! As will be the case repeatedly in the course, our tools such as products, sums, and inductive types are subsumed by the new polymorphic types. -
Bs-6026-0512E.Pdf
THERMAL PRINTER SPEC BAS - 6026 1. Basic Features 1.) Type : PANEL Mounting or DESK top type 2.) Printing Type : THERMAL PRINT 3.) Printing Speed : 25mm / SEC 4.) Printing Column : 24 COLUMNS 5.) FONT : 24 X 24 DOT MATRIX 6.) Character : English, Numeric & Others 7.) Paper width : 57.5mm ± 0.5mm 8.) Character Size : 5times enlarge possible 9.) INTERFACE : CENTRONICS PARALLEL I/F SERIAL I/F 10.) DIMENSION : 122(W) X 90(D) X 129(H) 11.) Operating Temperature range : 0℃ - 50℃ 12.) Storage Temperature range : -20℃ - 70℃ 13.) Outlet Power : DC 12V ( 1.6 A )/ DC 5V ( 2.5 A) 14.) Application : Indicator, Scale, Factory automation equipments and any other data recording, etc.,, - 1 - 1) SERIAL INTERFACE SPECIFICATION * CONNECTOR : 25 P FEMALE PRINTER : 4 P CONNECTOR 3 ( TXD ) ----------------------- 2 ( RXD ) 2 2 ( RXD ) ----------------------- 1 ( TXD ) 3 7 ( GND ) ----------------------- 4 ( GND ) 5 DIP SWITCH BUAD RATE 1 2 3 ON ON ON 150 OFF ON ON 300 ON OFF ON 600 OFF OFF ON 1200 ON ON OFF 2400 OFF ON OFF 4800 ON OFF OFF 9600 OFF OFF OFF 19200 2) BAUD RATE SELECTION * PROTOCOL : XON / XOFF Type DIP SWITCH (4) ON : Combination type * DATA BIT : 8 BIT STOP BIT : 1 STOP BIT OFF: Complete type PARITY CHECK : NO PARITY * DEFAULT VALUE : BAUD RATE (9600 BPS) - 2 - PRINTING COMMAND * Explanation Command is composed of One Byte Control code and ESC code. This arrangement is started with ESC code which is connected by character & numeric code The control code in Printer does not be still in standardization (ESC Control Code). All printers have a code structure by themselves. -
1 Polymorphism in Ocaml 2 Type Inference
CS 4110 – Programming Languages and Logics .. Lecture #25: Type Inference . 1 Polymorphism in OCaml In languages lik OCaml, programmers don’t have to annotate their programs with 8X: τ or e [τ]. Both are automatically inferred by the compiler, although the programmer can specify types explicitly if desired. For example, we can write let double f x = f (f x) and Ocaml will gure out that the type is ('a ! 'a) ! 'a ! 'a which is roughly equivalent to 8A: (A ! A) ! A ! A We can also write double (fun x ! x+1) 7 and Ocaml will infer that the polymorphic function double is instantiated on the type int. The polymorphism in ML is not, however, exactly like the polymorphism in System F. ML restricts what types a type variable may be instantiated with. Specically, type variables can not be instantiated with polymorphic types. Also, polymorphic types are not allowed to appear on the left-hand side of arrows—i.e., a polymorphic type cannot be the type of a function argument. This form of polymorphism is known as let-polymorphism (due to the special role played by let in ML), or prenex polymorphism. These restrictions ensure that type inference is decidable. An example of a term that is typable in System F but not typable in ML is the self-application expression λx. x x. Try typing fun x ! x x in the top-level loop of Ocaml, and see what happens... 2 Type Inference In the simply-typed lambda calculus, we explicitly annotate the type of function arguments: λx:τ: e.