Harmonizing Classes, Functions, Tuples, and Type Parameters in Virgil III
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Assignment 6: Subtyping and Bidirectional Typing
Assignment 6: Subtyping and Bidirectional Typing 15-312: Foundations of Programming Languages Joshua Dunfield ([email protected]) Out: Thursday, October 24, 2002 Due: Thursday, November 7 (11:59:59 pm) 100 points total + (up to) 20 points extra credit 1 Introduction In this assignment, you will implement a bidirectional typechecker for MinML with , , +, 1, 0, , , and subtyping with base types int and float. ! ∗ 8 9 Note: In the .sml files, most changes from Assignment 4 are indicated like this: (* new asst6 code: *) ... (* end asst6 code *) 2 New in this assignment Some things have become obsolete (and have either been removed or left • in a semi-supported state). Exceptions and continuations are no longer “officially” supported. One can now (and sometimes must!) write type annotations e : τ. The • abstract syntax constructor is called Anno. The lexer supports shell-style comments in .mml source files: any line • beginning with # is ignored. There are now two valid syntaxes for functions, the old syntax fun f (x:t1):t2 is e end • and a new syntax fun f(x) is e end. Note the lack of type anno- tations. The definition of the abstract syntax constructor Fun has been changed; its arguments are now just bindings for f and x and the body. It no longer takes two types. 1 The old syntax fun f(x:t1):t2 is e end is now just syntactic sugar, transformed by the parser into fun f(x) is e end : t1 -> t2. There are floating point numbers, written as in SML. There is a new set of • arithmetic operators +., -., *., ˜. -
G22.2110-003 Programming Languages - Fall 2012 Week 14 - Part 1
G22.2110-003 Programming Languages - Fall 2012 Week 14 - Part 1 Thomas Wies New York University Review Last lecture I Exceptions Outline Today: I Generic Programming Sources for today's lecture: I PLP, ch. 8.4 I Programming in Scala, ch. 19, 20.6 Generic programming Subroutines provide a way to abstract over values. Generic programming lets us abstract over types. Examples: I A sorting algorithm has the same structure, regardless of the types being sorted I Stack primitives have the same semantics, regardless of the objects stored on the stack. One common use: I algorithms on containers: updating, iteration, search Language models: I C: macros (textual substitution) or unsafe casts I Ada: generic units and instantiations I C++, Java, C#, Scala: generics (also called templates) I ML: parametric polymorphism, functors Parameterizing software components Construct Parameter(s): array bounds, element type subprogram values (arguments) Ada generic package values, types, packages Ada generic subprogram values, types C++ class template values, types C++ function template values, types Java generic classes Scala generic types (and implicit values) ML function values (including other functions) ML type constructor types ML functor values, types, structures Templates in C++ template <typename T> class Array { public : explicit Array (size_t); // constructor T& operator[] (size_t); // subscript operator ... // other operations private : ... // a size and a pointer to an array }; Array<int> V1(100); // instantiation Array<int> V2; // use default constructor -
Advanced-Java.Pdf
Advanced java i Advanced java Advanced java ii Contents 1 How to create and destroy objects 1 1.1 Introduction......................................................1 1.2 Instance Construction.................................................1 1.2.1 Implicit (Generated) Constructor.......................................1 1.2.2 Constructors without Arguments.......................................1 1.2.3 Constructors with Arguments........................................2 1.2.4 Initialization Blocks.............................................2 1.2.5 Construction guarantee............................................3 1.2.6 Visibility...................................................4 1.2.7 Garbage collection..............................................4 1.2.8 Finalizers...................................................5 1.3 Static initialization..................................................5 1.4 Construction Patterns.................................................5 1.4.1 Singleton...................................................6 1.4.2 Utility/Helper Class.............................................7 1.4.3 Factory....................................................7 1.4.4 Dependency Injection............................................8 1.5 Download the Source Code..............................................9 1.6 What’s next......................................................9 2 Using methods common to all objects 10 2.1 Introduction...................................................... 10 2.2 Methods equals and hashCode........................................... -
(901133) Instructor: Eng
home Al-Albayt University Computer Science Department C++ Programming 1 (901133) Instructor: Eng. Rami Jaradat [email protected] 1 home Subjects 1. Introduction to C++ Programming 2. Control Structures 3. Functions 4. Arrays 5. Pointers 6. Strings 2 home 1 - Introduction to C++ Programming 3 home What is computer? • Computers are programmable devices capable of performing computations and making logical decisions. • Computers can store, retrieve, and process data according to a list of instructions • Hardware is the physical part of the compute: keyboard, screen, mouse, disks, memory, and processing units • Software is a collection of computer programs, procedures and documentation that perform some tasks on a computer system 4 home Computer Logical Units • Input unit – obtains information (data) from input devices • Output unit – outputs information to output device or to control other devices. • Memory unit – Rapid access, low capacity, stores information • Secondary storage unit – cheap, long-term, high-capacity storage, stores inactive programs • Arithmetic and logic unit (ALU) – performs arithmetic calculations and logic decisions • Central processing unit (CPU): – supervises and coordinates the other sections of the computer 5 home Computer language • Machine languages: machine dependent, it consists of strings of numbers giving machine specific instructions: +1300042774 +1400593419 +1200274027 • Assembly languages: English-like abbreviations representing elementary operations, assemblers convert assembly language to machine -
Java Generics Adoption: How New Features Are Introduced, Championed, Or Ignored
Java Generics Adoption: How New Features are Introduced, Championed, or Ignored Chris Parnin Christian Bird Emerson Murphy-Hill College of Computing Microsoft Research Dept. of Computer Science Georgia Institute of Redmond, Washington North Carolina State Technology [email protected] University Atlanta, Georgia Raleigh, North Carolina [email protected] [email protected] Far too often, greatly heralded claims and visions of new language features fail to hold or persist in practice. Discus- ABSTRACT sions of the costs and benefits of language features can easily devolve into a religious war with both sides armed with little Support for generic programming was added to the Java more than anecdotes [13]. Empirical evidence about the language in 2004, representing perhaps the most significant adoption and use of past language features should inform change to one of the most widely used programming lan- and encourage a more rational discussion when designing guages today. Researchers and language designers antici- language features and considering how they should be de- pated this addition would relieve many long-standing prob- ployed. Collecting this evidence is not just sensible but a lems plaguing developers, but surprisingly, no one has yet responsibility of our community. measured whether generics actually provide such relief. In In this paper, we examine the adoption and use of generics, this paper, we report on the first empirical investigation into which were introduced into the Java language in 2004. When how Java generics have been integrated into open source Sun introduced generics, they claimed that the language software by automatically mining the history of 20 popular feature was \a long-awaited enhancement to the type system" open source Java programs, traversing more than 500 million that \eliminates the drudgery of casting." Sun recommended lines of code in the process. -
Explicitly Implicifying Explicit Constructors
Explicitly Implicifying explicit Constructors Document number: P1163R0 Date: 2018-08-31 Project: Programming Language C++, Library Working Group Reply-to: Nevin “☺” Liber, [email protected] or [email protected] Table of Contents Revision History ................................................................................................................ 3 P11630R0 .................................................................................................................................... 3 Introduction ....................................................................................................................... 4 Motivation and Scope ....................................................................................................... 5 Impact On the Standard ................................................................................................... 6 Policy .................................................................................................................................. 7 Design Decisions ................................................................................................................ 8 Technical Specifications ................................................................................................... 9 [template.bitset]........................................................................................................................ 10 [bitset.cons] .............................................................................................................................. -
Addressing Common Crosscutting Problems with Arcum∗
Addressing Common Crosscutting Problems with Arcum∗ Macneil Shonle William G. Griswold Sorin Lerner Computer Science & Engineering, UC San Diego La Jolla, CA 92093-0404 {mshonle, wgg, lerner}@cs.ucsd.edu ABSTRACT 1. INTRODUCTION Crosscutting is an inherent part of software development and can Arcum is a framework for declaring and performing user-defined typically be managed through modularization: A module’s stable program checks and transformations, with the goal of increasing properties are defined in an interface while its likely-to-change automated refactoring opportunities for the user [21]. By using Ar- properties are encapsulated within the module [19]. The cross- cum, a programmer can view the implementation of a crosscutting cutting of the stable properties, such as class and method names, design idiom as a form of module. Arcum uses a declarative lan- can be mitigated with automated refactoring tools that allow, for guage to describe the idiom’s implementation, where descriptions example, the interface’s elements to be renamed [9, 18]. However, are composed of Arcum interface and Arcum option constructs. An often the crosscutting from design idioms (such as design patterns option describes one possible implementation of a crosscutting de- and coding styles) are so specific to the program’s domain that sign idiom, and a set of options are related to each other when they their crosscutting would not likely have been anticipated by the all implement the same Arcum interface. developers of an automated refactoring system. Arcum’s declarative language uses a Java-like syntax for first- The Arcum plug-in for Eclipse enables programmers to describe order logic predicate statements, including a special pattern nota- the implementation of a crosscutting design idiom as a set of syn- tion for expressing Java code. -
The Cool Reference Manual∗
The Cool Reference Manual∗ Contents 1 Introduction 3 2 Getting Started 3 3 Classes 4 3.1 Features . 4 3.2 Inheritance . 5 4 Types 6 4.1 SELF TYPE ........................................... 6 4.2 Type Checking . 7 5 Attributes 8 5.1 Void................................................ 8 6 Methods 8 7 Expressions 9 7.1 Constants . 9 7.2 Identifiers . 9 7.3 Assignment . 9 7.4 Dispatch . 10 7.5 Conditionals . 10 7.6 Loops . 11 7.7 Blocks . 11 7.8 Let . 11 7.9 Case . 12 7.10 New . 12 7.11 Isvoid . 12 7.12 Arithmetic and Comparison Operations . 13 ∗Copyright c 1995-2000 by Alex Aiken. All rights reserved. 1 8 Basic Classes 13 8.1 Object . 13 8.2 IO ................................................. 13 8.3 Int................................................. 14 8.4 String . 14 8.5 Bool . 14 9 Main Class 14 10 Lexical Structure 14 10.1 Integers, Identifiers, and Special Notation . 15 10.2 Strings . 15 10.3 Comments . 15 10.4 Keywords . 15 10.5 White Space . 15 11 Cool Syntax 17 11.1 Precedence . 17 12 Type Rules 17 12.1 Type Environments . 17 12.2 Type Checking Rules . 18 13 Operational Semantics 22 13.1 Environment and the Store . 22 13.2 Syntax for Cool Objects . 24 13.3 Class definitions . 24 13.4 Operational Rules . 25 14 Acknowledgements 30 2 1 Introduction This manual describes the programming language Cool: the Classroom Object-Oriented Language. Cool is a small language that can be implemented with reasonable effort in a one semester course. Still, Cool retains many of the features of modern programming languages including objects, static typing, and automatic memory management. -
Generic Immutability and Nullity Types for an Imperative Object-Oriented Programming Language with flexible Initialization
Generic Immutability and Nullity Types for an imperative object-oriented programming language with flexible initialization James Elford June 21, 2012 Abstract We present a type system for parametric object mutability and ref- erence nullity in an imperative object oriented language. We present a simple but powerful system for generic nullity constraints, and build on previous work to provide safe initialization of objects which is not bound to constructors. The system is expressive enough to handle initialization of cyclic immutable data structures, and to enforce their cyclic nature through the type system. We provide the crucial parts of soundness ar- guments (though the full proof is not yet complete). Our arguments are novel, in that they do not require auxiliary runtime constructs (ghost state) in order to express or demonstrate our desired properties. 2 Contents 1 Introduction 4 1.1 In this document . .5 2 Background 6 2.1 Parametric Types . .6 2.1.1 Static Polymorphism through Templates . .7 2.1.2 Static Polymorphism through Generic Types . 12 2.2 Immutability . 18 2.2.1 Immutability in C++ .................... 19 2.2.2 Immutability in Java and C# ............... 21 2.2.3 An extension to Java's immutability model . 21 2.2.4 Parametric Immutability Constraints . 24 2.3 IGJ: Immutability Generic Java .................. 25 2.4 Nullity . 27 2.5 Areas of commonality . 30 3 Goals 32 4 Existing systems in more detail 34 4.1 The initialization problem . 34 4.2 What do we require from initialization? . 35 4.3 Approaches to initialization . 37 4.4 Delay Types and initialization using stack-local regions . -
REVERSE GENERICS Parametrization After the Fact
REVERSE GENERICS Parametrization after the Fact Alexandre Bergel PLEIAD Laboratory, Computer Science Department (DCC), University of Chile, Santiago, Chile Lorenzo Bettini Dipartimento di Informatica, Universit`adi Torino, Italy Keywords: Generic programming, Java generics, C++ templates. Abstract: By abstracting over types, generic programming enables one to write code that is independent from specific data type implementation. This style is supported by most mainstream languages, including C++ with tem- plates and Java with generics. If some code is not designed in a generic way from the start, a major effort is required to convert this code to use generic types. This conversion is manually realized which is known to be tedious and error-prone. We propose Reverse Generics, a general linguistic mechanism to define a generic class from a non-generic class. For a given set of types, a generic is formed by unbinding static dependencies contained in these types. This generalization and generic type instantiation may be done incrementally. This paper studies the possible application of this linguistic mechanism to C++ and Java and, in particular, it reviews limitations of Java generics against our proposal. 1 INTRODUCTION more than 100 down-casts and up-casts and 70 uses of instanceof. This examination reveals that in many The concept of generic programming (Dos Reis and places the amount of up-casting subsequent down- J¨arvi, 2005), which has characterized functional pro- casting that is used almost makes the programs be- gramming for several decades, appeared in main- have like dynamically typed code. stream programming object-oriented languages such Note, that the need to make existing code generic as C++, only in the late 80s, where it motivated from may arise also in languages where generic types were the beginning the design of the Standard Template Li- already available. -
C DEFINES and C++ TEMPLATES Professor Ken Birman
Professor Ken Birman C DEFINES AND C++ TEMPLATES CS4414 Lecture 10 CORNELL CS4414 - FALL 2020. 1 COMPILE TIME “COMPUTING” In lecture 9 we learned about const, constexpr and saw that C++ really depends heavily on these Ken’s solution to homework 2 runs about 10% faster with extensive use of these annotations Constexpr underlies the “auto” keyword and can sometimes eliminate entire functions by precomputing their results at compile time. Parallel C++ code would look ugly without normal code structuring. Const and constexpr allow the compiler to see “beyond” that and recognize parallelizable code paths. CORNELL CS4414 - FALL 2020. 2 … BUT HOW FAR CAN WE TAKE THIS IDEA? Today we will look at the concept of programming the compiler using the templating layer of C++ We will see that it is a powerful tool! There are also programmable aspects of Linux, and of the modern hardware we use. By controlling the whole system, we gain speed and predictability while writing elegant, clean code. CORNELL CS4414 - FALL 2020. 3 IDEA MAP FOR TODAY History of generics: #define in C Templates are easy to create, if you stick to basics The big benefit compared to Java is that a template We have seen a number of parameterized is a compile-time construct, whereas in Java a generic types in C++, like std::vector and std::map is a run-time construct. The template language is Turing-complete, but computes These are examples of “templates”. only on types, not data from the program (even when They are like generics in Java constants are provided). -
Class Notes on Type Inference 2018 Edition Chuck Liang Hofstra University Computer Science
Class Notes on Type Inference 2018 edition Chuck Liang Hofstra University Computer Science Background and Introduction Many modern programming languages that are designed for applications programming im- pose typing disciplines on the construction of programs. In constrast to untyped languages such as Scheme/Perl/Python/JS, etc, and weakly typed languages such as C, a strongly typed language (C#/Java, Ada, F#, etc ...) place constraints on how programs can be written. A type system ensures that programs observe logical structure. The origins of type theory stretches back to the early twentieth century in the work of Bertrand Russell and Alfred N. Whitehead and their \Principia Mathematica." They observed that our language, if not restrained, can lead to unsolvable paradoxes. Specifically, let's say a mathematician defined S to be the set of all sets that do not contain themselves. That is: S = fall A : A 62 Ag Then it is valid to ask the question does S contain itself (S 2 S?). If the answer is yes, then by definition of S, S is one of the 'A's, and thus S 62 S. But if S 62 S, then S is one of those sets that do not contain themselves, and so it must be that S 2 S! This observation is known as Russell's Paradox. In order to avoid this paradox, the language of mathematics (or any language for that matter) must be constrained so that the set S cannot be defined. This is one of many discoveries that resulted from the careful study of language, logic and meaning that formed the foundation of twentieth century analytical philosophy and abstract mathematics, and also that of computer science.