Java Idioms: Exception Handling
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CS 61A Streams Summer 2019 1 Streams
CS 61A Streams Summer 2019 Discussion 10: August 6, 2019 1 Streams In Python, we can use iterators to represent infinite sequences (for example, the generator for all natural numbers). However, Scheme does not support iterators. Let's see what happens when we try to use a Scheme list to represent an infinite sequence of natural numbers: scm> (define (naturals n) (cons n (naturals (+ n 1)))) naturals scm> (naturals 0) Error: maximum recursion depth exceeded Because cons is a regular procedure and both its operands must be evaluted before the pair is constructed, we cannot create an infinite sequence of integers using a Scheme list. Instead, our Scheme interpreter supports streams, which are lazy Scheme lists. The first element is represented explicitly, but the rest of the stream's elements are computed only when needed. Computing a value only when it's needed is also known as lazy evaluation. scm> (define (naturals n) (cons-stream n (naturals (+ n 1)))) naturals scm> (define nat (naturals 0)) nat scm> (car nat) 0 scm> (cdr nat) #[promise (not forced)] scm> (car (cdr-stream nat)) 1 scm> (car (cdr-stream (cdr-stream nat))) 2 We use the special form cons-stream to create a stream: (cons-stream <operand1> <operand2>) cons-stream is a special form because the second operand is not evaluated when evaluating the expression. To evaluate this expression, Scheme does the following: 1. Evaluate the first operand. 2. Construct a promise containing the second operand. 3. Return a pair containing the value of the first operand and the promise. 2 Streams To actually get the rest of the stream, we must call cdr-stream on it to force the promise to be evaluated. -
Chapter 2 Basics of Scanning And
Chapter 2 Basics of Scanning and Conventional Programming in Java In this chapter, we will introduce you to an initial set of Java features, the equivalent of which you should have seen in your CS-1 class; the separation of problem, representation, algorithm and program – four concepts you have probably seen in your CS-1 class; style rules with which you are probably familiar, and scanning - a general class of problems we see in both computer science and other fields. Each chapter is associated with an animating recorded PowerPoint presentation and a YouTube video created from the presentation. It is meant to be a transcript of the associated presentation that contains little graphics and thus can be read even on a small device. You should refer to the associated material if you feel the need for a different instruction medium. Also associated with each chapter is hyperlinked code examples presented here. References to previously presented code modules are links that can be traversed to remind you of the details. The resources for this chapter are: PowerPoint Presentation YouTube Video Code Examples Algorithms and Representation Four concepts we explicitly or implicitly encounter while programming are problems, representations, algorithms and programs. Programs, of course, are instructions executed by the computer. Problems are what we try to solve when we write programs. Usually we do not go directly from problems to programs. Two intermediate steps are creating algorithms and identifying representations. Algorithms are sequences of steps to solve problems. So are programs. Thus, all programs are algorithms but the reverse is not true. -
File I/O Stream Byte Stream
File I/O In Java, we can read data from files and also write data in files. We do this using streams. Java has many input and output streams that are used to read and write data. Same as a continuous flow of water is called water stream, in the same way input and output flow of data is called stream. Stream Java provides many input and output stream classes which are used to read and write. Streams are of two types. Byte Stream Character Stream Let's look at the two streams one by one. Byte Stream It is used in the input and output of byte. We do this with the help of different Byte stream classes. Two most commonly used Byte stream classes are FileInputStream and FileOutputStream. Some of the Byte stream classes are listed below. Byte Stream Description BufferedInputStream handles buffered input stream BufferedOutputStrea handles buffered output stream m FileInputStream used to read from a file FileOutputStream used to write to a file InputStream Abstract class that describe input stream OutputStream Abstract class that describe output stream Byte Stream Classes are in divided in two groups - InputStream Classes - These classes are subclasses of an abstract class, InputStream and they are used to read bytes from a source(file, memory or console). OutputStream Classes - These classes are subclasses of an abstract class, OutputStream and they are used to write bytes to a destination(file, memory or console). InputStream InputStream class is a base class of all the classes that are used to read bytes from a file, memory or console. -
Metaclasses: Generative C++
Metaclasses: Generative C++ Document Number: P0707 R3 Date: 2018-02-11 Reply-to: Herb Sutter ([email protected]) Audience: SG7, EWG Contents 1 Overview .............................................................................................................................................................2 2 Language: Metaclasses .......................................................................................................................................7 3 Library: Example metaclasses .......................................................................................................................... 18 4 Applying metaclasses: Qt moc and C++/WinRT .............................................................................................. 35 5 Alternatives for sourcedefinition transform syntax .................................................................................... 41 6 Alternatives for applying the transform .......................................................................................................... 43 7 FAQs ................................................................................................................................................................. 46 8 Revision history ............................................................................................................................................... 51 Major changes in R3: Switched to function-style declaration syntax per SG7 direction in Albuquerque (old: $class M new: constexpr void M(meta::type target, -
C++ Input/Output: Streams 4
C++ Input/Output: Streams 4. Input/Output 1 The basic data type for I/O in C++ is the stream. C++ incorporates a complex hierarchy of stream types. The most basic stream types are the standard input/output streams: istream cin built-in input stream variable; by default hooked to keyboard ostream cout built-in output stream variable; by default hooked to console header file: <iostream> C++ also supports all the input/output mechanisms that the C language included. However, C++ streams provide all the input/output capabilities of C, with substantial improvements. We will exclusively use streams for input and output of data. Computer Science Dept Va Tech August, 2001 Intro Programming in C++ ©1995-2001 Barnette ND & McQuain WD C++ Streams are Objects 4. Input/Output 2 The input and output streams, cin and cout are actually C++ objects. Briefly: class: a C++ construct that allows a collection of variables, constants, and functions to be grouped together logically under a single name object: a variable of a type that is a class (also often called an instance of the class) For example, istream is actually a type name for a class. cin is the name of a variable of type istream. So, we would say that cin is an instance or an object of the class istream. An instance of a class will usually have a number of associated functions (called member functions) that you can use to perform operations on that object or to obtain information about it. The following slides will present a few of the basic stream member functions, and show how to go about using member functions. -
Subtyping, Declaratively an Exercise in Mixed Induction and Coinduction
Subtyping, Declaratively An Exercise in Mixed Induction and Coinduction Nils Anders Danielsson and Thorsten Altenkirch University of Nottingham Abstract. It is natural to present subtyping for recursive types coin- ductively. However, Gapeyev, Levin and Pierce have noted that there is a problem with coinductive definitions of non-trivial transitive inference systems: they cannot be \declarative"|as opposed to \algorithmic" or syntax-directed|because coinductive inference systems with an explicit rule of transitivity are trivial. We propose a solution to this problem. By using mixed induction and coinduction we define an inference system for subtyping which combines the advantages of coinduction with the convenience of an explicit rule of transitivity. The definition uses coinduction for the structural rules, and induction for the rule of transitivity. We also discuss under what condi- tions this technique can be used when defining other inference systems. The developments presented in the paper have been mechanised using Agda, a dependently typed programming language and proof assistant. 1 Introduction Coinduction and corecursion are useful techniques for defining and reasoning about things which are potentially infinite, including streams and other (poten- tially) infinite data types (Coquand 1994; Gim´enez1996; Turner 2004), process congruences (Milner 1990), congruences for functional programs (Gordon 1999), closures (Milner and Tofte 1991), semantics for divergence of programs (Cousot and Cousot 1992; Hughes and Moran 1995; Leroy and Grall 2009; Nakata and Uustalu 2009), and subtyping relations for recursive types (Brandt and Henglein 1998; Gapeyev et al. 2002). However, the use of coinduction can lead to values which are \too infinite”. For instance, a non-trivial binary relation defined as a coinductive inference sys- tem cannot include the rule of transitivity, because a coinductive reading of transitivity would imply that every element is related to every other (to see this, build an infinite derivation consisting solely of uses of transitivity). -
Generic Programming
Generic Programming July 21, 1998 A Dagstuhl Seminar on the topic of Generic Programming was held April 27– May 1, 1998, with forty seven participants from ten countries. During the meeting there were thirty seven lectures, a panel session, and several problem sessions. The outcomes of the meeting include • A collection of abstracts of the lectures, made publicly available via this booklet and a web site at http://www-ca.informatik.uni-tuebingen.de/dagstuhl/gpdag.html. • Plans for a proceedings volume of papers submitted after the seminar that present (possibly extended) discussions of the topics covered in the lectures, problem sessions, and the panel session. • A list of generic programming projects and open problems, which will be maintained publicly on the World Wide Web at http://www-ca.informatik.uni-tuebingen.de/people/musser/gp/pop/index.html http://www.cs.rpi.edu/˜musser/gp/pop/index.html. 1 Contents 1 Motivation 3 2 Standards Panel 4 3 Lectures 4 3.1 Foundations and Methodology Comparisons ........ 4 Fundamentals of Generic Programming.................. 4 Jim Dehnert and Alex Stepanov Automatic Program Specialization by Partial Evaluation........ 4 Robert Gl¨uck Evaluating Generic Programming in Practice............... 6 Mehdi Jazayeri Polytypic Programming........................... 6 Johan Jeuring Recasting Algorithms As Objects: AnAlternativetoIterators . 7 Murali Sitaraman Using Genericity to Improve OO Designs................. 8 Karsten Weihe Inheritance, Genericity, and Class Hierarchies.............. 8 Wolf Zimmermann 3.2 Programming Methodology ................... 9 Hierarchical Iterators and Algorithms................... 9 Matt Austern Generic Programming in C++: Matrix Case Study........... 9 Krzysztof Czarnecki Generative Programming: Beyond Generic Programming........ 10 Ulrich Eisenecker Generic Programming Using Adaptive and Aspect-Oriented Programming . -
Java Application Programming Interface (API) Java Application Programming Interface (API) Is a List of All Classes That Are Part of the Java Development Kit (JDK)
Java Application Programming Interface (API) Java application programming interface (API) is a list of all classes that are part of the Java development kit (JDK). It includes all Java packages, classes, and interfaces, along with their methods, fields, and constructors. These prewritten classes provide a tremendous amount of functionality to a programmer. A programmer should be aware of these classes and should know how to use them. A complete listing of all classes in Java API can be found at Oracle’s website: http://docs.oracle.com/javase/7/docs/api/. Please visit the above site and bookmark it for future reference. Please consult this site often, especially when you are using a new class and would like to know more about its methods and fields. If you browse through the list of packages in the API, you will observe that there are packages written for GUI programming, networking programming, managing input and output, database programming, and many more. Please browse the complete list of packages and their descriptions to see how they can be used. In order to use a class from Java API, one needs to include an import statement at the start of the program. For example, in order to use the Scanner class, which allows a program to accept input from the keyboard, one must include the following import statement: import java.util.Scanner; The above import statement allows the programmer to use any method listed in the Scanner class. Another choice for including the import statement is the wildcard option shown below: import java.util.*; This version of the import statement imports all the classes in the API’s java.util package and makes them available to the programmer. -
A Metaobject Protocol for Fault-Tolerant CORBA Applications
A Metaobject Protocol for Fault-Tolerant CORBA Applications Marc-Olivier Killijian*, Jean-Charles Fabre*, Juan-Carlos Ruiz-Garcia*, Shigeru Chiba** *LAAS-CNRS, 7 Avenue du Colonel Roche **Institute of Information Science and 31077 Toulouse cedex, France Electronics, University of Tsukuba, Tennodai, Tsukuba, Ibaraki 305-8573, Japan Abstract The corner stone of a fault-tolerant reflective The use of metalevel architectures for the architecture is the MOP. We thus propose a special implementation of fault-tolerant systems is today very purpose MOP to address the problems of general-purpose appealing. Nevertheless, all such fault-tolerant systems ones. We show that compile-time reflection is a good have used a general-purpose metaobject protocol (MOP) approach for developing a specialized runtime MOP. or are based on restricted reflective features of some The definition and the implementation of an object-oriented language. According to our past appropriate runtime metaobject protocol for implementing experience, we define in this paper a suitable metaobject fault tolerance into CORBA applications is the main protocol, called FT-MOP for building fault-tolerant contribution of the work reported in this paper. This systems. We explain how to realize a specialized runtime MOP, called FT-MOP (Fault Tolerance - MetaObject MOP using compile-time reflection. This MOP is CORBA Protocol), is sufficiently general to be used for other aims compliant: it enables the execution and the state evolution (mobility, adaptability, migration, security). FT-MOP of CORBA objects to be controlled and enables the fault provides a mean to attach dynamically fault tolerance tolerance metalevel to be developed as CORBA software. strategies to CORBA objects as CORBA metaobjects, enabling thus these strategies to be implemented as 1 . -
Variable-Arity Generic Interfaces
Variable-Arity Generic Interfaces T. Stephen Strickland, Richard Cobbe, and Matthias Felleisen College of Computer and Information Science Northeastern University Boston, MA 02115 [email protected] Abstract. Many programming languages provide variable-arity func- tions. Such functions consume a fixed number of required arguments plus an unspecified number of \rest arguments." The C++ standardiza- tion committee has recently lifted this flexibility from terms to types with the adoption of a proposal for variable-arity templates. In this paper we propose an extension of Java with variable-arity interfaces. We present some programming examples that can benefit from variable-arity generic interfaces in Java; a type-safe model of such a language; and a reduction to the core language. 1 Introduction In April of 2007 the C++ standardization committee adopted Gregor and J¨arvi's proposal [1] for variable-length type arguments in class templates, which pre- sented the idea and its implementation but did not include a formal model or soundness proof. As a result, the relevant constructs will appear in the upcom- ing C++09 draft. Demand for this feature is not limited to C++, however. David Hall submitted a request for variable-arity type parameters for classes to Sun in 2005 [2]. For an illustration of the idea, consider the remarks on first-class functions in Scala [3] from the language's homepage. There it says that \every function is a value. Scala provides a lightweight syntax for defining anonymous functions, it supports higher-order functions, it allows functions to be nested, and supports currying." To achieve this integration of objects and closures, Scala's standard library pre-defines ten interfaces (traits) for function types, which we show here in Java-like syntax: interface Function0<Result> { Result apply(); } interface Function1<Arg1,Result> { Result apply(Arg1 a1); } interface Function2<Arg1,Arg2,Result> { Result apply(Arg1 a1, Arg2 a2); } .. -
Data-Trace Types for Distributed Stream Processing Systems
Data-Trace Types for Distributed Stream Processing Systems Konstantinos Mamouras Caleb Stanford Rajeev Alur Rice University, USA University of Pennsylvania, USA University of Pennsylvania, USA [email protected] [email protected] [email protected] Zachary G. Ives Val Tannen University of Pennsylvania, USA University of Pennsylvania, USA [email protected] [email protected] Abstract guaranteeing correct deployment, and (2) the throughput of Distributed architectures for efficient processing of stream- the automatically compiled distributed code is comparable ing data are increasingly critical to modern information pro- to that of hand-crafted distributed implementations. cessing systems. The goal of this paper is to develop type- CCS Concepts • Information systems → Data streams; based programming abstractions that facilitate correct and Stream management; • Theory of computation → Stream- efficient deployment of a logical specification of the desired ing models; • Software and its engineering → General computation on such architectures. In the proposed model, programming languages. each communication link has an associated type specifying tagged data items along with a dependency relation over tags Keywords distributed data stream processing, types that captures the logical partial ordering constraints over data items. The semantics of a (distributed) stream process- ACM Reference Format: ing system is then a function from input data traces to output Konstantinos Mamouras, Caleb Stanford, Rajeev Alur, Zachary data traces, where a data trace is an equivalence class of se- G. Ives, and Val Tannen. 2019. Data-Trace Types for Distributed quences of data items induced by the dependency relation. Stream Processing Systems. In Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation This data-trace transduction model generalizes both acyclic (PLDI ’19), June 22–26, 2019, Phoenix, AZ, USA. -
On the Interaction of Object-Oriented Design Patterns and Programming
On the Interaction of Object-Oriented Design Patterns and Programming Languages Gerald Baumgartner∗ Konstantin L¨aufer∗∗ Vincent F. Russo∗∗∗ ∗ Department of Computer and Information Science The Ohio State University 395 Dreese Lab., 2015 Neil Ave. Columbus, OH 43210–1277, USA [email protected] ∗∗ Department of Mathematical and Computer Sciences Loyola University Chicago 6525 N. Sheridan Rd. Chicago, IL 60626, USA [email protected] ∗∗∗ Lycos, Inc. 400–2 Totten Pond Rd. Waltham, MA 02154, USA [email protected] February 29, 1996 Abstract Design patterns are distilled from many real systems to catalog common programming practice. However, some object-oriented design patterns are distorted or overly complicated because of the lack of supporting programming language constructs or mechanisms. For this paper, we have analyzed several published design patterns looking for idiomatic ways of working around constraints of the implemen- tation language. From this analysis, we lay a groundwork of general-purpose language constructs and mechanisms that, if provided by a statically typed, object-oriented language, would better support the arXiv:1905.13674v1 [cs.PL] 31 May 2019 implementation of design patterns and, transitively, benefit the construction of many real systems. In particular, our catalog of language constructs includes subtyping separate from inheritance, lexically scoped closure objects independent of classes, and multimethod dispatch. The proposed constructs and mechanisms are not radically new, but rather are adopted from a variety of languages and programming language research and combined in a new, orthogonal manner. We argue that by describing design pat- terns in terms of the proposed constructs and mechanisms, pattern descriptions become simpler and, therefore, accessible to a larger number of language communities.