Adding Genericity to the Java Programming Language
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Introduction Code Reuse
The Sather Language: Efficient, Interactive, Object-Oriented Programming Stephen Omohundro Dr. Dobbs Journal Introduction Sather is an object oriented language which aims to be simple, efficient, interactive, safe, and non-proprietary. One way of placing it in the "space of languages" is to say that it aims to be as efficient as C, C++, or Fortran, as elegant and safe as Eiffel or CLU, and to support interactive programming and higher-order functions as well as Common Lisp, Scheme, or Smalltalk. Sather has parameterized classes, object-oriented dispatch, statically-checked strong typing, separate implementation and type inheritance, multiple inheritance, garbage collection, iteration abstraction, higher-order routines and iters, exception handling, constructors for arbitrary data structures, and assertions, preconditions, postconditions, and class invariants. This article describes the first few of these features. The development environment integrates an interpreter, a debugger, and a compiler. Sather programs can be compiled into portable C code and can efficiently link with C object files. Sather has a very unrestrictive license which allows its use in proprietary projects but encourages contribution to the public library. The original 0.2 version of the Sather compiler and tools was made available in June 1991. This article describes version 1.0. By the time the article appears, the combined 1.0 compiler/interpreter/debugger should be available on "ftp.icsi.berkeley.edu" and the newsgroup "comp.lang.sather" should be activated for discussion. Code Reuse The primary benefit promised by object-oriented languages is reuse of code. Sather programs consist of collections of modules called "classes" which encapsulate well-defined abstractions. -
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 for Scientific Computing, Pros and Cons
Journal of Universal Computer Science, vol. 4, no. 1 (1998), 11-15 submitted: 25/9/97, accepted: 1/11/97, appeared: 28/1/98 Springer Pub. Co. Java for Scienti c Computing, Pros and Cons Jurgen Wol v. Gudenb erg Institut fur Informatik, Universitat Wurzburg wol @informatik.uni-wuerzburg.de Abstract: In this article we brie y discuss the advantages and disadvantages of the language Java for scienti c computing. We concentrate on Java's typ e system, investi- gate its supp ort for hierarchical and generic programming and then discuss the features of its oating-p oint arithmetic. Having found the weak p oints of the language we pro- p ose workarounds using Java itself as long as p ossible. 1 Typ e System Java distinguishes b etween primitive and reference typ es. Whereas this distinc- tion seems to b e very natural and helpful { so the primitives which comprise all standard numerical data typ es have the usual value semantics and expression concept, and the reference semantics of the others allows to avoid p ointers at all{ it also causes some problems. For the reference typ es, i.e. arrays, classes and interfaces no op erators are available or may b e de ned and expressions can only b e built by metho d calls. Several variables may simultaneously denote the same ob ject. This is certainly strange in a numerical setting, but not to avoid, since classes have to b e used to intro duce higher data typ es. On the other hand, the simple hierarchy of classes with the ro ot Object clearly b elongs to the advantages of the language. -
CLOS, Eiffel, and Sather: a Comparison
CLOS, Eiffel, and Sather: A Comparison Heinz W. Schmidt-, Stephen M. Omohundrot " September, 1991 li ____________T_R_._91_-0_47____________~ INTERNATIONAL COMPUTER SCIENCE INSTITUTE 1947 Center Street, Suite 600 Berkeley, California 94704-1105 CLOS, Eiffel, and Sather: A Comparison Heinz W. Schmidt-, Stephen M. Omohundrot September, 1991 Abstract The Common Lisp Object System defines a powerful and flexible type system that builds on more than fifteen years of experience with object-oriented programming. Most current implementations include a comfortable suite of Lisp support tools in cluding an Emacs Lisp editor, an interpreter, an incremental compiler, a debugger, and an inspector that together promote rapid prototyping and design. What else might one want from a system? We argue that static typing yields earlier error detec tion, greater robustness, and higher efficiency and that greater simplicity and more orthogonality in the language constructs leads to a shorter learning curve and more in tuitive programming. These elements can be found in Eiffel and a new object-oriented language, Sather, that we are developing at leS!. Language simplicity and static typ ing are not for free,·though. Programmers have to pay with loss of polymorphism and flexibility in prototyping. We give a short comparison of CLOS, Eiffel and Sather, addressing both language and environment issues. The different approaches taken by the languages described in this paper have evolved to fulfill different needs. While we have only touched on the essential differ ences, we hope that this discussion will be helpful in understanding the advantages and disadvantages of each language. -ICSI, on leave from: Inst. f. Systemtechnik, GMD, Germany tICSI 1 Introduction Common Lisp [25] was developed to consolidate the best ideas from a long line of Lisp systems and has become an important standard. -
Iterable Abstract Pattern Matching for Java
JMatch: Iterable Abstract Pattern Matching for Java Jed Liu and Andrew C. Myers Computer Science Department Cornell University, Ithaca, New York Abstract. The JMatch language extends Java with iterable abstract pattern match- ing, pattern matching that is compatible with the data abstraction features of Java and makes iteration abstractions convenient. JMatch has ML-style deep pattern matching, but patterns can be abstract; they are not tied to algebraic data con- structors. A single JMatch method may be used in several modes; modes may share a single implementation as a boolean formula. Modal abstraction simplifies specification and implementation of abstract data types. This paper describes the JMatch language and its implementation. 1 Introduction Object-oriented languages have become a dominant programming paradigm, yet they still lack features considered useful in other languages. Functional languages offer expressive pattern matching. Logic programming languages provide powerful mech- anisms for iteration and backtracking. However, these useful features interact poorly with the data abstraction mechanisms central to object-oriented languages. Thus, ex- pressing some computations is awkward in object-oriented languages. In this paper we present the design and implementation of JMatch, a new object- oriented language that extends Java [GJS96] with support for iterable abstract pattern matching—a mechanism for pattern matching that is compatible with the data abstrac- tion features of Java and that makes iteration abstractions more convenient. -
Programming Paradigms
PROGRAMMING PARADIGMS SNS COLLEGE OF TECHNOLOGY (An Autonomous Institution) COIMBATORE – 35 DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING (UG & PG) Third Year Computer Science and Engineering, 4th Semester QUESTION BANK UNIVERSITY QUESTIONS Subject Code & Name: 16CS206 PROGRAMMING PARADIGMS UNIT-IV PART – A 1. What is an exception? .(DEC 2011-2m) An exception is an event, which occurs during the execution of a program, that disrupts the normal flow of the program's instructions. 2. What is error? .(DEC 2011-2m) An Error indicates that a non-recoverable condition has occurred that should not be caught. Error, a subclass of Throwable, is intended for drastic problems, such as OutOfMemoryError, which would be reported by the JVM itself. 3. Which is superclass of Exception? .(DEC 2011-2m) "Throwable", the parent class of all exception related classes. 4. What are the advantages of using exception handling? .(DEC 2012-2m) Exception handling provides the following advantages over "traditional" error management techniques: Separating Error Handling Code from "Regular" Code. Propagating Errors Up the Call Stack. Grouping Error Types and Error Differentiation. 5. What are the types of Exceptions in Java .(DEC 2012-2m) There are two types of exceptions in Java, unchecked exceptions and checked exceptions. Checked exceptions: A checked exception is some subclass of Exception (or Exception itself), excluding class RuntimeException and its subclasses. Each method must either SNSCT – Department of Compute Science and Engineering Page 1 PROGRAMMING PARADIGMS handle all checked exceptions by supplying a catch clause or list each unhandled checked exception as a thrown exception. Unchecked exceptions: All Exceptions that extend the RuntimeException class are unchecked exceptions. -
Static Reflection
N3996- Static reflection Document number: N3996 Date: 2014-05-26 Project: Programming Language C++, SG7, Reflection Reply-to: Mat´uˇsChochl´ık([email protected]) Static reflection How to read this document The first two sections are devoted to the introduction to reflection and reflective programming, they contain some motivational examples and some experiences with usage of a library-based reflection utility. These can be skipped if you are knowledgeable about reflection. Section3 contains the rationale for the design decisions. The most important part is the technical specification in section4, the impact on the standard is discussed in section5, the issues that need to be resolved are listed in section7, and section6 mentions some implementation hints. Contents 1. Introduction4 2. Motivation and Scope6 2.1. Usefullness of reflection............................6 2.2. Motivational examples.............................7 2.2.1. Factory generator............................7 3. Design Decisions 11 3.1. Desired features................................. 11 3.2. Layered approach and extensibility...................... 11 3.2.1. Basic metaobjects........................... 12 3.2.2. Mirror.................................. 12 3.2.3. Puddle.................................. 12 3.2.4. Rubber................................. 13 3.2.5. Lagoon................................. 13 3.3. Class generators................................ 14 3.4. Compile-time vs. Run-time reflection..................... 16 4. Technical Specifications 16 4.1. Metaobject Concepts............................. -
Libraries for Generic Programming in Haskell
Libraries for Generic Programming in Haskell Johan Jeuring, Sean Leather, Jos´ePedroMagalh˜aes, and Alexey Rodriguez Yakushev Universiteit Utrecht, The Netherlands Abstract. These lecture notes introduce libraries for datatype-generic program- ming in Haskell. We introduce three characteristic generic programming libraries: lightweight implementation of generics and dynamics, extensible and modular generics for the masses, and scrap your boilerplate. We show how to use them to use and write generic programs. In the case studies for the different libraries we introduce generic components of a medium-sized application which assists a student in solving mathematical exercises. 1 Introduction In the development of software, structuring data plays an important role. Many pro- gramming methods and software development tools center around creating a datatype (or XML schema, UML model, class, grammar, etc.). Once the structure of the data has been designed, a software developer adds functionality to the datatypes. There is always some functionality that is specific for a datatype, and part of the reason why the datatype has been designed in the first place. Other functionality is similar or even the same on many datatypes, following common programming patterns. Examples of such patterns are: – in a possibly large value of a complicated datatype (for example for representing the structure of a company), applying a given action at all occurrences of a par- ticular constructor (e.g., adding or updating zip codes at all occurrences of street addresses) while leaving the rest of the value unchanged; – serializing a value of a datatype, or comparing two values of a datatype for equality, functionality that depends only on the structure of the datatype; – adapting data access functions after a datatype has changed, something that often involves modifying large amounts of existing code. -
Generic Programming Sean Parent | Principal Scientist “You Cannot Fully Grasp Mathematics Until You Understand Its Historical Context.” – Alex Stepanov
Generic Programming Sean Parent | Principal Scientist “You cannot fully grasp mathematics until you understand its historical context.” – Alex Stepanov © 2018 Adobe. All Rights Reserved. 2 1988 © 2018 Adobe. All Rights Reserved. 3 © 2018 Adobe. All Rights Reserved. 4 © 2018 Adobe. All Rights Reserved. 4 © 2018 Adobe. All Rights Reserved. 4 “By generic programming we mean the definition of algorithms and data structures at an abstract or generic level, thereby accomplishing many related programming tasks simultaneously. The central notion is that of generic algorithms, which are parameterized procedural schemata that are completely independent of the underlying data representation and are derived from concrete, efficient algorithms.” © 2018 Adobe. All Rights Reserved. 5 “By generic programming we mean the definition of algorithms and data structures at an abstract or generic level, thereby accomplishing many related programming tasks simultaneously. The central notion is that of generic algorithms, which are parameterized procedural schemata that are completely independent of the underlying data representation and are derived from concrete, efficient algorithms.” © 2018 Adobe. All Rights Reserved. 6 “By generic programming we mean the definition of algorithms and data structures at an abstract or generic level, thereby accomplishing many related programming tasks simultaneously. The central notion is that of generic algorithms, which are parameterized procedural schemata that are completely independent of the underlying data representation and are derived from concrete, efficient algorithms.” © 2018 Adobe. All Rights Reserved. 7 “By generic programming we mean the definition of algorithms and data structures at an abstract or generic level, thereby accomplishing many related programming tasks simultaneously. The central notion is that of generic algorithms, which are parameterized procedural schemata that are completely independent of the underlying data representation and are derived from concrete, efficient algorithms.” © 2018 Adobe. -
Concepts in Programming Languages
Concepts in Programming Languages Alan Mycrofta Computer Laboratory University of Cambridge 2014–2015 (Easter Term) http://www.cl.cam.ac.uk/teaching/1415/ConceptsPL/ aNotes largely due to Marcelo Fiore—but errors are my responsibility. 1 Practicalities Course web page: www.cl.cam.ac.uk/teaching/1415/ConceptsPL/ with lecture slides, exercise sheet, and reading material. One exam question. 2 Main books J. C. Mitchell. Concepts in programming languages. Cambridge University Press, 2003. T.W. Pratt and M. V.Zelkowitz. Programming Languages: Design and implementation (3RD EDITION). Prentice Hall, 1999. ⋆ M. L. Scott. Programming language pragmatics (2ND EDITION). Elsevier, 2006. R. Harper. Practical Foundations for Programming Languages. Cambridge University Press, 2013. 3 Context : so many programming languages Peter J. Landin: “The Next 700 Programming Languages”, CACM >>>>1966<<<<. Some programming-language ‘family trees’ (too big for slide): http://www.oreilly.com/go/languageposter http://www.levenez.com/lang/ http://rigaux.org/language-study/diagram.html http://www.rackspace.com/blog/ infographic-evolution-of-computer-languages/ Plan of this course: pick out interesting programming- language concepts and major evolutionary trends. 4 Topics I. Introduction and motivation. II. The first procedural language: FORTRAN (1954–58). III. The first declarative language: LISP (1958–62). IV. Block-structured procedural languages: Algol (1958–68), Pascal (1970). V. Object-oriented languages — Concepts and origins: Simula (1964–67), Smalltalk (1971–80). VI. Languages for concurrency and parallelism. VII. Types in programming languages: ML (1973–1978). VIII. Data abstraction and modularity: SML Modules (1984–97). IX. A modern language design: Scala (2007) X. Miscellaneous concepts 5 Topic I Introduction and motivation References: g g Chapter 1 of Concepts in programming languages by J. -
Generic Programming in OCAML
Generic Programming in OCAML Florent Balestrieri Michel Mauny ENSTA-ParisTech, Université Paris-Saclay Inria Paris [email protected] [email protected] We present a library for generic programming in OCAML, adapting some techniques borrowed from other functional languages. The library makes use of three recent additions to OCAML: generalised abstract datatypes are essential to reflect types, extensible variants allow this reflection to be open for new additions, and extension points provide syntactic sugar and generate boiler plate code that simplify the use of the library. The building blocks of the library can be used to support many approachesto generic programmingthrough the concept of view. Generic traversals are implemented on top of the library and provide powerful combinators to write concise definitions of recursive functions over complex tree types. Our case study is a type-safe deserialisation function that respects type abstraction. 1 Introduction Typed functional programming languages come with rich type systems guaranteeing strong safety prop- erties for the programs. However, the restrictions imposed by types, necessary to banish wrong programs, may prevent us from generalizing over some particular programming patterns, thus leading to boilerplate code and duplicated logic. Generic programming allows us to recover the loss of flexibility by adding an extra expressive layer to the language. The purpose of this article is to describe the user interface and explain the implementation of a generic programming library1 for the language OCAML. We illustrate its usefulness with an implementation of a type-safe deserialisation function. 1.1 A Motivating Example Algebraic datatypes are very suitable for capturing structured data, in particular trees. -
Object-Oriented and Concurrent Program Design Issues in Ada 95
Object-Oriented and Concurrent Program Design Issues in Ada 95 Stephen H. Kaisler Michael B. Feldman Director, Systems Architecture Professor of Engineering and Applied Science Office of the Sergeant at Arms Dept. of Electrical Engineering and Computer Science United States Senate George Washington University Washington, DC 20510 Washington, DC 20052 202-224-2582 202-994-6083 [email protected] [email protected] 1. ABSTRACT Kaisler [4] identified several design issues that arose 2. INTRODUCTION from developing a process for transforming object- oriented programs written in Ada 95 or other object- Kaisler [4] described research leading to a methodology oriented programming languages to process-oriented for converting object-oriented programs to process- programs written in Ada 95. These issues limit - in the oriented programs and, thereby, making the concurrency authors' opinion - the flexibility of Ada 95 in writing implicit in object-oriented programs explicit. This concurrent programs. These problems arise from research was motivated by the fact that writing specific decisions made by the Ada 95 designers. This concurrent programs is difficult to do - no general paper addresses three of these issues: circular methodology exists - and by our recognition of the references are invalid in packages, lack of a similarity between object-oriented and process-oriented subclassing mechanism for protected types, and an programs. inability to internally invoke access statements from within a task body. Our goal is to raise the Ada 95 We believed that object-oriented programs, which exhibit community's awareness concerning these design issues a potential for concurrency, could be converted to and provide some suggestions for correcting these process-oriented programs, thereby making the problems for a future revision of the Ada concurrency explicit.