The Evolution of Lua
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Understanding the Syntactic Rule Usage in Java
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by UCL Discovery Understanding the Syntactic Rule Usage in Java Dong Qiua, Bixin Lia,∗, Earl T. Barrb, Zhendong Suc aSchool of Computer Science and Engineering, Southeast University, China bDepartment of Computer Science, University College London, UK cDepartment of Computer Science, University of California Davis, USA Abstract Context: Syntax is fundamental to any programming language: syntax defines valid programs. In the 1970s, computer scientists rigorously and empirically studied programming languages to guide and inform language design. Since then, language design has been artistic, driven by the aesthetic concerns and intuitions of language architects. Despite recent studies on small sets of selected language features, we lack a comprehensive, quantitative, empirical analysis of how modern, real-world source code exercises the syntax of its programming language. Objective: This study aims to understand how programming language syntax is employed in actual development and explore their potential applications based on the results of syntax usage analysis. Method: We present our results on the first such study on Java, a modern, mature, and widely-used programming language. Our corpus contains over 5,000 open-source Java projects, totalling 150 million source lines of code (SLoC). We study both independent (i.e. applications of a single syntax rule) and dependent (i.e. applications of multiple syntax rules) rule usage, and quantify their impact over time and project size. Results: Our study provides detailed quantitative information and yields insight, particularly (i) confirming the conventional wisdom that the usage of syntax rules is Zipfian; (ii) showing that the adoption of new rules and their impact on the usage of pre-existing rules vary significantly over time; and (iii) showing that rule usage is highly contextual. -
S-Algol Reference Manual Ron Morrison
S-algol Reference Manual Ron Morrison University of St. Andrews, North Haugh, Fife, Scotland. KY16 9SS CS/79/1 1 Contents Chapter 1. Preface 2. Syntax Specification 3. Types and Type Rules 3.1 Universe of Discourse 3.2 Type Rules 4. Literals 4.1 Integer Literals 4.2 Real Literals 4.3 Boolean Literals 4.4 String Literals 4.5 Pixel Literals 4.6 File Literal 4.7 pntr Literal 5. Primitive Expressions and Operators 5.1 Boolean Expressions 5.2 Comparison Operators 5.3 Arithmetic Expressions 5.4 Arithmetic Precedence Rules 5.5 String Expressions 5.6 Picture Expressions 5.7 Pixel Expressions 5.8 Precedence Table 5.9 Other Expressions 6. Declarations 6.1 Identifiers 6.2 Variables, Constants and Declaration of Data Objects 6.3 Sequences 6.4 Brackets 6.5 Scope Rules 7. Clauses 7.1 Assignment Clause 7.2 if Clause 7.3 case Clause 7.4 repeat ... while ... do ... Clause 7.5 for Clause 7.6 abort Clause 8. Procedures 8.1 Declarations and Calls 8.2 Forward Declarations 2 9. Aggregates 9.1 Vectors 9.1.1 Creation of Vectors 9.1.2 upb and lwb 9.1.3 Indexing 9.1.4 Equality and Equivalence 9.2 Structures 9.2.1 Creation of Structures 9.2.2 Equality and Equivalence 9.2.3 Indexing 9.3 Images 9.3.1 Creation of Images 9.3.2 Indexing 9.3.3 Depth Selection 9.3.4 Equality and Equivalence 10. Input and Output 10.1 Input 10.2 Output 10.3 i.w, s.w and r.w 10.4 End of File 11. -
Sugarj: Library-Based Syntactic Language Extensibility
SugarJ: Library-based Syntactic Language Extensibility Sebastian Erdweg, Tillmann Rendel, Christian Kastner,¨ and Klaus Ostermann University of Marburg, Germany Abstract import pair.Sugar; Existing approaches to extend a programming language with syntactic sugar often leave a bitter taste, because they cannot public class Test f be used with the same ease as the main extension mechanism private (String, Integer) p = ("12", 34); of the programming language—libraries. Sugar libraries are g a novel approach for syntactically extending a programming Figure 1. Using a sugar library for pairs. language within the language. A sugar library is like an or- dinary library, but can, in addition, export syntactic sugar for using the library. Sugar libraries maintain the compos- 1. Introduction ability and scoping properties of ordinary libraries and are Bridging the gap between domain concepts and the imple- hence particularly well-suited for embedding a multitude of mentation of these concepts in a programming language is domain-specific languages into a host language. They also one of the “holy grails” of software development. Domain- inherit self-applicability from libraries, which means that specific languages (DSLs), such as regular expressions for sugar libraries can provide syntactic extensions for the defi- the domain of text recognition or Java Server Pages for the nition of other sugar libraries. domain of dynamic web pages have often been proposed To demonstrate the expressiveness and applicability of to address this problem [31]. To use DSLs in large soft- sugar libraries, we have developed SugarJ, a language on ware systems that touch multiple domains, developers have top of Java, SDF and Stratego, which supports syntactic to be able to compose multiple domain-specific languages extensibility. -
Syntactic Sugar Programming Languages' Constructs - Preliminary Study
ICIT 2011 The 5th International Conference on Information Technology Syntactic Sugar Programming Languages' Constructs - Preliminary Study #1 #2 Mustafa Al-Tamim , Rashid Jayousi Department of Computer Science, Al-Quds University, Jerusalem, Palestine [email protected] 00972-59-9293002 [email protected] 00972-52-7456731 ICIT 2011 The 5th International Conference on Information Technology Syntactic Sugar Programming Languages' Constructs - Preliminary Study #1 #2 Mustafa Al-Tamim , Rashid Jayousi Department of Computer Science, Al-Quds University, Jerusalem, Palestine [email protected] [email protected] Abstract— Software application development is a daily task done syntax and help in making it more readable, easier to write, by developers and code writer all over the world. Valuable less syntax errors and less ambiguous. portion of developers’ time is spent in writing repetitive In this research, we proposed new set of syntactic sugar keywords, debugging code, trying to understand its semantic, constructs that can be composed by a mixture of existing and fixing syntax errors. These tasks become harder when no constructs obtained from some programming languages in integrated development environment (IDE) is available or developers use remote access terminals like UNIX and simple addition to syntactic enhancements suggested by us. Through text editors for code writing. Syntactic sugar constructs in our work as software developer, team leaders, and guiding programming languages are found to offer simple and easy many students in their projects, we noticed that developers syntax constructs to make developers life easier and smother. In write a lot of repetitive keywords in specific parts of code like this paper, we propose a new set of syntactic sugar constructs, packages calling keywords, attributes access modifiers, code and try to find if they really can help developers in eliminating segments and building blocks’ scopes determination symbols syntax errors, make code more readable, more easier to write, and others. -
Compiler Construction E Syntactic Sugar E
Compiler Construction e Syntactic sugar E Compiler Construction Syntactic sugar 1 / 16 Syntactic sugar & Desugaring Syntactic Sugar Additions to a language to make it easier to read or write, but that do not change the expressiveness Desugaring Higher-level features that can be decomposed into language core of essential constructs ) This process is called ”desugaring”. Compiler Construction Syntactic sugar 2 / 16 Pros & Cons for syntactic sugar Pros More readable, More writable Express things more elegantly Cons Adds bloat to the languages Syntactic sugar can affect the formal structure of a language Compiler Construction Syntactic sugar 3 / 16 Syntactic Sugar in Lambda-Calculus The term ”syntactic sugar” was coined by Peter J. Landin in 1964, while describing an ALGOL-like language that was defined in term of lambda-calculus ) goal: replace λ by where Curryfication λxy:e ) λx:(λy:e) Local variables let x = e1 in e2 ) (λx:e2):e1 Compiler Construction Syntactic sugar 4 / 16 List Comprehension in Haskell qs [] = [] qs (x:xs) = qs lt_x ++ [x] ++ qs ge_x where lt_x = [y | y <- xs, y < x] ge_x = [y | y <- xs, x <= y] Compiler Construction Syntactic sugar 5 / 16 List Comprehension in Haskell Sugared [(x,y) | x <- [1 .. 6], y <- [1 .. x], x+y < 10] Desugared filter p (concat (map (\ x -> map (\ y -> (x,y)) [1..x]) [1..6] ) ) where p (x,y) = x+y < 10 Compiler Construction Syntactic sugar 6 / 16 Interferences with error messages ”true” | 42 standard input:1.1-6: type mismatch condition type: string expected type: int function _main() = ( (if "true" then 1 else (42 <> 0)); () ) Compiler Construction Syntactic sugar 7 / 16 Regular Unary - & and | Beware of ( exp ) vs. -
CSC 272 - Software II: Principles of Programming Languages
CSC 272 - Software II: Principles of Programming Languages Lecture 1 - An Introduction What is a Programming Language? • A programming language is a notational system for describing computation in machine-readable and human-readable form. • Most of these forms are high-level languages , which is the subject of the course. • Assembly languages and other languages that are designed to more closely resemble the computer’s instruction set than anything that is human- readable are low-level languages . Why Study Programming Languages? • In 1969, Sammet listed 120 programming languages in common use – now there are many more! • Most programmers never use more than a few. – Some limit their career’s to just one or two. • The gain is in learning about their underlying design concepts and how this affects their implementation. The Six Primary Reasons • Increased ability to express ideas • Improved background for choosing appropriate languages • Increased ability to learn new languages • Better understanding of significance of implementation • Better use of languages that are already known • Overall advancement of computing Reason #1 - Increased ability to express ideas • The depth at which people can think is heavily influenced by the expressive power of their language. • It is difficult for people to conceptualize structures that they cannot describe, verbally or in writing. Expressing Ideas as Algorithms • This includes a programmer’s to develop effective algorithms • Many languages provide features that can waste computer time or lead programmers to logic errors if used improperly – E. g., recursion in Pascal, C, etc. – E. g., GoTos in FORTRAN, etc. Reason #2 - Improved background for choosing appropriate languages • Many professional programmers have a limited formal education in computer science, limited to a small number of programming languages. -
Note Quiz 1 K All 10 Questions Ise File Main Sy Thay Note Handouts Main Note Keyword Ko Search Krien Important Points Hain Jin Ko Lazmi Yaad Krna Hy
Note Quiz 1 k all 10 questions ise file main sy thay Note handouts main note keyword ko search krien important points hain jin ko lazmi yaad krna hy. Ada discriminate types is similar to . C/C++ pointer C/C++ union C/C++ reference All of the given Page # 52 - My Ok The block structure feature of ALGOL60 has scope. No Local Universal Global Page # 26 – My Ok Unlike C/C++, Ada can have _____ within functions/procedures. Objects Functions/procedures Events Parameters Page # 58 – My Ok In the Decimal fixed point type, the distance between values is implemented as a power of 2 10 8 16 Page # 50 – My Ok Function must have at least ______ return statement. Three Two One Four Page # 57 – My Ok Every function must have at least one return statement. A procedure is not required to have any return statements. The expression in a function's return statement must evaluate to a type that matches the return type in the function's declaration. ______ operations must have one of its parameters of the tagged type. Concurrent Synchronized Primitive Generic Page # 59 – My Ok An understanding of implementation issues leads to a/an ______ of why languages are designed the way they are. Uncertainty Understanding Misunderstanding Confusion Page # 5 – My Ok ________ has an efficient use of processor and memory. Plankul Kool LISP CORBA C++ Imperative programming languages are the direct result of . Charles Babbage engine Logic or list program languages. Von Neumann architecture Language application domain Page # 22 – My Ok Following are imperative languages EXCEPT LISP C FORTRAN PASCAL Page # 22 – My Ok Which statement is true from programming language evolution perspective about 1970's era? Analysis and elaboration era Era of effective software technology Era of object oriented programming languages Era of discovery and description Page # 30 – My Ok SNOBOL language questions starts from here Variable name in SNOBOL may not be longer than . -
PHP 7: What to Expect Lorna Mitchell, PHPUK 2016
PHP 7: What To Expect Lorna Mitchell, PHPUK 2016 Slides available online, help yourself: http://www.lornajane.net/resources Versions of PHP Version Support until Security fixes until PHP 5.5 (expired) 10th July 2016 PHP 5.6 31st December 2016 31st December 2018 PHP 7.0 3rd December 2017 3rd December 2018 see also: http://php.net/supported-versions.php PHP 7 Is Fast PHP 7 Is Fast Why PHP 7 Is Fast • Grew from the phpng project • Influenced by HHVM/Hacklang • Major refactoring of the Zend Engine • More compact data structures throughout • As a result all extensions need updates • http://gophp7.org/gophp7-ext/ Rasmus' stats: http://talks.php.net/fluent15#/6 Abstract Syntax Trees PHP 7 uses an additional AST step during compilation This gives a performance boost and much nicer architecture Abstract Syntax Trees Example code: 1 $a = rand(0,1); 2 3 if($a) { 4 echo "Heads"; 5 } else { 6 echo "Tails"; 7 } Abstract Syntax Trees Tokenized PHP: T_OPEN_TAG: <?php T_VARIABLE: $a T_WHITESPACE: = T_WHITESPACE: T_STRING: rand ( T_LNUMBER: 0 , T_LNUMBER: 1 ) ; Abstract Syntax Trees Abstract syntax tree representation: AST_STMT_LIST AST_ASSIGN AST_VAR a AST_CALL AST_NAME rand AST_ARG_LIST 0 1 New Features Combined Comparison Operator The <=> "spaceship" operator is for quick greater/less than comparison. 1 echo 2 <=> 1; // 1 2 echo 2 <=> 3; // -1 3 echo 2 <=> 2; // 0 Ternary Shorthand Refresher on this PHP 5 feature: 1 echo $count ? $count : 10; // 10 2 echo $count ?: 10; // 10 Null Coalesce Operator Operator ?? is ternary shorthand (?:) but with isset(). 1 $b = 16; 2 3 echo $a ?? 2; // 2 4 echo $a ?? $b ?? 7; // 16 Type Hints PHP 5 has type hinting, allowing you to say what kind of parameter is acceptable in a method call. -
R and C++ Integration
OPENCOURSEWARE ADVANCED PROGRAMMING STATISTICS FOR DATA SCIENCE Ricardo Aler R and C++ integration The purpose of this topic is to show how to improve the efficiency of some R operations by programming them in a compiled language : C++. R is an interpreted language and this makes its execution slow. This is not usually a problem, because R is used as a glue language, in order to put together functions which belong to external libraries. Those libraries have been programmed in Fortran, C, or C++, all of them fast (compiled) languages. Given that R spends most of its time executing those libraries, R inefficiencies do not show in most cases. However, there are some situations, such as executing long loops, for which R is known to be slow, and efficiency might benefit from moving those parts to functions programmed in a compiled language. Package RCpp offers a simple and seamless way of integrating both languages. First it will be explained what is meant by interpreted versus compiled, dynamic versus static typing, and at what situations R is slow (mainly loops and function calling). And therefore, it is worth considering moving those parts to a compiled language like C++. Instead of explaining the complete C++ language, RCpp will be introduced by means of examples. In particular, the following types of functions will be explained, with both the R syntax and the C++ syntax : 1. No inputs, scalar output 2. Scalar input, scalar output 3. Vector input, scalar output 4. Vector input, vector output Finally, the concept of RCpp syntactic sugar will be explained : syntactic sugar is a way of making writing C++ programs more simple, using a simplified yet powerful syntax. -
ED027743.Pdf
DOCUMENT RESUME ED 027 743 EM 007 134 By-Fasana, Paul J., Ed.; Shank, Russell, Ed. Tutorial on Generalized Programming Language s and Systems. Instructor Edition. American Society for Information Science, Washington, D.C. Spons Agency-National Science Foundation, Washington, D.C. Pub Date Jul 68 Grant- F -NSF -GN -657 Note-65p.; Manual based on materials prepared and presented by Thomas K. Burgess and others at the Annual Convention of the American Society for Information Science (New York, October 22-26, 1967) EDRS Price MF-$0.50 HC-$3.35 Descriptors-*Computer Science, *Computer Science Education, Information Retrieval, Information Storage, *Manuals Identifiers-COBOL, FORTRAN, PL I, SNOBOL This instructor's manual is a comparative analysis and review of the various computer programing languagescurrentlyavailable andtheircapabilitiesfor performing text manipulation, information storage, and data retrieval tasks. Based on materials presented at the 1967 Convention of the American Society for Information Science,themanualdescribes FORTRAN, a language designedprimarilyfor mathematicalcomputation;SNOBOL, alist-processinglanguagedesignedfor information retrieval application; COBOL, a business oriented language; and PL/L a new language incorporating many of the desirable features of FORTRAN andCOBOL but as yet implemented only for the IBM 360 computer system. (TI) U.S. DEPARTMENT OF HEALTH, EDUCATION & WELFARE OFFICE OF EDUCATION Pek THIS DOCUMENT HAS BEEN REPRODUCED EXACTLY AS RECEIVED FROM THE N. PERSON OR ORGANIZATION ORIGINATING IT.POINTS Of VIEW OR OPINIONS rJ STATED DO NOT NECESSARILY REPRESENT OFFICIAL OFFICE OF EDUCATION TUTORIAL ON POSITION OR POLICY. GENERALIZED PROGRAMMING LANGUAGES AND SYSTEMS Instructor Edition. Edited by Paul J. Fasana Columbia University Libraries New York, N. Y. and Russell Shank The Smithsonian Institution Washington, D. -
Elements of Programming Languages Overview Advanced Constructs
Advanced constructs Functions as objects Iterators and comprehensions Advanced constructs Functions as objects Iterators and comprehensions Overview Elements of Programming Languages We’ve now covered: Lecture 11: Object-oriented functional programming basics of functional programming (with semantics) basics of modular and OO programming (via Scala examples) James Cheney Today, finish discussion of “programming in the large”: University of Edinburgh some more advanced OO constructs and how they co-exist with/support functional October 30, 2017 programming in Scala list comprehensions as an extended example Advanced constructs Functions as objects Iterators and comprehensions Advanced constructs Functions as objects Iterators and comprehensions Advanced constructs Motivating inner class example So far, we’ve covered the “basic” OOP model (circa Java A nested/inner class has access to the private/protected 1.0), plus some Scala-isms members of the containing class Modern languages extend this model in several ways So, we can use nested classes to expose an interface We can define a structure (class/object/trait) inside associated with a specific object: another: As a member of the enclosing class (tied to a specific class List<A> { instance) private A head; or as a static member (shared across all instances) private List<A> tail; As a local definition inside a method class ListIterator<A> implements Iterator<A> { As an anonymous local definition ... (can access head, tail) Java (since 1.5) and Scala support “generics” } } (parameterized types -
Coffeescript Accelerated Javascript Development
Extracted from: CoffeeScript Accelerated JavaScript Development This PDF file contains pages extracted from CoffeeScript, published by the Prag- matic Bookshelf. For more information or to purchase a paperback or PDF copy, please visit http://www.pragprog.com . Note: This extract contains some colored text (particularly in code listing). This is available only in online versions of the books. The printed versions are black and white. Pagination might vary between the online and printer versions; the content is otherwise identical. Copyright © 2010 The Pragmatic Programmers, LLC. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form, or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior consent of the publisher. The Pragmatic Bookshelf Dallas, Texas • Raleigh, North Carolina CoffeeScript Accelerated JavaScript Development Trevor Burnham The Pragmatic Bookshelf Dallas, Texas • Raleigh, North Carolina Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and The Pragmatic Programmers, LLC was aware of a trademark claim, the designations have been printed in initial capital letters or in all capitals. The Pragmatic Starter Kit, The Pragmatic Programmer, Pragmatic Programming, Pragmatic Bookshelf, PragProg and the linking g device are trade- marks of The Pragmatic Programmers, LLC. Every precaution was taken in the preparation of this book. However, the publisher assumes no responsibility for errors or omissions, or for damages that may result from the use of information (including program listings) contained herein. Our Pragmatic courses, workshops, and other products can help you and your team create better software and have more fun.