Aeroscript Programming Language Reference
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Scala Tutorial
Scala Tutorial SCALA TUTORIAL Simply Easy Learning by tutorialspoint.com tutorialspoint.com i ABOUT THE TUTORIAL Scala Tutorial Scala is a modern multi-paradigm programming language designed to express common programming patterns in a concise, elegant, and type-safe way. Scala has been created by Martin Odersky and he released the first version in 2003. Scala smoothly integrates features of object-oriented and functional languages. This tutorial gives a great understanding on Scala. Audience This tutorial has been prepared for the beginners to help them understand programming Language Scala in simple and easy steps. After completing this tutorial, you will find yourself at a moderate level of expertise in using Scala from where you can take yourself to next levels. Prerequisites Scala Programming is based on Java, so if you are aware of Java syntax, then it's pretty easy to learn Scala. Further if you do not have expertise in Java but you know any other programming language like C, C++ or Python, then it will also help in grasping Scala concepts very quickly. Copyright & Disclaimer Notice All the content and graphics on this tutorial are the property of tutorialspoint.com. Any content from tutorialspoint.com or this tutorial may not be redistributed or reproduced in any way, shape, or form without the written permission of tutorialspoint.com. Failure to do so is a violation of copyright laws. This tutorial may contain inaccuracies or errors and tutorialspoint provides no guarantee regarding the accuracy of the site or its contents including this tutorial. If you discover that the tutorialspoint.com site or this tutorial content contains some errors, please contact us at [email protected] TUTORIALS POINT Simply Easy Learning Table of Content Scala Tutorial .......................................................................... -
Php Foreach Array Example
Php Foreach Array Example Positivism Sonnie always besought his dimeters if Esme is fruticose or touch-types incompletely. Sometimes anything.plenipotentiary Zane Gordieemits unobtrusively alchemise her while foreman untrained slower, Harlan but bubbliest presages Rodge obsoletely strides or pippingriotously masterfully. or recapitalizes You can have explored deep are using array_map prevents you forgot, and will keep multiple. How we have an associative array is a different values are times has a numeric array and arrays can be obtained by working along. This url into two variables are such type. PHP 4 introduced foreach construct it works only on arrays. Let's understand this with the help bear the porter example. The running one uses it. PHP foreach Manual. Sample PHP Code PHP For Loops Foreach While ago Do. Arrayvalue is your temporary variable that holds the current total item values block of code is the its of code that operates on already array values Example 1. Usually depending on my favourite site for passing it on how if statement. PHP foreach loops FreeKB. Start from any one statement is that, instead of items in an example of each elements with examples to get an array. PHP foreach within foreach repeat data flow not escaping loops. Of iteration helps you can access or public route on here? PHP foreach Loop GeeksforGeeks. Foreach Semantic portal learn smart. Nested for loops One for brother can be no inside another for purpose and force can generate different scripts using nested loops Here is an intelligence for. Here there is used in a block on array index or break statement or associative array by using a multidimensional array an. -
Multi-Return Function Call
To appear in J. Functional Programming 1 Multi-return Function Call OLIN SHIVERS and DAVID FISHER College of Computing Georgia Institute of Technology (e-mail: fshivers,[email protected]) Abstract It is possible to extend the basic notion of “function call” to allow functions to have multiple re- turn points. This turns out to be a surprisingly useful mechanism. This article conducts a fairly wide-ranging tour of such a feature: a formal semantics for a minimal λ-calculus capturing the mechanism; motivating examples; monomorphic and parametrically polymorphic static type sys- tems; useful transformations; implementation concerns and experience with an implementation; and comparison to related mechanisms, such as exceptions, sum-types and explicit continuations. We conclude that multiple-return function call is not only a useful and expressive mechanism, at both the source-code and intermediate-representation levels, but also quite inexpensive to implement. Capsule Review Interesting new control-flow constructs don’t come along every day. Shivers and Fisher’s multi- return function call offers intriguing possibilities—but unlike delimited control operators or first- class continuations, it won’t make your head hurt or break the bank. It might even make you smile when you see the well-known tail call generalized to a “semi-tail call” and a “super-tail call.” What I enjoyed the most was the chance to reimagine several of my favorite little hacks using the new mechanism, but this unusually broad paper offers something for everyone: the language designer, the theorist, the implementor, and the programmer. 1 Introduction The purpose of this article is to explore in depth a particular programming-language mech- anism: the ability to specify multiple return points when calling a function. -
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. -
G, a Language Based on Demand-Driven Stream Evaluations
AN ABSTRACT OF THE THESIS OF John R. Placer for the degree of Doctor of Philosophy in Computer Science presented on November 4, 1988. Title: C: A Language Based On Demand-Driven Stream Evalutions Redacted for privacy Abstract approved: Timothy Budd A programming paradigm can be defined as a model or an approach employed in solving a problem. The results of the research described in this document demon- strate that it is possible to unite several different programming paradigms into a single linguistic framework. The imperative, procedural, applicative, lambda-free, relational, logic and object-oriented programming paradigms were combined ina language called G whose basic datatype is the stream. A stream is a data object whose values are produced as it is traversed. In this dissertation we describe the methodology we developed to guide the design of G, we present the language G itself, we discuss a prototype implementation of G and we provide example programs that show how the paradigms included in G are expressed. We also present programs that demonstrate some ways in which paradigms can be combined to facilitate the solutions to problems. G : A Language Based On Demand-Driven Stream Evaluations by John R. Placer A THESIS submitted to Oregon State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy Completed November 4, 1988 Commencement June 1989 APPROVED: Redacted for privacy Professor of Computer Science in Charge of Major Redacted for privacy Head of Department of Computer Science Redacted for privacy Dean of Gradutate Sc o 1 Date thesis is presented November 4, 1988 Typed by John R. -
C Programming Tutorial
C Programming Tutorial C PROGRAMMING TUTORIAL Simply Easy Learning by tutorialspoint.com tutorialspoint.com i COPYRIGHT & DISCLAIMER NOTICE All the content and graphics on this tutorial are the property of tutorialspoint.com. Any content from tutorialspoint.com or this tutorial may not be redistributed or reproduced in any way, shape, or form without the written permission of tutorialspoint.com. Failure to do so is a violation of copyright laws. This tutorial may contain inaccuracies or errors and tutorialspoint provides no guarantee regarding the accuracy of the site or its contents including this tutorial. If you discover that the tutorialspoint.com site or this tutorial content contains some errors, please contact us at [email protected] ii Table of Contents C Language Overview .............................................................. 1 Facts about C ............................................................................................... 1 Why to use C ? ............................................................................................. 2 C Programs .................................................................................................. 2 C Environment Setup ............................................................... 3 Text Editor ................................................................................................... 3 The C Compiler ............................................................................................ 3 Installation on Unix/Linux ............................................................................ -
Iterating in Perl: Loops
Iterating in Perl: Loops - Computers are great for doing repetitive tasks. - All programming languages come with some way of iterating over some interval. - These methods of iteration are called ‘loops’. - Perl comes with a variety of loops, we will cover 4 of them: 1. if statement and if-else statement 2. while loop and do-while loop 3. for loop 4. foreach loop if statement Syntax: - if the conditional is ‘true’ then the if(conditional) body of the statement (what’s in { between the curly braces) is …some code… executed. } #!/usr/bin/perl -w $var1 = 1333; Output? if($var1 > 10) 1333 is greater than 10 { print “$var1 is greater than 10\n”; } exit; if-else statement Syntax: -if the conditional is ‘true’ then execute if(conditional) the code within the first pair of curly { braces. …some code… } - otherwise (else) execute the code in else the next set of curly braces { …some different code… } Output? #!/usr/bin/perl -w 13 is less than 100 $var1 = 13; if($var1 > 100) { print “$var1 is greater than 100\n”; } else { print “$var1 is less than 100\n”; } exit; Comparisons that are Allowed - In perl you can compare numbers and strings within conditionals - The comparison operators are slightly different for each one - The most common comparison operators for strings: syntax meaning example lt Less than “dog” lt “cat” False! d > c gt Greater than “dog” gt “cat” True! d > c le Less than or equal to “dog” le “cat” False! d > c ge Greater than or equal to “dog” ge “cat” True! d > c eq Equal to “cat” eq “cat” True! c = c ne Not equal to “cat” eq “Cat” -
Functions in C
Functions in C Fortran 90 has three kinds of units: a program unit, subroutine units and function units. In C, all units are functions. For example, the C counterpart to the Fortran 90 program unit is the function named main: #include <stdio.h> main () /* main */ f float w, x, y, z; int i, j, k; w = 0.5; x = 5.0; y = 10.0; z = x + y * w; i = j = k = 5; printf("x = %f, y = %f, z = %f n", x, y, z); printf("i = %d, j = %d, k = %dnn", i, j, k); /* main */ n g Every C program must have a function named main; it’s the func- tion where the program begins execution. C also has a bunch of standard library functions, which are functions that come predefined for everyone to use. 1 Standard Library Functions in C1 C has a bunch of standard library functions that everyone gets to use for free. They are analogous to Fortran 90’s intrinsic functions, but they’re not quite the same. Why? Because Fortran 90’s intrinsic functions are built directly into the language, while C’s library functions are not really built into the language as such; you could replace them with your own if you wanted. Here’s some example standard library functions in C: Function Return Type Return Value #include file printf int number of characters written stdio.h Print (output) to standard output (the terminal) in the given format scanf int number of items input stdio.h Scan (input) from standard input (the keyboard) in the given format isalpha int Boolean: is argument a letter? ctype.h isdigit int Boolean: is argument a digit? ctype.h strcpy char [ ] string containing copy string.h Copy a string into another (empty) string strcmp int comparison of two strings string.h Lexical comparison of two strings; result is index in which strings differ: negative value if first string less than second, positive if vice versa, zero if equal sqrt float square root of argument math.h pow float 1st argument raised to 2nd argument math.h 1 Brian W. -
Coexecutability for Efficient Verification of Data Model Updates
Coexecutability for Efficient Verification of Data Model Updates Ivan Bocic´∗, Tevfik Bultany Department of Computer Science University of California, Santa Barbara, USA ∗ [email protected] y [email protected] Abstract—Modern applications use back-end data stores for 1 class PostsController persistent data. Automated verification of the code that updates 2 def destroy_tags the data store would prevent bugs that can cause loss or 3 ... 4 posts = Post.where(id: params[:post_ids]) corruption of data. In this paper, we focus on the most challenging 5 ... part of this problem: automated verification of code that updates 6 posts.each do |p| the data store and contains loops. Due to dependencies between 7 p.tags.destroy_all! loop iterations, verification of code that contains loops is a hard 8 end problem, and typically requires manual assistance in the form of 9 ... loop invariants. We present a fully automated technique that 10 end 11 end improves verifiability of loops. We first define coexecution, a method for modeling loop iterations that simplifies automated Fig. 1. An Example Action reasoning about loops. Then, we present a fully automated static program analysis that detects whether the behavior of In our earlier work [5], we demonstrated that one can a given loop can be modeled using coexecution. We provide check invariants about the data store by translating verification a customized verification technique for coexecutable loops that queries about actions to satisfiability queries in First Order results in more effective verification. In our experiments we Logic (FOL), and then using an automated FOL theorem observed that, in 45% of cases, modeling loops using coexecution reduces verification time between 1 and 4 orders of magnitude. -
Functional Programming Patterns in Scala and Clojure Write Lean Programs for the JVM
Early Praise for Functional Programming Patterns This book is an absolute gem and should be required reading for anybody looking to transition from OO to FP. It is an extremely well-built safety rope for those crossing the bridge between two very different worlds. Consider this mandatory reading. ➤ Colin Yates, technical team leader at QFI Consulting, LLP This book sticks to the meat and potatoes of what functional programming can do for the object-oriented JVM programmer. The functional patterns are sectioned in the back of the book separate from the functional replacements of the object-oriented patterns, making the book handy reference material. As a Scala programmer, I even picked up some new tricks along the read. ➤ Justin James, developer with Full Stack Apps This book is good for those who have dabbled a bit in Clojure or Scala but are not really comfortable with it; the ideal audience is seasoned OO programmers looking to adopt a functional style, as it gives those programmers a guide for transitioning away from the patterns they are comfortable with. ➤ Rod Hilton, Java developer and PhD candidate at the University of Colorado Functional Programming Patterns in Scala and Clojure Write Lean Programs for the JVM Michael Bevilacqua-Linn 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. -
Python 3 Types in the Wild:A Tale of Two Type Systems
Python 3 Types in the Wild: A Tale of Two Type Systems Ingkarat Rak-amnouykit Daniel McCrevan Ana Milanova Rensselaer Polytechnic Institute Rensselaer Polytechnic Institute Rensselaer Polytechnic Institute New York, USA New York, USA New York, USA [email protected] [email protected] [email protected] Martin Hirzel Julian Dolby IBM TJ Watson Research Center IBM TJ Watson Research Center New York, USA New York, USA [email protected] [email protected] Abstract ACM Reference Format: Python 3 is a highly dynamic language, but it has introduced Ingkarat Rak-amnouykit, Daniel McCrevan, Ana Milanova, Martin a syntax for expressing types with PEP484. This paper ex- Hirzel, and Julian Dolby. 2020. Python 3 Types in the Wild: A Tale of Two Type Systems. In Proceedings of the 16th ACM SIGPLAN plores how developers use these type annotations, the type International Symposium on Dynamic Languages (DLS ’20), Novem- system semantics provided by type checking and inference ber 17, 2020, Virtual, USA. ACM, New York, NY, USA, 14 pages. tools, and the performance of these tools. We evaluate the https://doi.org/10.1145/3426422.3426981 types and tools on a corpus of public GitHub repositories. We review MyPy and PyType, two canonical static type checking 1 Introduction and inference tools, and their distinct approaches to type Dynamic languages in general and Python in particular1 analysis. We then address three research questions: (i) How are increasingly popular. Python is particularly popular for often and in what ways do developers use Python 3 types? machine learning and data science2. A defining feature of (ii) Which type errors do developers make? (iii) How do type dynamic languages is dynamic typing, which, essentially, for- errors from different tools compare? goes type annotations, allows variables to change type and Surprisingly, when developers use static types, the code does nearly all type checking at runtime. -
The Grace Programming Language Draft Specification Version 0.5. 2025" (2015)
Portland State University PDXScholar Computer Science Faculty Publications and Presentations Computer Science 2015 The Grace Programming Language Draft Specification ersionV 0.5. 2025 Andrew P. Black Portland State University, [email protected] Kim B. Bruce James Noble Follow this and additional works at: https://pdxscholar.library.pdx.edu/compsci_fac Part of the Programming Languages and Compilers Commons Let us know how access to this document benefits ou.y Citation Details Black, Andrew P.; Bruce, Kim B.; and Noble, James, "The Grace Programming Language Draft Specification Version 0.5. 2025" (2015). Computer Science Faculty Publications and Presentations. 140. https://pdxscholar.library.pdx.edu/compsci_fac/140 This Working Paper is brought to you for free and open access. It has been accepted for inclusion in Computer Science Faculty Publications and Presentations by an authorized administrator of PDXScholar. Please contact us if we can make this document more accessible: [email protected]. The Grace Programming Language Draft Specification Version 0.5.2025 Andrew P. Black Kim B. Bruce James Noble April 2, 2015 1 Introduction This is a specification of the Grace Programming Language. This specifica- tion is notably incomplete, and everything is subject to change. In particular, this version does not address: • James IWE MUST COMMIT TO CLASS SYNTAX!J • the library, especially collections and collection literals • static type system (although we’ve made a start) • module system James Ishould write up from DYLA paperJ • dialects • the abstract top-level method, as a marker for abstract methods, • identifier resolution rule. • metadata (Java’s @annotations, C] attributes, final, abstract etc) James Ishould add this tooJ Kim INeed to add syntax, but not necessarily details of which attributes are in language (yet)J • immutable data and pure methods.