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Preview Objective-C Tutorial (PDF Version)
Objective-C Objective-C About the Tutorial Objective-C is a general-purpose, object-oriented programming language that adds Smalltalk-style messaging to the C programming language. This is the main programming language used by Apple for the OS X and iOS operating systems and their respective APIs, Cocoa and Cocoa Touch. This reference will take you through simple and practical approach while learning Objective-C Programming language. Audience This reference has been prepared for the beginners to help them understand basic to advanced concepts related to Objective-C Programming languages. Prerequisites Before you start doing practice with various types of examples given in this reference, I'm making an assumption that you are already aware about what is a computer program, and what is a computer programming language? Copyright & Disclaimer © Copyright 2015 by Tutorials Point (I) Pvt. Ltd. All the content and graphics published in this e-book are the property of Tutorials Point (I) Pvt. Ltd. The user of this e-book can retain a copy for future reference but commercial use of this data is not allowed. Distribution or republishing any content or a part of the content of this e-book in any manner is also not allowed without written consent of the publisher. We strive to update the contents of our website and tutorials as timely and as precisely as possible, however, the contents may contain inaccuracies or errors. Tutorials Point (I) Pvt. Ltd. provides no guarantee regarding the accuracy, timeliness or completeness of our website or its contents including this tutorial. If you discover any errors on our website or in this tutorial, please notify us at [email protected] ii Objective-C Table of Contents About the Tutorial .................................................................................................................................. -
The LLVM Instruction Set and Compilation Strategy
The LLVM Instruction Set and Compilation Strategy Chris Lattner Vikram Adve University of Illinois at Urbana-Champaign lattner,vadve ¡ @cs.uiuc.edu Abstract This document introduces the LLVM compiler infrastructure and instruction set, a simple approach that enables sophisticated code transformations at link time, runtime, and in the field. It is a pragmatic approach to compilation, interfering with programmers and tools as little as possible, while still retaining extensive high-level information from source-level compilers for later stages of an application’s lifetime. We describe the LLVM instruction set, the design of the LLVM system, and some of its key components. 1 Introduction Modern programming languages and software practices aim to support more reliable, flexible, and powerful software applications, increase programmer productivity, and provide higher level semantic information to the compiler. Un- fortunately, traditional approaches to compilation either fail to extract sufficient performance from the program (by not using interprocedural analysis or profile information) or interfere with the build process substantially (by requiring build scripts to be modified for either profiling or interprocedural optimization). Furthermore, they do not support optimization either at runtime or after an application has been installed at an end-user’s site, when the most relevant information about actual usage patterns would be available. The LLVM Compilation Strategy is designed to enable effective multi-stage optimization (at compile-time, link-time, runtime, and offline) and more effective profile-driven optimization, and to do so without changes to the traditional build process or programmer intervention. LLVM (Low Level Virtual Machine) is a compilation strategy that uses a low-level virtual instruction set with rich type information as a common code representation for all phases of compilation. -
“A Magnetzed Needle and a Steady Hand”
“A Magne)zed Needle and a Steady Hand” Alternaves in the modern world of Integrated Development Environments Jennifer Wood CSCI 5828 Spring 2012 Real Programmers hp://xkcd.com/378/ For the rest of us • Modern Integrated Development Environments (IDE) – A one-stop shop with mul)ple features that can be easily accessed by the developer (without switching modes or ac)vang other u)li)es) to ease the task of creang soYware – A mul)tude of IDEs exist for each programming language (Java, C++, Python, etc.) and each plaorm (desktops, cell phones, web-based, etc.) – Some IDEs can handle mul)ple programming languages, but most are based in just one – There are many good free IDEs out there, but you can also pay for func)onality from $ to $$$$ – IDEs are like opinions, everyone has one and everyone thinks everyone else's s)nks Why are IDEs a good thing? • They aack many of the sources of accidental difficul)es in soYware development by having: – Real-)me protec)on from fault generang typos and bad syntax – High levels of abstrac)on to keep developers from being forced to redevelop basic (and not so basic) classes and structures for every project – IDE increases the power of many development tools by merging them into one that provides “integrated libraries, unified file formats, and pipes and filters. As a result, conceptual structures that in principle could always call, feed, and use one another can indeed easily do so in prac)ce.” (Brooks, 1987). • A core focus of IDE developers is con)nuous improvement in transparency to minimize searching for func)ons -
Programming Java for OS X
Programming Java for OS X hat’s so different about Java on a Mac? Pure Java applica- tions run on any operating system that supports Java. W Popular Java tools run on OS X. From the developer’s point of view, Java is Java, no matter where it runs. Users do not agree. To an OS X user, pure Java applications that ignore the feel and features of OS X are less desirable, meaning the customers will take their money elsewhere. Fewer sales translates into unhappy managers and all the awkwardness that follows. In this book, I show how to build GUIs that feel and behave like OS X users expect them to behave. I explain development tools and libraries found on the Mac. I explore bundling of Java applications for deployment on OS X. I also discuss interfacing Java with other languages commonly used on the Mac. This chapter is about the background and basics of Java develop- ment on OS X. I explain the history of Java development. I show you around Apple’s developer Web site. Finally, I go over the IDEs commonly used for Java development on the Mac. In This Chapter Reviewing Apple Java History Exploring the history of Apple embraced Java technologies long before the first version of Java on Apple computers OS X graced a blue and white Mac tower. Refugees from the old Installing developer tan Macs of the 1990s may vaguely remember using what was tools on OS X called the MRJ when their PC counterparts were busy using JVMs. Looking at the MRJ stands for Mac OS Runtime for Java. -
What Is LLVM? and a Status Update
What is LLVM? And a Status Update. Approved for public release Hal Finkel Leadership Computing Facility Argonne National Laboratory Clang, LLVM, etc. ✔ LLVM is a liberally-licensed(*) infrastructure for creating compilers, other toolchain components, and JIT compilation engines. ✔ Clang is a modern C++ frontend for LLVM ✔ LLVM and Clang will play significant roles in exascale computing systems! (*) Now under the Apache 2 license with the LLVM Exception LLVM/Clang is both a research platform and a production-quality compiler. 2 A role in exascale? Current/Future HPC vendors are already involved (plus many others)... Apple + Google Intel (Many millions invested annually) + many others (Qualcomm, Sony, Microsoft, Facebook, Ericcson, etc.) ARM LLVM IBM Cray NVIDIA (and PGI) Academia, Labs, etc. AMD 3 What is LLVM: LLVM is a multi-architecture infrastructure for constructing compilers and other toolchain components. LLVM is not a “low-level virtual machine”! LLVM IR Architecture-independent simplification Architecture-aware optimization (e.g. vectorization) Assembly printing, binary generation, or JIT execution Backends (Type legalization, instruction selection, register allocation, etc.) 4 What is Clang: LLVM IR Clang is a C++ frontend for LLVM... Code generation Parsing and C++ Source semantic analysis (C++14, C11, etc.) Static analysis ● For basic compilation, Clang works just like gcc – using clang instead of gcc, or clang++ instead of g++, in your makefile will likely “just work.” ● Clang has a scalable LTO, check out: https://clang.llvm.org/docs/ThinLTO.html 5 The core LLVM compiler-infrastructure components are one of the subprojects in the LLVM project. These components are also referred to as “LLVM.” 6 What About Flang? ● Started as a collaboration between DOE and NVIDIA/PGI. -
LAZARUS FREE PASCAL Développement Rapide
LAZARUS FREE PASCAL Développement rapide Matthieu GIROUX Programmation Livre de coaching créatif par les solutions ISBN 9791092732214 et 9782953125177 Éditions LIBERLOG Éditeur n° 978-2-9531251 Droits d'auteur RENNES 2009 Dépôt Légal RENNES 2010 Sommaire A) À lire................................................................................................................5 B) LAZARUS FREE PASCAL.............................................................................9 C) Programmer facilement..................................................................................25 D) Le langage PASCAL......................................................................................44 E) Calculs et types complexes.............................................................................60 F) Les boucles.....................................................................................................74 G) Créer ses propres types..................................................................................81 H) Programmation procédurale avancée.............................................................95 I) Gérer les erreurs............................................................................................105 J) Ma première application................................................................................115 K) Bien développer...........................................................................................123 L) L'Objet..........................................................................................................129 -
A DSL for Resource Checking Using Finite State Automaton-Driven Symbolic Execution Code
Open Comput. Sci. 2021; 11:107–115 Research Article Endre Fülöp and Norbert Pataki* A DSL for Resource Checking Using Finite State Automaton-Driven Symbolic Execution https://doi.org/10.1515/comp-2020-0120 code. Compilers validate the syntactic elements, referred Received Mar 31, 2020; accepted May 28, 2020 variables, called functions to name a few. However, many problems may remain undiscovered. Abstract: Static analysis is an essential way to find code Static analysis is a widely-used method which is by smells and bugs. It checks the source code without exe- definition the act of uncovering properties and reasoning cution and no test cases are required, therefore its cost is about software without observing its runtime behaviour, lower than testing. Moreover, static analysis can help in restricting the scope of tools to those which operate on the software engineering comprehensively, since static anal- source representation, the code written in a single or mul- ysis can be used for the validation of code conventions, tiple programming languages. While most static analysis for measuring software complexity and for executing code methods are designed to detect anomalies (called bugs) in refactorings as well. Symbolic execution is a static analy- software code, the methods they employ are varied [1]. One sis method where the variables (e.g. input data) are inter- major difference is the level of abstraction at which the preted with symbolic values. code is represented [2]. Because static analysis is closely Clang Static Analyzer is a powerful symbolic execution related to the compilation of the code, the formats used engine based on the Clang compiler infrastructure that to represent the different abstractions are not unique to can be used with C, C++ and Objective-C. -
SMT-Based Refutation of Spurious Bug Reports in the Clang Static Analyzer
SMT-Based Refutation of Spurious Bug Reports in the Clang Static Analyzer Mikhail R. Gadelha∗, Enrico Steffinlongo∗, Lucas C. Cordeiroy, Bernd Fischerz, and Denis A. Nicole∗ ∗University of Southampton, UK. yUniversity of Manchester, UK. zStellenbosch University, South Africa. Abstract—We describe and evaluate a bug refutation extension bit in a is one, and (a & 1) ˆ 1 inverts the last bit in a. for the Clang Static Analyzer (CSA) that addresses the limi- The analyzer, however, produces the following (spurious) bug tations of the existing built-in constraint solver. In particular, report when analyzing the program: we complement CSA’s existing heuristics that remove spurious bug reports. We encode the path constraints produced by CSA as Satisfiability Modulo Theories (SMT) problems, use SMT main.c:4:12: warning: Dereference of null solvers to precisely check them for satisfiability, and remove pointer (loaded from variable ’z’) bug reports whose associated path constraints are unsatisfi- return *z; able. Our refutation extension refutes spurious bug reports in ˆ˜ 8 out of 12 widely used open-source applications; on aver- age, it refutes ca. 7% of all bug reports, and never refutes 1 warning generated. any true bug report. It incurs only negligible performance overheads, and on average adds 1.2% to the runtime of the The null pointer dereference reported here means that CSA full Clang/LLVM toolchain. A demonstration is available at claims to nevertheless have found a path where the dereference https://www.youtube.com/watch?v=ylW5iRYNsGA. of z is reachable. Such spurious bug reports are in practice common; in our I. -
CUDA Flux: a Lightweight Instruction Profiler for CUDA Applications
CUDA Flux: A Lightweight Instruction Profiler for CUDA Applications Lorenz Braun Holger Froning¨ Institute of Computer Engineering Institute of Computer Engineering Heidelberg University Heidelberg University Heidelberg, Germany Heidelberg, Germany [email protected] [email protected] Abstract—GPUs are powerful, massively parallel processors, hardware, it lacks verbosity when it comes to analyzing the which require a vast amount of thread parallelism to keep their different types of instructions executed. This problem is aggra- thousands of execution units busy, and to tolerate latency when vated by the recently frequent introduction of new instructions, accessing its high-throughput memory system. Understanding the behavior of massively threaded GPU programs can be for instance floating point operations with reduced precision difficult, even though recent GPUs provide an abundance of or special function operations including Tensor Cores for ma- hardware performance counters, which collect statistics about chine learning. Similarly, information on the use of vectorized certain events. Profiling tools that assist the user in such analysis operations is often lost. Characterizing workloads on PTX for their GPUs, like NVIDIA’s nvprof and cupti, are state-of- level is desirable as PTX allows us to determine the exact types the-art. However, instrumentation based on reading hardware performance counters can be slow, in particular when the number of the instructions a kernel executes. On the contrary, nvprof of metrics is large. Furthermore, the results can be inaccurate as metrics are based on a lower-level representation called SASS. instructions are grouped to match the available set of hardware Still, even if there was an exact mapping, some information on counters. -
B-Human 2018
Team Report and Code Release 2018 Thomas R¨ofer1;2, Tim Laue2, Arne Hasselbring2, Jannik Heyen2, Bernd Poppinga2, Philip Reichenberg2, Enno R¨ohrig2, Felix Thielke2 1 Deutsches Forschungszentrum f¨urK¨unstliche Intelligenz, Enrique-Schmidt-Str. 5, 28359 Bremen, Germany 2 Universit¨atBremen, Fachbereich 3, Postfach 330440, 28334 Bremen, Germany Revision: November 14, 2018 Contents 1 Introduction 4 1.1 About Us........................................4 1.2 About the Document..................................4 2 Getting Started6 2.1 Download........................................6 2.2 Components and Configurations...........................7 2.3 Building the Code...................................8 2.3.1 Project Generation...............................8 2.3.2 Visual Studio on Windows...........................8 2.3.3 Xcode on macOS................................9 2.3.4 Linux...................................... 10 2.4 Setting Up the NAO.................................. 11 2.4.1 Requirements.................................. 11 2.4.2 Installing the Operating System....................... 12 2.4.3 Creating Robot Configuration Files for a NAO............... 12 2.4.4 Managing Wireless Configurations...................... 13 2.4.5 Installing the Robot.............................. 13 2.5 Copying the Compiled Code.............................. 13 2.6 Working with the NAO................................ 14 2.7 Starting SimRobot................................... 15 2.8 Calibrating the Robots................................. 16 2.8.1 Overall Physical -
Installing a Development Environment
IBM TRIRIGA Anywhere Version 10 Release 4.2 Installing a development environment IBM Note Before using this information and the product it supports, read the information in “Notices” on page 13. This edition applies to version 10, release 4, modification 2 of IBM TRIRIGA Anywhere and to all subsequent releases and modifications until otherwise indicated in new editions. © Copyright IBM Corporation 2014, 2015. US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents Chapter 1. Preparing the IBM TRIRIGA Trademarks .............. 15 Anywhere environment ........ 1 Installing the Android development tools..... 1 Installing the iOS development tools ...... 3 Installing the Windows development tools .... 5 Chapter 2. Installing IBM TRIRIGA Anywhere .............. 7 Chapter 3. Installing an integrated development environment ....... 9 Chapter 4. Deploying apps by using MobileFirst Studio .......... 11 Notices .............. 13 Privacy Policy Considerations ........ 14 © Copyright IBM Corp. 2014, 2015 iii iv Installing a development environment Chapter 1. Preparing the IBM TRIRIGA Anywhere environment Before you can build and deploy the IBM® TRIRIGA® Anywhere Work Task Management app, you must set up the computer on which IBM TRIRIGA Anywhere is installed. Procedure 1. Prepare the environment for building the app: Android Install the Android development tools. iOS Install the iOS development tools. Windows Install the Windows development tools 2. Install IBM TRIRIGA Anywhere 3. Optional: Install an integrated development environment. 4. Deploy the app with MobileFirst Studio. Installing the Android development tools Oracle JDK and Android SDK are required to build Android mobile apps. About this task If you install the integrated development environment, which includes MobileFirst Studio and Eclipse, you must also install the Android Development Tools (ADT) plug-in. -
Implementing Continuation Based Language in LLVM and Clang
Implementing Continuation based language in LLVM and Clang Kaito TOKUMORI Shinji KONO University of the Ryukyus University of the Ryukyus Email: [email protected] Email: [email protected] Abstract—The programming paradigm which use data seg- 1 __code f(Allocate allocate){ 2 allocate.size = 0; ments and code segments are proposed. This paradigm uses 3 goto g(allocate); Continuation based C (CbC), which a slight modified C language. 4 } 5 Code segments are units of calculation and Data segments are 6 // data segment definition sets of typed data. We use these segments as units of computation 7 // (generated automatically) 8 union Data { and meta computation. In this paper we show the implementation 9 struct Allocate { of CbC on LLVM and Clang 3.7. 10 long size; 11 } allocate; 12 }; I. A PRACTICAL CONTINUATION BASED LANGUAGE TABLE I The proposed units of programming are named code seg- CBCEXAMPLE ments and data segments. Code segments are units of calcu- lation which have no state. Data segments are sets of typed data. Code segments are connected to data segments by a meta data segment called a context. After the execution of a code have input data segments and output data segments. Data segment and its context, the next code segment (continuation) segments have two kind of dependency with code segments. is executed. First, Code segments access the contents of data segments Continuation based C (CbC) [1], hereafter referred to as using field names. So data segments should have the named CbC, is a slight modified C which supports code segments.