Studying a Minimal Object-Oriented Kernel
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18-Variables.Pdf
Mehran Sahami Handout #18 CS 106A October 12, 2007 Variables, variables, everywhere… Based on a handout by Patrick Young. Local Variables Local variables are created local to the method (or the block—see “Block Scope” section below) in which they are defined. They are destroyed when execution of the method has been completed. Local variables can only be accessed from within the method in which they are declared. Because of their transient nature, local variables cannot store persistent information about an object between method calls. Local Variables Example Consider, for example, the following snippet of code. class AnExample extends ConsoleProgram { public void methodOne { int a = readInt("Enter a: "); println("a = " + a); } public void methodTwo { int b = a; // BUG!: cannot refer to variable a in methodOne println("b = " + b); } } The variables a and b are local variables declared within different methods in the class AnExample . Because these variables are local variables, a can only be referred to within methodOne and variable b can only be accessed within methodTwo . Our attempt to initialize b using the value of a is illegal, as code in methodTwo cannot access local variables from methodOne or any other method. Because local variable values do not persist after their containing method has completed, the variable a will be destroyed when methodOne has completed execution. The next time methodOne is called, a new variable a will be created. Block Scope While we typically think of local variables as local to a particular method, in Java local variables are actually local to a block of code. While a method defines a block of code (since the opening and closing braces of the method define a block), for and while loops, if -statements, and other constructs are also considered blocks of code. -
Bit Nove Signal Interface Processor
www.audison.eu bit Nove Signal Interface Processor POWER SUPPLY CONNECTION Voltage 10.8 ÷ 15 VDC From / To Personal Computer 1 x Micro USB Operating power supply voltage 7.5 ÷ 14.4 VDC To Audison DRC AB / DRC MP 1 x AC Link Idling current 0.53 A Optical 2 sel Optical In 2 wire control +12 V enable Switched off without DRC 1 mA Mem D sel Memory D wire control GND enable Switched off with DRC 4.5 mA CROSSOVER Remote IN voltage 4 ÷ 15 VDC (1mA) Filter type Full / Hi pass / Low Pass / Band Pass Remote OUT voltage 10 ÷ 15 VDC (130 mA) Linkwitz @ 12/24 dB - Butterworth @ Filter mode and slope ART (Automatic Remote Turn ON) 2 ÷ 7 VDC 6/12/18/24 dB Crossover Frequency 68 steps @ 20 ÷ 20k Hz SIGNAL STAGE Phase control 0° / 180° Distortion - THD @ 1 kHz, 1 VRMS Output 0.005% EQUALIZER (20 ÷ 20K Hz) Bandwidth @ -3 dB 10 Hz ÷ 22 kHz S/N ratio @ A weighted Analog Input Equalizer Automatic De-Equalization N.9 Parametrics Equalizers: ±12 dB;10 pole; Master Input 102 dBA Output Equalizer 20 ÷ 20k Hz AUX Input 101.5 dBA OPTICAL IN1 / IN2 Inputs 110 dBA TIME ALIGNMENT Channel Separation @ 1 kHz 85 dBA Distance 0 ÷ 510 cm / 0 ÷ 200.8 inches Input sensitivity Pre Master 1.2 ÷ 8 VRMS Delay 0 ÷ 15 ms Input sensitivity Speaker Master 3 ÷ 20 VRMS Step 0,08 ms; 2,8 cm / 1.1 inch Input sensitivity AUX Master 0.3 ÷ 5 VRMS Fine SET 0,02 ms; 0,7 cm / 0.27 inch Input impedance Pre In / Speaker In / AUX 15 kΩ / 12 Ω / 15 kΩ GENERAL REQUIREMENTS Max Output Level (RMS) @ 0.1% THD 4 V PC connections USB 1.1 / 2.0 / 3.0 Compatible Microsoft Windows (32/64 bit): Vista, INPUT STAGE Software/PC requirements Windows 7, Windows 8, Windows 10 Low level (Pre) Ch1 ÷ Ch6; AUX L/R Video Resolution with screen resize min. -
Signedness-Agnostic Program Analysis: Precise Integer Bounds for Low-Level Code
Signedness-Agnostic Program Analysis: Precise Integer Bounds for Low-Level Code Jorge A. Navas, Peter Schachte, Harald Søndergaard, and Peter J. Stuckey Department of Computing and Information Systems, The University of Melbourne, Victoria 3010, Australia Abstract. Many compilers target common back-ends, thereby avoid- ing the need to implement the same analyses for many different source languages. This has led to interest in static analysis of LLVM code. In LLVM (and similar languages) most signedness information associated with variables has been compiled away. Current analyses of LLVM code tend to assume that either all values are signed or all are unsigned (except where the code specifies the signedness). We show how program analysis can simultaneously consider each bit-string to be both signed and un- signed, thus improving precision, and we implement the idea for the spe- cific case of integer bounds analysis. Experimental evaluation shows that this provides higher precision at little extra cost. Our approach turns out to be beneficial even when all signedness information is available, such as when analysing C or Java code. 1 Introduction The “Low Level Virtual Machine” LLVM is rapidly gaining popularity as a target for compilers for a range of programming languages. As a result, the literature on static analysis of LLVM code is growing (for example, see [2, 7, 9, 11, 12]). LLVM IR (Intermediate Representation) carefully specifies the bit- width of all integer values, but in most cases does not specify whether values are signed or unsigned. This is because, for most operations, two’s complement arithmetic (treating the inputs as signed numbers) produces the same bit-vectors as unsigned arithmetic. -
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, -
Java Static Keyword
This page was exported from - TechnicalStack Export date: Sun Sep 26 13:56:23 2021 / +0000 GMT Java static keyword Java static keyword The static keyword in java is used for memory management mainly. We can apply java static keyword with variables, methods, blocks and nested class. The static keyword belongs to the class than instance of the class. The static can be: - variable (also known as class variable) - method (also known as class method) - block - nested class 1) Java static variable If you declare any variable as static, it is known static variable. - The static variable can be used to refer the common property of all objects (that is not unique for each object) e.g. company name of employees,college name of students etc. - The static variable gets memory only once in class area at the time of class loading. Advantage of static variable It makes your program memory efficient (i.e it saves memory). Understanding problem without static variable class Student{ int rollno; String name; String college="ITS"; } Suppose there are 500 students in my college, now all instance data members will get memory each time when object is created.All student have its unique rollno and name so instance data member is good.Here, college refers to the common property of all objects.If we make it static,this field will get memory only once. Java static property is shared to all objects. Example of static variable //Program of static variable class Student8{ int rollno; String name; static String college ="ITS"; Student8(int r,String n){ -
Meta-Class Features for Large-Scale Object Categorization on a Budget
Meta-Class Features for Large-Scale Object Categorization on a Budget Alessandro Bergamo Lorenzo Torresani Dartmouth College Hanover, NH, U.S.A. faleb, [email protected] Abstract cation accuracy over a predefined set of classes, and without consideration of the computational costs of the recognition. In this paper we introduce a novel image descriptor en- We believe that these two assumptions do not meet the abling accurate object categorization even with linear mod- requirements of modern applications of large-scale object els. Akin to the popular attribute descriptors, our feature categorization. For example, test-recognition efficiency is a vector comprises the outputs of a set of classifiers evaluated fundamental requirement to be able to scale object classi- on the image. However, unlike traditional attributes which fication to Web photo repositories, such as Flickr, which represent hand-selected object classes and predefined vi- are growing at rates of several millions new photos per sual properties, our features are learned automatically and day. Furthermore, while a fixed set of object classifiers can correspond to “abstract” categories, which we name meta- be used to annotate pictures with a set of predefined tags, classes. Each meta-class is a super-category obtained by the interactive nature of searching and browsing large im- grouping a set of object classes such that, collectively, they age collections calls for the ability to allow users to define are easy to distinguish from other sets of categories. By us- their own personal query categories to be recognized and ing “learnability” of the meta-classes as criterion for fea- retrieved from the database, ideally in real-time. -
CS 61A A&S Section 3.0 Object-Oriented Programming
CS 61A A&S Section 3.0 Object-Oriented Programming | Above the line view This document should be read before Section 3.1 of the text. A second document, \Object-Oriented Programming | Below the line view," should be read after Section 3.1 and perhaps after Section 3.2; the idea is that you first learn how to use the object-oriented programming facility, then you learn how it's implemented. Object-oriented programming is a metaphor. It expresses the idea of several independent agents inside the computer, instead of a single process manipulating various data. For example, the next programming project is an adventure game, in which several people, places, and things interact. We want to be able to say things like \Ask Fred to pick up the potstickers." (Fred is a person object, and the potstickers are a thing object.) Programmers who use the object metaphor have a special vocabulary to describe the components of an object-oriented programming (OOP) system. In the example just above, \Fred" is called an instance and the general category \person" is called a class. Programming languages that support OOP let the programmer talk directly in this vocabulary; for example, every OOP language has a “define class" command in some form. For this course, we have provided an extension to Scheme that supports OOP in the style of other OOP languages. Later we shall see how these new features are implemented using Scheme capabilities that you already understand. OOP is not magic; it's a way of thinking and speaking about the structure of a program. -
Bit, Byte, and Binary
Bit, Byte, and Binary Number of Number of values 2 raised to the power Number of bytes Unit bits 1 2 1 Bit 0 / 1 2 4 2 3 8 3 4 16 4 Nibble Hexadecimal unit 5 32 5 6 64 6 7 128 7 8 256 8 1 Byte One character 9 512 9 10 1024 10 16 65,536 16 2 Number of bytes 2 raised to the power Unit 1 Byte One character 1024 10 KiloByte (Kb) Small text 1,048,576 20 MegaByte (Mb) A book 1,073,741,824 30 GigaByte (Gb) An large encyclopedia 1,099,511,627,776 40 TeraByte bit: Short for binary digit, the smallest unit of information on a machine. John Tukey, a leading statistician and adviser to five presidents first used the term in 1946. A single bit can hold only one of two values: 0 or 1. More meaningful information is obtained by combining consecutive bits into larger units. For example, a byte is composed of 8 consecutive bits. Computers are sometimes classified by the number of bits they can process at one time or by the number of bits they use to represent addresses. These two values are not always the same, which leads to confusion. For example, classifying a computer as a 32-bit machine might mean that its data registers are 32 bits wide or that it uses 32 bits to identify each address in memory. Whereas larger registers make a computer faster, using more bits for addresses enables a machine to support larger programs. -
Floating Point Arithmetic
Systems Architecture Lecture 14: Floating Point Arithmetic Jeremy R. Johnson Anatole D. Ruslanov William M. Mongan Some or all figures from Computer Organization and Design: The Hardware/Software Approach, Third Edition, by David Patterson and John Hennessy, are copyrighted material (COPYRIGHT 2004 MORGAN KAUFMANN PUBLISHERS, INC. ALL RIGHTS RESERVED). Lec 14 Systems Architecture 1 Introduction • Objective: To provide hardware support for floating point arithmetic. To understand how to represent floating point numbers in the computer and how to perform arithmetic with them. Also to learn how to use floating point arithmetic in MIPS. • Approximate arithmetic – Finite Range – Limited Precision • Topics – IEEE format for single and double precision floating point numbers – Floating point addition and multiplication – Support for floating point computation in MIPS Lec 14 Systems Architecture 2 Distribution of Floating Point Numbers e = -1 e = 0 e = 1 • 3 bit mantissa 1.00 X 2^(-1) = 1/2 1.00 X 2^0 = 1 1.00 X 2^1 = 2 1.01 X 2^(-1) = 5/8 1.01 X 2^0 = 5/4 1.01 X 2^1 = 5/2 • exponent {-1,0,1} 1.10 X 2^(-1) = 3/4 1.10 X 2^0 = 3/2 1.10 X 2^1= 3 1.11 X 2^(-1) = 7/8 1.11 X 2^0 = 7/4 1.11 X 2^1 = 7/2 0 1 2 3 Lec 14 Systems Architecture 3 Floating Point • An IEEE floating point representation consists of – A Sign Bit (no surprise) – An Exponent (“times 2 to the what?”) – Mantissa (“Significand”), which is assumed to be 1.xxxxx (thus, one bit of the mantissa is implied as 1) – This is called a normalized representation • So a mantissa = 0 really is interpreted to be 1.0, and a mantissa of all 1111 is interpreted to be 1.1111 • Special cases are used to represent denormalized mantissas (true mantissa = 0), NaN, etc., as will be discussed. -
10. Classes: an Initial Example
10. Classes: An Initial Example This is the first chapter about classes. It is also the first chapter in the first lecture about classes. Our basic coverage of classes runs until Chapter 13. 10.1. The Die Class Lecture 3 - slide 2 In this section we encounter a number of important OOP ideas, observations, and principles. We will very briefly preview many of these in a concrete way in the context of a simple initial class. Later we will discuss the ideas in depth. We use the example of a die , which is the singular form of "dice", see Program 10.1. One of the teaching assistants in 2006 argued that the class Die is a sad beginning of the story about classes. Well, it is maybe right. I think, however, that the concept of a die is a good initial example. So we will go for it! On purpose, we are concerned with use of either the singular or the plural forms of class names. The singular form is used when we wish to describe and program a single phenomenon/thing/object. The plural form is most often used for collections, to which we can add or delete (singular) objects. Notice that we can make multiple instances of a class, such as the Die class. In this way we can create a number of dice. The class Die in Program 10.1 is programmed in C#. We program a die such that each given die has a fixed maximum number of eyes, determined by the constant maxNumberOfEyes . The class encapsulates the instance variables : numberOfEyes , randomNumberSupplier , and the constant maxNumberOfEyes . -
C++ Fundamentals
C++ Fundamentals Only what you need to know Outline • Part 1 – Basic Syntax Review – C++ Definitions, Source Code Organization, Building your Code • Part 2 – Scope – Pointers and References – Dynamic Memory Allocation – Const-ness – Function Overloading • Part 3 – Type System – Brief Intro to Using Templates – C++ Data Structures – Standard Template Library Containers • Part 4 – Object Oriented Design – Classes in C++ 2 / 82 Typeface Conventions • Key concepts • Special attention required! • Code • // Comments • int x;// Language keywords 3 / 82 MOOSE Coding Standards • Capitalization –ClassName –methodName – member variable – local variable • FileNames – src/ClassName.C – include/ClassName.h • Spacing – Two spaces for each indentation level – Four spaces for initialization lists – Braces should occupy their own line – Spaces around all binary operators and declaration symbols + - * & ... • No Trailing Whitespace! • Documentation for each method (Doxygen keywords) – @param – @return – ///Doxygen Style Comment • See our wiki page for a comprehensive list https://hpcsc.inl.gov/moose/wiki/CodeStandards 4 / 82 Part 1 • Basic Syntax Review • C++ Definitions • Source Code Organization • Building your Code 5 / 82 Review: C Preprocessor Commands • “#” Should be the first character on the line – #include <iostream> – #include "myheader.h" – #define SOMEWORD value – #ifdef, #ifndef, #endif • Some predefined Macros – FILE – LINE – cplusplus 6 / 82 Review: Intrinsic Data Types Basic Type Variant(s) bool char unsigned int unsigned, long, short float double -
OMG Meta Object Facility (MOF) Core Specification
Date : October 2019 OMG Meta Object Facility (MOF) Core Specification Version 2.5.1 OMG Document Number: formal/2019-10-01 Standard document URL: https://www.omg.org/spec/MOF/2.5.1 Normative Machine-Readable Files: https://www.omg.org/spec/MOF/20131001/MOF.xmi Informative Machine-Readable Files: https://www.omg.org/spec/MOF/20131001/CMOFConstraints.ocl https://www.omg.org/spec/MOF/20131001/EMOFConstraints.ocl Copyright © 2003, Adaptive Copyright © 2003, Ceira Technologies, Inc. Copyright © 2003, Compuware Corporation Copyright © 2003, Data Access Technologies, Inc. Copyright © 2003, DSTC Copyright © 2003, Gentleware Copyright © 2003, Hewlett-Packard Copyright © 2003, International Business Machines Copyright © 2003, IONA Copyright © 2003, MetaMatrix Copyright © 2015, Object Management Group Copyright © 2003, Softeam Copyright © 2003, SUN Copyright © 2003, Telelogic AB Copyright © 2003, Unisys USE OF SPECIFICATION - TERMS, CONDITIONS & NOTICES The material in this document details an Object Management Group specification in accordance with the terms, conditions and notices set forth below. This document does not represent a commitment to implement any portion of this specification in any company's products. The information contained in this document is subject to change without notice. LICENSES The companies listed above have granted to the Object Management Group, Inc. (OMG) a nonexclusive, royalty-free, paid up, worldwide license to copy and distribute this document and to modify this document and distribute copies of the modified version. Each of the copyright holders listed above has agreed that no person shall be deemed to have infringed the copyright in the included material of any such copyright holder by reason of having used the specification set forth herein or having conformed any computer software to the specification.