C++ Structures in Addition to Naming Places and Processes, an Identifier
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Java Programming Standards & Reference Guide
Java Programming Standards & Reference Guide Version 3.2 Office of Information & Technology Department of Veterans Affairs Java Programming Standards & Reference Guide, Version 3.2 REVISION HISTORY DATE VER. DESCRIPTION AUTHOR CONTRIBUTORS 10-26-15 3.2 Added Logging Sid Everhart JSC Standards , updated Vic Pezzolla checkstyle installation instructions and package name rules. 11-14-14 3.1 Added ground rules for Vic Pezzolla JSC enforcement 9-26-14 3.0 Document is continually Raymond JSC and several being edited for Steele OI&T noteworthy technical accuracy and / PD Subject Matter compliance to JSC Experts (SMEs) standards. 12-1-09 2.0 Document Updated Michael Huneycutt Sr 4-7-05 1.2 Document Updated Sachin Mai L Vo Sharma Lyn D Teague Rajesh Somannair Katherine Stark Niharika Goyal Ron Ruzbacki 3-4-05 1.0 Document Created Sachin Sharma i Java Programming Standards & Reference Guide, Version 3.2 ABSTRACT The VA Java Development Community has been establishing standards, capturing industry best practices, and applying the insight of experienced (and seasoned) VA developers to develop this “Java Programming Standards & Reference Guide”. The Java Standards Committee (JSC) team is encouraging the use of CheckStyle (in the Eclipse IDE environment) to quickly scan Java code, to locate Java programming standard errors, find inconsistencies, and generally help build program conformance. The benefits of writing quality Java code infused with consistent coding and documentation standards is critical to the efforts of the Department of Veterans Affairs (VA). This document stands for the quality, readability, consistency and maintainability of code development and it applies to all VA Java programmers (including contractors). -
A Hybrid Static Type Inference Framework with Neural
HiTyper: A Hybrid Static Type Inference Framework with Neural Prediction Yun Peng Zongjie Li Cuiyun Gao∗ The Chinese University of Hong Kong Harbin Institute of Technology Harbin Institute of Technology Hong Kong, China Shenzhen, China Shenzhen, China [email protected] [email protected] [email protected] Bowei Gao David Lo Michael Lyu Harbin Institute of Technology Singapore Management University The Chinese University of Hong Kong Shenzhen, China Singapore Hong Kong, China [email protected] [email protected] [email protected] ABSTRACT also supports type annotations in the Python Enhancement Pro- Type inference for dynamic programming languages is an impor- posals (PEP) [21, 22, 39, 43]. tant yet challenging task. By leveraging the natural language in- Type prediction is a popular task performed by most attempts. formation of existing human annotations, deep neural networks Traditional static type inference techniques [4, 9, 14, 17, 36] and outperform other traditional techniques and become the state-of- type inference tools such as Pytype [34], Pysonar2 [33], and Pyre the-art (SOTA) in this task. However, they are facing some new Infer [31] can predict sound results for the variables with enough challenges, such as fixed type set, type drift, type correctness, and static constraints, e.g., a = 1, but are unable to handle the vari- composite type prediction. ables with few static constraints, e.g. most function arguments. To mitigate the challenges, in this paper, we propose a hybrid On the other hand, dynamic type inference techniques [3, 37] and type inference framework named HiTyper, which integrates static type checkers simulate the workflow of functions and solve types inference into deep learning (DL) models for more accurate type according to input cases and typing rules. -
ACDT: Architected Composite Data Types Trading-In Unfettered Data Access for Improved Execution
ACDT: Architected Composite Data Types Trading-in Unfettered Data Access for Improved Execution Andres Marquez∗, Joseph Manzano∗, Shuaiwen Leon Song∗, Benoˆıt Meistery Sunil Shresthaz, Thomas St. Johnz and Guang Gaoz ∗Pacific Northwest National Laboratory fandres.marquez,joseph.manzano,[email protected] yReservoir Labs [email protected] zUniversity of Delaware fshrestha,stjohn,[email protected] Abstract— reduction approaches associated with improved data locality, obtained through optimized data and computation distribution. With Exascale performance and its challenges in mind, one ubiquitous concern among architects is energy efficiency. In the SW-stack we foresee the runtime system to have a Petascale systems projected to Exascale systems are unsustainable particular important role to contribute to the solution of the at current power consumption rates. One major contributor power challenge. It is here where the massive concurrency is to system-wide power consumption is the number of memory managed and where judicious data layouts [11] and data move- operations leading to data movement and management techniques ments are orchestrated. With that in mind, we set to investigate applied by the runtime system. To address this problem, we on how to improve efficiency of a massively multithreaded present the concept of the Architected Composite Data Types adaptive runtime system in managing and moving data, and the (ACDT) framework. The framework is made aware of data trade-offs an improved data management efficiency requires. composites, assigning them a specific layout, transformations Specifically, in the context of run-time system (RTS), we and operators. Data manipulation overhead is amortized over a explore the power efficiency potential that data compression larger number of elements and program performance and power efficiency can be significantly improved. -
Declaring Data Member Public C
Declaring Data Member Public C Rickard brooch stickily. Interceptive and hamulate Connie enure, but Norbert crossways extinguishes her patroness. Is Mario estimated or electrotonic when strangulating some moribundity deified deeply? Optimize for declaring data member public If dynamic allocation is necessary, prefer to keep ownership with the code that allocated it. This process of creating an object from a class is known as instantiation. Here is the quite surprising output of the program. Data attributes need not be declared; like local variables, they spring into existence when they are first assigned to. The term __________ means the ability to takemany forms. In many cases, this is not a problem, but it is a problem in some cases. Use rvalue references only in certain special cases listed below. By default, functions and data members of the class are public. How many data members should be in every class and why? Is it acceptable to omit default constructors in a class? For accessing the data, the declaration of a friend function should be done inside the body of a class starting with the keyword friend. The constructor is declared much like a normal member function but it will share the name of the class and it has no return value. Spirit would be impossible without it. The basic idea is really very simple. Giving sensible names to types and variables is much better than using obscure names that you must then explain through comments. Special member functions called constructors and destructors. This makes it impossible for the class to ensure that invariant properties of that variable are respected. -
Evaluating Variability Modeling Techniques for Supporting Cyber-Physical System Product Line Engineering
This paper will be presented at System Analysis and Modeling (SAM) Conference 2016 (http://sdl-forum.org/Events/SAM2016/index.htm) Evaluating Variability Modeling Techniques for Supporting Cyber-Physical System Product Line Engineering Safdar Aqeel Safdar 1, Tao Yue1,2, Shaukat Ali1, Hong Lu1 1Simula Research Laboratory, Oslo, Norway 2 University of Oslo, Oslo, Norway {safdar, tao, shaukat, honglu}@simula.no Abstract. Modern society is increasingly dependent on Cyber-Physical Systems (CPSs) in diverse domains such as aerospace, energy and healthcare. Employing Product Line Engineering (PLE) in CPSs is cost-effective in terms of reducing production cost, and achieving high productivity of a CPS development process as well as higher quality of produced CPSs. To apply CPS PLE in practice, one needs to first select an appropriate variability modeling technique (VMT), with which variabilities of a CPS Product Line (PL) can be specified. In this paper, we proposed a set of basic and CPS-specific variation point (VP) types and modeling requirements for proposing CPS-specific VMTs. Based on the proposed set of VP types (basic and CPS-specific) and modeling requirements, we evaluated four VMTs: Feature Modeling, Cardinality Based Feature Modeling, Common Variability Language, and SimPL (a variability modeling technique dedicated to CPS PLE), with a real-world case study. Evaluation results show that none of the selected VMTs can capture all the basic and CPS-specific VP and meet all the modeling requirements. Therefore, there is a need to extend existing techniques or propose new ones to satisfy all the requirements. Keywords: Product Line Engineering, Variability Modeling, and Cyber- Physical Systems 1 Introduction Cyber-Physical Systems (CPSs) integrate computation and physical processes and their embedded computers and networks monitor and control physical processes by often relying on closed feedback loops [1, 2]. -
UML Profile for Communicating Systems a New UML Profile for the Specification and Description of Internet Communication and Signaling Protocols
UML Profile for Communicating Systems A New UML Profile for the Specification and Description of Internet Communication and Signaling Protocols Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakultäten der Georg-August-Universität zu Göttingen vorgelegt von Constantin Werner aus Salzgitter-Bad Göttingen 2006 D7 Referent: Prof. Dr. Dieter Hogrefe Korreferent: Prof. Dr. Jens Grabowski Tag der mündlichen Prüfung: 30.10.2006 ii Abstract This thesis presents a new Unified Modeling Language 2 (UML) profile for communicating systems. It is developed for the unambiguous, executable specification and description of communication and signaling protocols for the Internet. This profile allows to analyze, simulate and validate a communication protocol specification in the UML before its implementation. This profile is driven by the experience and intelligibility of the Specification and Description Language (SDL) for telecommunication protocol engineering. However, as shown in this thesis, SDL is not optimally suited for specifying communication protocols for the Internet due to their diverse nature. Therefore, this profile features new high-level language concepts rendering the specification and description of Internet protocols more intuitively while abstracting from concrete implementation issues. Due to its support of several concrete notations, this profile is designed to work with a number of UML compliant modeling tools. In contrast to other proposals, this profile binds the informal UML semantics with many semantic variation points by defining formal constraints for the profile definition and providing a mapping specification to SDL by the Object Constraint Language. In addition, the profile incorporates extension points to enable mappings to many formal description languages including SDL. To demonstrate the usability of the profile, a case study of a concrete Internet signaling protocol is presented. -
Data Types and Variables
Color profile: Generic CMYK printer profile Composite Default screen Complete Reference / Visual Basic 2005: The Complete Reference / Petrusha / 226033-5 / Chapter 2 2 Data Types and Variables his chapter will begin by examining the intrinsic data types supported by Visual Basic and relating them to their corresponding types available in the .NET Framework’s Common TType System. It will then examine the ways in which variables are declared in Visual Basic and discuss variable scope, visibility, and lifetime. The chapter will conclude with a discussion of boxing and unboxing (that is, of converting between value types and reference types). Visual Basic Data Types At the center of any development or runtime environment, including Visual Basic and the .NET Common Language Runtime (CLR), is a type system. An individual type consists of the following two items: • A set of values. • A set of rules to convert every value not in the type into a value in the type. (For these rules, see Appendix F.) Of course, every value of another type cannot always be converted to a value of the type; one of the more common rules in this case is to throw an InvalidCastException, indicating that conversion is not possible. Scalar or primitive types are types that contain a single value. Visual Basic 2005 supports two basic kinds of scalar or primitive data types: structured data types and reference data types. All data types are inherited from either of two basic types in the .NET Framework Class Library. Reference types are derived from System.Object. Structured data types are derived from the System.ValueType class, which in turn is derived from the System.Object class. -
DRAFT1.2 Methods
HL7 v3.0 Data Types Specification - Version 0.9 Table of Contents Abstract . 1 1 Introduction . 2 1.1 Goals . 3 DRAFT1.2 Methods . 6 1.2.1 Analysis of Semantic Fields . 7 1.2.2 Form of Data Type Definitions . 10 1.2.3 Generalized Types . 11 1.2.4 Generic Types . 12 1.2.5 Collections . 15 1.2.6 The Meta Model . 18 1.2.7 Implicit Type Conversion . 22 1.2.8 Literals . 26 1.2.9 Instance Notation . 26 1.2.10 Typus typorum: Boolean . 28 1.2.11 Incomplete Information . 31 1.2.12 Update Semantics . 33 2 Text . 36 2.1 Introduction . 36 2.1.1 From Characters to Strings . 36 2.1.2 Display Properties . 37 2.1.3 Encoding of appearance . 37 2.1.4 From appearance of text to multimedial information . 39 2.1.5 Pulling the pieces together . 40 2.2 Character String . 40 2.2.1 The Unicode . 41 2.2.2 No Escape Sequences . 42 2.2.3 ITS Responsibilities . 42 2.2.4 HL7 Applications are "Black Boxes" . 43 2.2.5 No Penalty for Legacy Systems . 44 2.2.6 Unicode and XML . 47 2.3 Free Text . 47 2.3.1 Multimedia Enabled Free Text . 48 2.3.2 Binary Data . 55 2.3.3 Outstanding Issues . 57 3 Things, Concepts, and Qualities . 58 3.1 Overview of the Problem Space . 58 3.1.1 Concept vs. Instance . 58 3.1.2 Real World vs. Artificial Technical World . 59 3.1.3 Segmentation of the Semantic Field . -
Csci 555: Functional Programming Functional Programming in Scala Functional Data Structures
CSci 555: Functional Programming Functional Programming in Scala Functional Data Structures H. Conrad Cunningham 6 March 2019 Contents 3 Functional Data Structures 2 3.1 Introduction . .2 3.2 A List algebraic data type . .2 3.2.1 Algebraic data types . .2 3.2.2 ADT confusion . .3 3.2.3 Using a Scala trait . .3 3.2.3.1 Aside on Haskell . .4 3.2.4 Polymorphism . .4 3.2.5 Variance . .5 3.2.5.1 Covariance and contravariance . .5 3.2.5.2 Function subtypes . .6 3.2.6 Defining functions in companion object . .7 3.2.7 Function to sum a list . .7 3.2.8 Function to multiply a list . .9 3.2.9 Function to remove adjacent duplicates . .9 3.2.10 Variadic function apply ................... 11 3.3 Data sharing . 11 3.3.1 Function to take tail of list . 12 3.3.2 Function to drop from beginning of list . 13 3.3.3 Function to append lists . 14 3.4 Other list functions . 15 3.4.1 Tail recursive function reverse . 15 3.4.2 Higher-order function dropWhile . 17 3.4.3 Curried function dropWhile . 17 3.5 Generalizing to Higher Order Functions . 18 3.5.1 Fold Right . 18 3.5.2 Fold Left . 22 3.5.3 Map . 23 1 3.5.4 Filter . 25 3.5.5 Flat Map . 26 3.6 Classic algorithms on lists . 27 3.6.1 Insertion sort and bounded generics . 27 3.6.2 Merge sort . 29 3.7 Lists in the Scala standard library . -
Classes in C++
Classes in C++ Bryce Boe 2012/08/15 CS32, Summer 2012 B Overview • Finish Sor?ng recap • Thinking object oriented recap • Classes in C++ • Building a class in C++ (real ?me demo) Sor?ng recap • Bubble sort • Inser?on sort • Selec?on sort • Merge sort • Heapsort • Quicksort Thinking object oriented recap • Language as an influence of thought process • OO concepts – Separaon of interface and implementaon – Informaon hiding – Inheritance • Wri?ng reusable code Exci?ng Note for Today • The gcc compiler now requires C++ to build – Essen?ally means parts of the gcc compiler are wriVen in C++ • hp://gcc.gnu.org/git/? p=gcc.git;a=commit;h=2b15d2ba7eb3a25d]1 5a7300f4ee7a141ee8539 Structures • Structures provide a way to organize data • Structures in C++ are essen?ally classes, not true in C Classes • an object is a variable that has member func?ons (instance methods) • a class is a data type whose variables are objects • Class – Describe the kind of values the variables hold (state) – Describe the member func?ons (behavior) Terminology • The book uses member to mean a par?cular instance of a class • The book uses members to mean aributes of a class (variables and methods) • Funcon and method are somewhat used interchangeably • Similar: – member variable = instance variable – member method = instance method Classes • Provide encapsulaon – Combining a number of items, such as variables and func?ons, into a single package, such as an object of some class (or instance of the class) Scope Resolu?on Operator • ClassName::method_name • Used to iden?fy -
Ata Lements for Mergency Epartment Ystems
D ata E lements for E mergency D epartment S ystems Release 1.0 U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES CDCCENTERS FOR DISEASE CONTROL AND PREVENTION D ata E lements for E mergency D epartment S ystems Release 1.0 National Center for Injury Prevention and Control Atlanta, Georgia 1997 Data Elements for Emergency Department Systems, Release 1.0 (DEEDS) is the result of contributions by participants in the National Workshop on Emergency Department Data, held January 23-25, 1996, in Atlanta, Georgia, subsequent review and comment by individuals who read Release 1.0 in draft form, and finalization by a multidisciplinary writing committee. DEEDS is a set of recommendations published by the National Center for Injury Prevention and Control of the Centers for Disease Control and Prevention: Centers for Disease Control and Prevention David Satcher, MD, PhD, Director National Center for Injury Prevention and Control Mark L. Rosenberg, MD, MPP, Director Division of Acute Care, Rehabilitation Research, and Disability Prevention Richard J. Waxweiler, PhD, Director Acute Care Team Daniel A. Pollock, MD, Leader Production services were provided by the staff of the Office of Communication Resources, National Center for Injury Prevention and Control, and the Management Analysis and Services Office: Editing Valerie R. Johnson Cover Design and Layout Barbara B. Lord Use of trade names is for identification only and does not constitute endorsement by the U.S. Department of Health and Human Services. This document and subsequent revisions can be found at the National Center for Injury Prevention and Control Web site: http://www.cdc.gov/ncipc/pub-res/deedspage.htm Suggested Citation: National Center for Injury Prevention and Control. -
Fundamental Programming Concepts
APPENDIX A Fundamental Programming Concepts The following information is for readers who are new to programming and need a primer on some fundamental programming concepts. If you have programmed in another language, chances are the concepts presented in this appendix are not new to you. You should, however, review the material briefly to become familiar with the C# syntax. Working with Variables and Data Types Variables in programming languages store values that can change while the program executes. For example, if you wanted to count the number of times a user tries to log in to an application, you could use a variable to track the number of attempts. A variable is a memory location where a value is stored. Using the variable, your program can read or alter the value stored in memory. Before you use a variable in your program, however, you must declare it. When you declare a variable, the compiler also needs to know what kind of data will be stored at the memory location. For example, will it be numbers or letters? If the variable will store numbers, how large can a number be? Will the variable store decimals or only whole numbers? You answer these questions by assigning a data type to the variable. A login counter, for example, only needs to hold positive whole numbers. The following code demonstrates how you declare a variable named counter in C# with an integer data type: int counter; Specifying the data type is referred to as strong typing. Strong typing results in more efficient memory management, faster execution, and compiler type checking, all of which reduces runtime errors.