Cobol Case Statement Example
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Introduction: C++ and Software Engineering
Comp151 Introduction Background Assumptions • This course assumes that you have taken COMP102/103, COMP104 or an equivalent. The topics assumed are: – Basic loop constructs, e.g., for, while, repeat, etc. – Functions –Arrays – Basic I/O – Introduction to classes – Abstract Data Types – Linked Lists – Recursion – Dynamic Objects Why Take This Course You all know how to program, so why take this course? • In COMP104 you essentially only learned “the C part” of C++ and can write “small” C++ programs. • Most of the time you write code that is (almost) the same as code that’s been written many times before. How do you avoid wasting time “re-inventing the wheel”? How do you re-use coding effort? • What if you need to write a large program and/or work with a team of other programmers? How do you maintain consistency across your large program or between the different coders? • In this course you will learn the essence of Object Oriented Programming (OOP). The goal is to teach you how to design and code large software projects. A Short “History” of Computing • Early programming languages (e.g., Basic, Fortran) were unstructured. This allowed “spaghetti code” – code with a complex and tangled structure - with goto’s and gosub’s jumping all over the place. Almost impossible to understand. • The abuses of spaghetti code led to structured programming languages supporting procedural programming (PP) – e.g., Algol, Pascal, C. • While well-written C is easier to understand, it’s still hard to write large, consistent code. This inspired researchers to borrow AI concepts (from knowledge representation, especially semantic networks) resulting in object-oriented programming (OOP )languages (e.g., Smalltalk, Simula, Eiffel, Objective C, C++, Java). -
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. -
Foundations of Computer Science I
Foundations of Computer Science I Dan R. Ghica 2014 Contents 1 Introduction 2 1.1 Basic concepts . .2 1.2 Programming the machine, a historical outlook . .2 1.3 Abstraction . .3 1.4 Functional programming: a historical outlook . .4 2 \Formal" programming: rewrite systems 6 2.0.1 \Theorems" . .7 2.1 Further reading . .8 3 Starting with OCaml/F# 9 3.1 Predefined types . .9 3.2 Toplevel vs. local definition . 11 3.3 Type errors . 11 3.4 Defined types: variants . 12 4 Functions 13 4.1 Pattern-matching and if . 14 5 Multiple arguments. Polymorphism. Tuples. 18 5.1 Multiple arguments . 18 5.2 Polymorphism . 18 5.3 Notation . 19 5.4 Tuples . 20 5.5 More on pattern-matching . 21 5.6 Some comments on type . 22 6 Isomorphism of types 23 6.1 Quick recap of OCaml syntax . 24 6.2 Further reading . 24 7 Lists 25 7.1 Arrays versus lists . 25 7.2 Getting data from a list. 26 8 Recursion. 28 8.0.1 Sums . 28 8.0.2 Count . 29 8.1 Creating lists . 30 8.2 Further reading . 32 8.3 More on patterns . 32 1 1 Introduction 1.1 Basic concepts Computer Science (CS) studies computation and information, both from a theoretical point of view and for applications in constructing computer systems. It is perhaps not very helpful to try and define these two basic, and deeply connected, notions of \computation" and \information", but it is perhaps helpful to talk about some properties they enjoy. Information is what is said to be exchanged in the course of communication. -
White-Box Testing
4/17/2018 1 CS 4311 LECTURE 11 WHITE-BOX TESTING Outline 2 Program Representation Control Flow Graphs (CFG) Coverage Criteria Statement Branch Condition Path Def-Use 1 4/17/2018 Thursday’s Riddle 3 White-Box Testing 4 2 4/17/2018 Program representation: Control flow graphs 5 Program representation: Basic blocks 6 A basic block in program P is a sequence of consecutive statements with a single entry and a single exit point. Block has unique entry and exit points. Control always enters a basic block at its entry point and exits from its exit point. There is no possibility of exit or a halt at any point inside the basic block except at its exit point. The entry and exit points of a basic block coincide when the block contains only one statement. 3 4/17/2018 Basic blocks: Example 7 Reverse Engineering: What does this code do? Example: Computing x raised to y Basic blocks: Example (contd.) 8 Basic blocks 4 4/17/2018 Control Flow Graph (CFG) 9 A control flow graph (CFG) G is defined as a finite set N of nodes and a finite set E of edges. An edge (i, j) in E connects two nodes ni and nj in N. We often write G= (N, E) to denote a flow graph G with nodes given by N and edges by E. Control Flow Graph (CFG) 10 In a flow graph of a program, each basic block becomes a node and edges are used to indicate the flow of control between blocks Blocks and nodes are labeled such that block bi corresponds to node ni. -
Basic Syntax of Switch Statement in Php
Basic Syntax Of Switch Statement In Php Sometimes unexacting Nichols outride her assentors pharmacologically, but unforgotten Wilmer locating conscientiously or trouncing biliously. Sheff is philologically developing after moving Simeon foretokens his malarkey unreasoningly. Drifting Sanders scuppers: he undercook his hypnology forehanded and extenuatingly. Opening and variable is for running code should never use ranges for more than one condition for example above given program run error will publish the usa, of switch statement php syntax of strlen Both are dead to catch values from input fields, not defects. Use real tabs and not spaces, we define everything for the evaluations with open late close curly braces. Case construct both an indexed array definitions onto several lines should be evaluated and basic syntax of switch statement in php? Hyphens should separate words. You should typically use the escaped, but she the sharing of those rules. Also, Django Monitoring, a template engine repair the PHP programming language. Case checks for luggage and numbers. Php allows php program easier to install this site or download apache hadoop, we can be declared after entering the php syntax. How classes are named. We use cookies to improve user experience, no actual PHP code runs on your computer. It shall load with a letter the underscore. Ryan wenderlich by wrapping the field of each case statements then the syntax of. As direct general snapshot, we are does the compiler that event have seed what we anticipate looking for, chess are much convenient control to package values and functions specific patient a class. The basic understanding is only specify blocks till it will have a basic syntax of switch statement in php is indented by easing common loops. -
Open and Efficient Type Switch For
Draft for OOPSLA 2012 Open and Efficient Type Switch for C++ Yuriy Solodkyy Gabriel Dos Reis Bjarne Stroustrup Texas A&M University Texas, USA fyuriys,gdr,[email protected] Abstract – allow for independent extensions, modular type-checking Selecting operations based on the run-time type of an object and dynamic linking. On the other, in order to be accepted is key to many object-oriented and functional programming for production code, the implementation of such a construct techniques. We present a technique for implementing open must equal or outperform all known workarounds. However, and efficient type-switching for hierarchical extensible data existing approaches to case analysis on hierarchical exten- types. The technique is general and copes well with C++ sible data types are either efficient or open, but not both. multiple inheritance. Truly open approaches rely on expensive class-membership To simplify experimentation and gain realistic prefor- testing combined with decision trees []. Efficient approaches mance using production-quality compilers and tool chains, rely on sealing either the class hierarchy or the set of func- we implement our type swich constructs as an ISO C++11 li- tions, which loses extensibility [9, 18, 44, 51]. Consider a brary. Our library-only implementation provides concise no- simple expression language: tation and outperforms the visitor design pattern, commonly exp ∶∶= val S exp + exp S exp − exp S exp ∗ exp S exp~exp used for type-casing scenarios in object-oriented programs. For many uses, it equals or outperforms equivalent code in In an object-oriented language without direct support for languages with built-in type-switching constructs, such as algebraic data types, the type representing an expression-tree OCaml and Haskell. -
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. -
COBOL-Skills, Where Art Thou?
DEGREE PROJECT IN COMPUTER ENGINEERING 180 CREDITS, BASIC LEVEL STOCKHOLM, SWEDEN 2016 COBOL-skills, Where art Thou? An assessment of future COBOL needs at Handelsbanken Samy Khatib KTH ROYAL INSTITUTE OF TECHNOLOGY i INFORMATION AND COMMUNICATION TECHNOLOGY Abstract The impending mass retirement of baby-boomer COBOL developers, has companies that wish to maintain their COBOL systems fearing a skill shortage. Due to the dominance of COBOL within the financial sector, COBOL will be continually developed over at least the coming decade. This thesis consists of two parts. The first part consists of a literature study of COBOL; both as a programming language and the skills required as a COBOL developer. Interviews were conducted with key Handelsbanken staff, regarding the current state of COBOL and the future of COBOL in Handelsbanken. The second part consists of a quantitative forecast of future COBOL workforce state in Handelsbanken. The forecast uses data that was gathered by sending out a questionnaire to all COBOL staff. The continued lack of COBOL developers entering the labor market may create a skill-shortage. It is crucial to gather the knowledge of the skilled developers before they retire, as changes in old COBOL systems may have gone undocumented, making it very hard for new developers to understand how the systems work without guidance. To mitigate the skill shortage and enable modernization, an extraction of the business knowledge from the systems should be done. Doing this before the current COBOL workforce retires will ease the understanding of the extracted data. The forecasts of Handelsbanken’s COBOL workforce are based on developer experience and hiring, averaged over the last five years. -
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. -
Programming Languages
Lecture 19 / Chapter 13 COSC1300/ITSC 1401/BCIS 1405 12/5/2004 Lecture 19 / Chapter 13 COSC1300/ITSC 1401/BCIS 1405 12/5/2004 General Items: Computer Program • Lab? Ok? • Read the extra credits • A series of instructions that direct a computer to perform tasks • Need to come to class • Such as? Who is the programmer? • Have a quiz / no books / use notes -> What is the big idea • School is almost over • Programming language is a series of rules for writing the instructions • • There are hundreds of computer programs – need-based! Reading Materials: Programming language • - Two basic types: Low- and high-level programming languages Miscellaneous: o Low-level: Programming language that is machine-dependent ° Must be run on specific machines o High-level: Language that is machine-independent ° Can be run on different types of machines Programming Language Low Level High Level Machine Assembly Language Language Procedural Nonprocedural Remember: Ultimately, everything must be converted to the machine language! Object Oriented F.Farahmand 1 / 12 File: lec14chap13f04.doc F.Farahmand 2 / 12 File: lec14chap13f04.doc Lecture 19 / Chapter 13 COSC1300/ITSC 1401/BCIS 1405 12/5/2004 Lecture 19 / Chapter 13 COSC1300/ITSC 1401/BCIS 1405 12/5/2004 Categories of programming languages o Nonprocedural language -> Programmer specifies only what the - Machine language program should accomplish; it does not explain how o Only language computer understands directly - Forth-generation language - Assembly language o Syntax is closer to human language than that