Type-Safe Composition of Object Modules*

Total Page:16

File Type:pdf, Size:1020Kb

Type-Safe Composition of Object Modules* International Conference on Computer Systems and Education I ISc Bangalore Typ esafe Comp osition of Ob ject Mo dules Guruduth Banavar Gary Lindstrom Douglas Orr Department of Computer Science University of Utah Salt LakeCity Utah USA Abstract Intro duction It is widely agreed that strong typing in We describ e a facility that enables routine creases the reliability and eciency of soft typ echecking during the linkage of exter ware However compilers for statically typ ed nal declarations and denitions of separately languages suchasC and C in tradi compiled programs in ANSI C The primary tional nonintegrated programming environ advantage of our serverstyle typ echecked ments guarantee complete typ esafety only linkage facility is the ability to program the within a compilation unit but not across comp osition of ob ject mo dules via a suite of suchunits Longstanding and widely avail strongly typ ed mo dule combination op era able linkers comp ose separately compiled tors Such programmability enables one to units bymatching symb ols purely byname easily incorp orate programmerdened data equivalence with no regard to their typ es format conversion stubs at linktime In ad Such common denominator linkers accom dition our linkage facility is able to automat mo date ob ject mo dules from various source ically generate safe co ercion stubs for com languages by simply ignoring the static se patible encapsulated data mantics of the language Moreover com monly used ob ject le formats are not de signed to incorp orate source language typ e information in an easily accessible manner This researchwas sp onsored by the Advanced In this pap er we presenta technique to Research Pro jects Agency DOD monitored by the p erform typ e checking of ob ject mo dules as Department of the Navy Oce of the Chief of a routine linktime activity Our technique is Naval Research under Grantnumb er NJ The views and conclusions contained in this characterized by i the design of sp ecic lan do cument are those of the authors and should not guage typ e systems into a systemwide linker be interpreted as representing ocial p olicies ei ii programmed linktime control over indi ther expressed or implied of the Advanced Research vidual symb ols of ob ject mo dules and iii Pro jects Agency or the US Government Contact author G Banavar Computer Science MEB University of Utah Salt LakeCity UT USA e C style namemangling do es not accomplish mail banavarcsutahedu phone complete typ esafety across compilation units see fax Section utilization of standard debugging informa similar to Mo dula using memb er or tion generated by compilers for typ e check der and typ e signicance along with names ing We describ e in detail the realization of Furthermore our programmable linkage these steps for ANSI C facility enables the incorp oration of auto matic and userdened conversion routines A crucial enabler for this facility is the abil for encapsulated data For automatic con ity to resolve inconsistencies among compiled version we p ostulate safe adaptability rules ob ject mo dules at link time The existence for converting builtin data typ es using the of link time typ e errors do es not mean that language denition in conjunction with the program source les need to b e mo died and characteristics of particular hardware plat recompiled as this may not b e p ossible for forms We then utilize these rules to auto precompiled libraries Programmer control matically generate data conversion stubs for correcting link time typ e errors is pro at link time More imp ortantly program vided via the already existing programming mer dened conversion stubs can also b e eas facilities of OMOS our dynamic linker ily incorp orated at link time This op ens For instance consider the case where the up the p ossibility of programmercontrolled typ e of a declaration in one translation unit data evolution and conversion across hetero do es not match with a denition in another geneous data formats eg those arising from This can usually b e xed by i uniformly re dierent languages hardware architectures naming the declaration and its uses to match etc the actually intended denition name or ii Weprovide the abilitytosupportavari in the case when the names match but the etyoftyp e systems by designing our typ e typ es do not byintro ducing a new decla checking facility as an extension of an ob ject ration to match the denition and binding oriented framework The OO framework the renamed original declaration with a typ e contains generic typ e system related abstrac conversion function Our linkage facility eas tions suchas named typ es function typ es ily supp orts such transformations If a typ e record typ es etc that are sp ecialized via in error cannot b e corrected with such simple heritance to implement the typ e domain of transformations on ob ject mo dules it might sp ecic languages indicate a more serious error in the design of In the following sections we describ e in the mo dules involved detail the typ echecking of ob ject mo dules generated by compiling ANSI C programs Our linktime typ echecking facility p er Section intro duces our notion of mo dules mits us to adapt and utilize the full expres and interfaces Section briey describ es our sivepower of language typ e systems to b et ob ject server OMOS and Section discusses ter suit mo dern p ersistent distributed and the essential asp ects of the typ e system of heterogeneous environments For example ANSI C We then give some implementation structural typing can b e applied to languages details discuss related work and conclude such as ANSI C with namebased typing Pure namebased typing b ecomes a problem in p ersistent and distributed environments Ob ject Mo dules and where data and typ es could migrate out side the program in which they were orig their Interfaces inally created and lead to matching of names that mayormay not have the same We refer to an ANSI C program source or programmerintended meaning This argues ob ject le as a module consisting of a set for structural matching of aggregate typ es of attributes with no order signicance An the compiled mo dule O provides a deni attribute is either a lelevel declaration a tion of function f Consider the case where name with an asso ciated typ e eg extern a programmer creates and compiles mo dule int i or a lelevel denition a name O with the intention of using Os f deni with a data storage or function binding tion by p erforming O merge O but makes Typ e denitions eg struct denitions the incorrect presumption that f returns an and typedefs in C are not attributes of intIfmerge were untyp ed as it is in com a mo dule The interface of a mo dule con mon linkage O merge O would have b een sists of name typ e declared or dened legal howeveritdoesnottyp echeck in our tuples of the attributes of the mo dule In the linker since the interfaces of O and O are context of typ echecking ob ject mo dule inter not typ e compatible for a merge op eration faces attributes match if they have the same Let us say that the programmer of O dis name There cannot b e matching attributes y coversduringlinkage that f returns the de within a single interface and attributes that sired int value as a comp onent of the re match across interfaces must b e typ e com turned structure Traditionally in order to patible The notion of typ e compatibilityde make O and O compatible the program p ends on the particular mo dule combination mer would mo dify the source co de of either op eration b eing p erformed and is informally mo dule extensivelyifitwere available and describ ed b elow recompile This of course could adversely Our linker is based up on a formal mo del aect combination of the mo died mo dule of mo dules prop osed in achieving a ne with yet other mo dules Alternatively in our level of control over individual attributes of mo del of exible linktime mo dule adapta ob ject mo dules Briey ob ject mo dules are tion O can b e adapted to get the desired ef combined via a suite of mo dule combination fect by constructing a stub mo dule O O operators that were originally conceived to consists of a new declaration that matches describ e the many facets of inheritance in fs denition and a stub function that ex ob jectoriented programming Figure gives tracts the desired value from the structure the primary op erators their informal seman returned by f With this a mo died ver tics and typ e rules These op erators pro sion of O is obtained with the mo dule ex vide control over asp ects of visibility sharing pression O rename f f stub merge O and rebindability of individual attributes of which can then b e mergeed with O to get mo dules The p ower that this mo del lends the originally desired eect to ob ject mo dule linkage is briey given in Section and is describ ed in more detail in where the original implementation of The OMOS Linker the typ eless OMOS linker is describ ed The current eort incorp orates the rules of the In this section we describ e our linkage strongly typ ed mo dule mo del and illustrates facility the Ob ject MetaOb ject Server some of its applications OMOS The semantics of common linkageisem The OMOS linkerloader is designed to b o died in the mo dule op erator merge For provide a dynamic linking and loading facil a simple example of the use of this mo dule ity for client programs via the use of mo dule op erator consider Figure In this gure combination and instantiation OMOS im plements a p ersistent hierarchical namespace y In order to mo del languages that supp ort user muchlike
Recommended publications
  • Faster Ffts in Medium Precision
    Faster FFTs in medium precision Joris van der Hoevena, Grégoire Lecerfb Laboratoire d’informatique, UMR 7161 CNRS Campus de l’École polytechnique 1, rue Honoré d’Estienne d’Orves Bâtiment Alan Turing, CS35003 91120 Palaiseau a. Email: [email protected] b. Email: [email protected] November 10, 2014 In this paper, we present new algorithms for the computation of fast Fourier transforms over complex numbers for “medium” precisions, typically in the range from 100 until 400 bits. On the one hand, such precisions are usually not supported by hardware. On the other hand, asymptotically fast algorithms for multiple precision arithmetic do not pay off yet. The main idea behind our algorithms is to develop efficient vectorial multiple precision fixed point arithmetic, capable of exploiting SIMD instructions in modern processors. Keywords: floating point arithmetic, quadruple precision, complexity bound, FFT, SIMD A.C.M. subject classification: G.1.0 Computer-arithmetic A.M.S. subject classification: 65Y04, 65T50, 68W30 1. Introduction Multiple precision arithmetic [4] is crucial in areas such as computer algebra and cryptography, and increasingly useful in mathematical physics and numerical analysis [2]. Early multiple preci- sion libraries appeared in the seventies [3], and nowadays GMP [11] and MPFR [8] are typically very efficient for large precisions of more than, say, 1000 bits. However, for precisions which are only a few times larger than the machine precision, these libraries suffer from a large overhead. For instance, the MPFR library for arbitrary precision and IEEE-style standardized floating point arithmetic is typically about a factor 100 slower than double precision machine arithmetic.
    [Show full text]
  • 5. Data Types
    IEEE FOR THE FUNCTIONAL VERIFICATION LANGUAGE e Std 1647-2011 5. Data types The e language has a number of predefined data types, including the integer and Boolean scalar types common to most programming languages. In addition, new scalar data types (enumerated types) that are appropriate for programming, modeling hardware, and interfacing with hardware simulators can be created. The e language also provides a powerful mechanism for defining OO hierarchical data structures (structs) and ordered collections of elements of the same type (lists). The following subclauses provide a basic explanation of e data types. 5.1 e data types Most e expressions have an explicit data type, as follows: — Scalar types — Scalar subtypes — Enumerated scalar types — Casting of enumerated types in comparisons — Struct types — Struct subtypes — Referencing fields in when constructs — List types — The set type — The string type — The real type — The external_pointer type — The “untyped” pseudo type Certain expressions, such as HDL objects, have no explicit data type. See 5.2 for information on how these expressions are handled. 5.1.1 Scalar types Scalar types in e are one of the following: numeric, Boolean, or enumerated. Table 17 shows the predefined numeric and Boolean types. Both signed and unsigned integers can be of any size and, thus, of any range. See 5.1.2 for information on how to specify the size and range of a scalar field or variable explicitly. See also Clause 4. 5.1.2 Scalar subtypes A scalar subtype can be named and created by using a scalar modifier to specify the range or bit width of a scalar type.
    [Show full text]
  • Python Programming
    Python Programming Wikibooks.org June 22, 2012 On the 28th of April 2012 the contents of the English as well as German Wikibooks and Wikipedia projects were licensed under Creative Commons Attribution-ShareAlike 3.0 Unported license. An URI to this license is given in the list of figures on page 149. If this document is a derived work from the contents of one of these projects and the content was still licensed by the project under this license at the time of derivation this document has to be licensed under the same, a similar or a compatible license, as stated in section 4b of the license. The list of contributors is included in chapter Contributors on page 143. The licenses GPL, LGPL and GFDL are included in chapter Licenses on page 153, since this book and/or parts of it may or may not be licensed under one or more of these licenses, and thus require inclusion of these licenses. The licenses of the figures are given in the list of figures on page 149. This PDF was generated by the LATEX typesetting software. The LATEX source code is included as an attachment (source.7z.txt) in this PDF file. To extract the source from the PDF file, we recommend the use of http://www.pdflabs.com/tools/pdftk-the-pdf-toolkit/ utility or clicking the paper clip attachment symbol on the lower left of your PDF Viewer, selecting Save Attachment. After extracting it from the PDF file you have to rename it to source.7z. To uncompress the resulting archive we recommend the use of http://www.7-zip.org/.
    [Show full text]
  • GNU MPFR the Multiple Precision Floating-Point Reliable Library Edition 4.1.0 July 2020
    GNU MPFR The Multiple Precision Floating-Point Reliable Library Edition 4.1.0 July 2020 The MPFR team [email protected] This manual documents how to install and use the Multiple Precision Floating-Point Reliable Library, version 4.1.0. Copyright 1991, 1993-2020 Free Software Foundation, Inc. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, with no Front-Cover Texts, and with no Back- Cover Texts. A copy of the license is included in Appendix A [GNU Free Documentation License], page 59. i Table of Contents MPFR Copying Conditions ::::::::::::::::::::::::::::::::::::::: 1 1 Introduction to MPFR :::::::::::::::::::::::::::::::::::::::: 2 1.1 How to Use This Manual::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 2 2 Installing MPFR ::::::::::::::::::::::::::::::::::::::::::::::: 3 2.1 How to Install ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 3 2.2 Other `make' Targets :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 4 2.3 Build Problems :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 4 2.4 Getting the Latest Version of MPFR ::::::::::::::::::::::::::::::::::::::::::::::: 4 3 Reporting Bugs::::::::::::::::::::::::::::::::::::::::::::::::: 5 4 MPFR Basics ::::::::::::::::::::::::::::::::::::::::::::::::::: 6 4.1 Headers and Libraries :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 6
    [Show full text]
  • Type Conversion ,Type Casting, Operator Precedence and Associativity in C
    Type Conversion ,Type Casting, Operator Precedence and Associativity in C Gaurav Kr. suman 4/30/20 MAT09 The type conversion in C is basically converting one type of data type to other to perform some operation. The conversion is done only between those datatypes wherein the conversion is possible There are two types of type conversion: This type of conversion is usually performed by the compiler when necessary without any commands by the user. Thus it is also called "Automatic Type Conversion". • Done by the compiler on its own, without any external trigger from the user. • Generally takes place when in an expression more than one data type is present. In such condition type conversion (type promotion) takes place to avoid lose of data. • All the data types of the variables are upgraded to the data type of the variable with largest data type. Now, let’s focus on some examples to further understand about type conversions in C. Example 1 int a = 20; double b = 20.5; a + b; Here, first operand is int type and other is of type double. So, as per rule, the variable a will be converted to double. Therefore, the final answer is double a + b = 40.500000. Example 2 char ch='a'; int a =13; a+c; Here, first operand is char type and other is of type int. So, as per rule , the char variable will be converted to int type during the operation and the final answer will be of type int. We know the ASCII value for ch is 97.
    [Show full text]
  • IEEE Standard 754 for Binary Floating-Point Arithmetic
    Work in Progress: Lecture Notes on the Status of IEEE 754 October 1, 1997 3:36 am Lecture Notes on the Status of IEEE Standard 754 for Binary Floating-Point Arithmetic Prof. W. Kahan Elect. Eng. & Computer Science University of California Berkeley CA 94720-1776 Introduction: Twenty years ago anarchy threatened floating-point arithmetic. Over a dozen commercially significant arithmetics boasted diverse wordsizes, precisions, rounding procedures and over/underflow behaviors, and more were in the works. “Portable” software intended to reconcile that numerical diversity had become unbearably costly to develop. Thirteen years ago, when IEEE 754 became official, major microprocessor manufacturers had already adopted it despite the challenge it posed to implementors. With unprecedented altruism, hardware designers had risen to its challenge in the belief that they would ease and encourage a vast burgeoning of numerical software. They did succeed to a considerable extent. Anyway, rounding anomalies that preoccupied all of us in the 1970s afflict only CRAY X-MPs — J90s now. Now atrophy threatens features of IEEE 754 caught in a vicious circle: Those features lack support in programming languages and compilers, so those features are mishandled and/or practically unusable, so those features are little known and less in demand, and so those features lack support in programming languages and compilers. To help break that circle, those features are discussed in these notes under the following headings: Representable Numbers, Normal and Subnormal, Infinite
    [Show full text]
  • Object Oriented Pogramming with C++
    OBJECT ORIENTED POGRAMMING WITH C++ 1. What is type conversion? Type Conversion is the process of converting one predefined type into another type. When variables of one type are mixed with variables of another type, a type conversion will occur. C++ facilitates the type conversion into the following two forms: Implicit Type Conversion: An implicit type conversion is a conversion performed by the compiler without programmer's intervention. It is applied whenever different data types are intermixed in an expression, so as not to lose information short x=6000; int y; y=x; // data type short variable x is converted to int and is assigned to the integer variable y. Explicit Type Conversion: The explicit conversion of an operand to a specific type is called type casting. An explicit type conversion is user-defined that forces an expression to be of specific type. Syntax: (type) expression #include <iostream.h> void main( ) { int a; float b, c; cout << "Enter the value of a:"; cin >> a; cout << "Enter the value of b:"; cin >> b; c = float(a)+b; cout << "The value of c is:" << c; getch(); } In the above program “a” is declared as integer and “b” and “c” are declared as float. In the type conversion statement namely c = float (a) +b; The variable a of type integer is converted into float type and so the value 10 is converted as 10.0 and then is added with the float variable b with value 12.5 giving a resultant float variable c with value as 22.5 2. Why C++ is called OOP language? M.VIJAY .
    [Show full text]
  • VHDL Type Conversion | Bitweenie
    VHDL Type Conversion | BitWeenie http://www.bitweenie.com/listings/vhdl-type-conversion/ Home About Electrical Engineer Jobs Request Topic Resources Home » VHDL Type Conversion VHDL Type Conversion Posted by Shannon Hilbert in Verilog / VHDL on 2-10-13 Any given VHDL FPGA design may have multiple VHDL types being used. The most common VHDL types used in synthesizable VHDL code are std_logic, std_logic_vector, signed, unsigned, and integer. Because VHDL is a strongly-typed language, most often differing types cannot be used in the same expression. In cases where you can directly combine two types into one expression, you are really leaving it up to the compiler or synthesis tool to determine how the expression should behave, which is a dangerous thing to do. This article will discuss the following concepts: 1. Type casting and conversion functions. 2. The importance of using the appropriate type. 3. Common uses and examples. VHDL Type Cast and Conversion Functions The picture below illustrates how to convert between the most common VHDL types. Type casting is used to move between the std_logic_vector type and the signed and unsigned types. 1 --signal definitions 2 signal slv : std_logic_vector(7 downto 0); 3 signal s : signed(7 downto 0); 4 signal us : unsigned(7 downto 0); 5 6 --FROM std_logic_vector TO signed/unsigned 1 de 5 07/10/2015 14:58 VHDL Type Conversion | BitWeenie http://www.bitweenie.com/listings/vhdl-type-conversion/ 7 sgn <= signed(slv); 8 usgn <= unsigned(slv); 9 10-- FROM signed/unsigned TO std_logic_vector 11svl <= std_logic_vector(sgn); 12svl <= std_logic_vector(usgn); Functions are used to move between signed and unsigned types and the integer type.
    [Show full text]
  • N1592 Explicit Conversion Operators
    Document Number: SC22/WG21/N1592=04-0032 Date: 2004-2-13 Author: Lois Goldthwaite Email: [email protected] Explicit Conversion Operators This paper proposes a small change in C++ grammar to permit the function-specifier 'explicit' to be applied to the definition of a user-defined conversion operator. The semantic effect is to inhibit automatic conversions in situations where they may not have been intended. The Problem One of the design principles of C++ is that the language does not enforce a different syntax for user-defined types and built-in primitive types. A variable of either category can be passed by value (assuming the programmer has not intentionally disabled this), and a variable of any type can be passed by reference. The compiler will perform automatic promotions and conversions, if necessary, when numeric types are used as function parameters or when differing types are combined with an operator (int to long, signed to unsigned, float to double, etc.). Similarly, the programmer can write conversion functions for user-defined types, so that the conversions will take place transparently. This is a feature, and A Good Thing, as it decreases the number of overloaded functions which would otherwise be needed (D&E 3.6.1). In Modern C++ Design, Alexandrescu says, "User-defined conversions in C++ have an interesting history. Back in the 1980s, when user-defined conversions were introduced, most programmers considered them a great invention. User-defined conversions promised a more unified type system, expressive semantics, and the ability to define new types that were indistinguishable from built-in ones.
    [Show full text]
  • Effectiveness of Floating-Point Precision on the Numerical Approximation by Spectral Methods
    Mathematical and Computational Applications Article Effectiveness of Floating-Point Precision on the Numerical Approximation by Spectral Methods José A. O. Matos 1,2,† and Paulo B. Vasconcelos 1,2,∗,† 1 Center of Mathematics, University of Porto, R. Dr. Roberto Frias, 4200-464 Porto, Portugal; [email protected] 2 Faculty of Economics, University of Porto, R. Dr. Roberto Frias, 4200-464 Porto, Portugal * Correspondence: [email protected] † These authors contributed equally to this work. Abstract: With the fast advances in computational sciences, there is a need for more accurate compu- tations, especially in large-scale solutions of differential problems and long-term simulations. Amid the many numerical approaches to solving differential problems, including both local and global methods, spectral methods can offer greater accuracy. The downside is that spectral methods often require high-order polynomial approximations, which brings numerical instability issues to the prob- lem resolution. In particular, large condition numbers associated with the large operational matrices, prevent stable algorithms from working within machine precision. Software-based solutions that implement arbitrary precision arithmetic are available and should be explored to obtain higher accu- racy when needed, even with the higher computing time cost associated. In this work, experimental results on the computation of approximate solutions of differential problems via spectral methods are detailed with recourse to quadruple precision arithmetic. Variable precision arithmetic was used in Tau Toolbox, a mathematical software package to solve integro-differential problems via the spectral Tau method. Citation: Matos, J.A.O.; Vasconcelos, Keywords: floating-point arithmetic; variable precision arithmetic; IEEE 754-2008 standard; quadru- P.B.
    [Show full text]
  • Polymorphism
    Polymorphism A closer look at types.... Chap 8 polymorphism º comes from Greek meaning ‘many forms’ In programming: Def: A function or operator is polymorphic if it has at least two possible types. Polymorphism i) OverloaDing Def: An overloaDeD function name or operator is one that has at least two Definitions, all of Different types. Example: In Java the ‘+’ operator is overloaDeD. String s = “abc” + “def”; +: String * String ® String int i = 3 + 5; +: int * int ® int Polymorphism Example: Java allows user DefineD polymorphism with overloaDeD function names. bool f (char a, char b) { return a == b; f : char * char ® bool } bool f (int a, int b) { f : int * int ® bool return a == b; } Note: ML Does not allow function overloaDing Polymorphism ii) Parameter Coercion Def: An implicit type conversion is calleD a coercion. Coercions usually exploit the type-subtype relationship because a wiDening type conversion from subtype to supertype is always DeemeD safe ® a compiler can insert these automatically ® type coercions. Example: type coercion in Java Double x; x = 2; the value 2 is coerceD from int to Double by the compiler Polymorphism Parameter coercion is an implicit type conversion on parameters. Parameter coercion makes writing programs easier – one function can be applieD to many subtypes. Example: Java voiD f (Double a) { ... } int Ì double float Ì double short Ì double all legal types that can be passeD to function ‘f’. byte Ì double char Ì double Note: ML Does not perform type coercion (ML has no notion of subtype). Polymorphism iii) Parametric Polymorphism Def: A function exhibits parametric polymorphism if it has a type that contains one or more type variables.
    [Show full text]
  • Primitive Data, Variables, and Expressions; Simple Conditional Execution
    Unit 2, Part 1 Primitive Data, Variables, and Expressions; Simple Conditional Execution Computer Science S-111 Harvard University David G. Sullivan, Ph.D. Overview of the Programming Process Analysis/Specification Design Implementation Testing/Debugging Example Problem: Adding Up Your Change • Let's say that we have a bunch of coins of various types, and we want to figure out how much money we have. • Let’s begin the process of developing a program that does this. Step 1: Analysis and Specification • Analyze the problem (making sure that you understand it), and specify the problem requirements clearly and unambiguously. • Describe exactly what the program will do, without worrying about how it will do it. Step 2: Design • Determine the necessary algorithms (and possibly other aspects of the program) and sketch out a design for them. • This is where we figure out how the program will solve the problem. • Algorithms are often designed using pseudocode. • more informal than an actual programming language • allows us to avoid worrying about the syntax of the language • example for our change-adder problem: get the number of quarters get the number of dimes get the number of nickels get the number of pennies compute the total value of the coins output the total value Step 3: Implementation • Translate your design into the programming language. pseudocode code • We need to learn more Java before we can do this! • Here's a portion or fragment of a Java program for computing the value of a particular collection of coins: quarters = 10; dimes = 3; nickels = 7; pennies = 6; cents = 25*quarters + 10*dimes + 5*nickels + pennies; System.out.println("Your total in cents is:"); System.out.println(cents); • In a moment, we'll use this fragment to examine some of the fundamental building blocks of a Java program.
    [Show full text]