Approaches to Composition and Refinement in Object-Oriented Design
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Encapsulation and Data Abstraction
Data abstraction l Data abstraction is the main organizing principle for building complex software systems l Without data abstraction, computing technology would stop dead in its tracks l We will study what data abstraction is and how it is supported by the programming language l The first step toward data abstraction is called encapsulation l Data abstraction is supported by language concepts such as higher-order programming, static scoping, and explicit state Encapsulation l The first step toward data abstraction, which is the basic organizing principle for large programs, is encapsulation l Assume your television set is not enclosed in a box l All the interior circuitry is exposed to the outside l It’s lighter and takes up less space, so it’s good, right? NO! l It’s dangerous for you: if you touch the circuitry, you can get an electric shock l It’s bad for the television set: if you spill a cup of coffee inside it, you can provoke a short-circuit l If you like electronics, you may be tempted to tweak the insides, to “improve” the television’s performance l So it can be a good idea to put the television in an enclosing box l A box that protects the television against damage and that only authorizes proper interaction (on/off, channel selection, volume) Encapsulation in a program l Assume your program uses a stack with the following implementation: fun {NewStack} nil end fun {Push S X} X|S end fun {Pop S X} X=S.1 S.2 end fun {IsEmpty S} S==nil end l This implementation is not encapsulated! l It has the same problems as a television set -
9. Abstract Data Types
COMPUTER SCIENCE COMPUTER SCIENCE SEDGEWICK/WAYNE SEDGEWICK/WAYNE 9. Abstract Data Types •Overview 9. Abstract Data Types •Color •Image processing •String processing Section 3.1 http://introcs.cs.princeton.edu http://introcs.cs.princeton.edu Abstract data types Object-oriented programming (OOP) A data type is a set of values and a set of operations on those values. Object-oriented programming (OOP). • Create your own data types (sets of values and ops on them). An object holds a data type value. Primitive types • Use them in your programs (manipulate objects). Variable names refer to objects. • values immediately map to machine representations data type set of values examples of operations • operations immediately map to Color three 8-bit integers get red component, brighten machine instructions. Picture 2D array of colors get/set color of pixel (i, j) String sequence of characters length, substring, compare We want to write programs that process other types of data. • Colors, pictures, strings, An abstract data type is a data type whose representation is hidden from the user. • Complex numbers, vectors, matrices, • ... Impact: We can use ADTs without knowing implementation details. • This lecture: how to write client programs for several useful ADTs • Next lecture: how to implement your own ADTs An abstract data type is a data type whose representation is hidden from the user. 3 4 Sound Strings We have already been using ADTs! We have already been using ADTs! A String is a sequence of Unicode characters. defined in terms of its ADT values (typical) Java's String ADT allows us to write Java programs that manipulate strings. -
The Inheritance Anomaly Revisited
The Inheritance Anomaly Revisited Ryan J. Wisnesky August 2006 Contents Contents i Preface ii Introduction 1 1 The Inheritance Anomaly and Formal Framework 2 1.1 An Overview of the Inheritance Anomaly . 2 1.2 An Overview of the Framework . 4 2 History-based Guard Languages 7 2.1 History-based guard languages . 7 2.2 Two tweaks . 8 2.2.1 The first tweak: Behavior Preservation . 8 2.2.2 The second tweak: Patching the Proof . 10 2.3 Discussion . 13 2.4 Related Work and Future Directions . 13 2.5 Conclusion . 15 3 Intra-object Concurrency 16 3.1 Methods and Messages . 16 3.1.1 New synchronization constructs . 17 3.1.2 Synchronization, Methods, and Messages . 18 3.2 New Types . 19 3.2.1 Mutual Exclusion: TypesS ............................ 20 3.2.2 Mutual Exclusion and Containment: TypesS .................. 24 3.2.3 TypesT,S ...................................... 25 3.3 Conclusion and Related Work . 27 4 Specification Languages 28 5 Overall Conclusion, Future Directions, and a Note on Typing 29 6 Related Work 30 6.1 Core Papers . 30 i 6.2 Concurrent Formal Systems . 31 6.3 Anomaly Avoidance Mechanisms . 33 6.4 Anomaly Generalizations . 36 6.5 Anomaly Experiences . 36 6.6 Surveys . 37 6.7 Aspect-Oriented Programming . 37 6.8 Others............................................ 38 Bibliography 41 ii Introduction The Inheritance Anomaly has been a thorn in the side of the concurrent object-oriented language community for 15 years. Simply put, the anomaly is a failure of inheritance and concurrency to work well with each other, negating the usefulness of inheritance as a mechanism for code-reuse in a concurrent setting. -
Abstract Data Types
Chapter 2 Abstract Data Types The second idea at the core of computer science, along with algorithms, is data. In a modern computer, data consists fundamentally of binary bits, but meaningful data is organized into primitive data types such as integer, real, and boolean and into more complex data structures such as arrays and binary trees. These data types and data structures always come along with associated operations that can be done on the data. For example, the 32-bit int data type is defined both by the fact that a value of type int consists of 32 binary bits but also by the fact that two int values can be added, subtracted, multiplied, compared, and so on. An array is defined both by the fact that it is a sequence of data items of the same basic type, but also by the fact that it is possible to directly access each of the positions in the list based on its numerical index. So the idea of a data type includes a specification of the possible values of that type together with the operations that can be performed on those values. An algorithm is an abstract idea, and a program is an implementation of an algorithm. Similarly, it is useful to be able to work with the abstract idea behind a data type or data structure, without getting bogged down in the implementation details. The abstraction in this case is called an \abstract data type." An abstract data type specifies the values of the type, but not how those values are represented as collections of bits, and it specifies operations on those values in terms of their inputs, outputs, and effects rather than as particular algorithms or program code. -
Abstract Data Types (Adts)
Data abstraction: Abstract Data Types (ADTs) CSE 331 University of Washington Michael Ernst Outline 1. What is an abstract data type (ADT)? 2. How to specify an ADT – immutable – mutable 3. The ADT design methodology Procedural and data abstraction Recall procedural abstraction Abstracts from the details of procedures A specification mechanism Reasoning connects implementation to specification Data abstraction (Abstract Data Type, or ADT): Abstracts from the details of data representation A specification mechanism + a way of thinking about programs and designs Next lecture: ADT implementations Representation invariants (RI), abstraction functions (AF) Why we need Abstract Data Types Organizing and manipulating data is pervasive Inventing and describing algorithms is rare Start your design by designing data structures Write code to access and manipulate data Potential problems with choosing a data structure: Decisions about data structures are made too early Duplication of effort in creating derived data Very hard to change key data structures An ADT is a set of operations ADT abstracts from the organization to meaning of data ADT abstracts from structure to use Representation does not matter; this choice is irrelevant: class RightTriangle { class RightTriangle { float base, altitude; float base, hypot, angle; } } Instead, think of a type as a set of operations create, getBase, getAltitude, getBottomAngle, ... Force clients (users) to call operations to access data Are these classes the same or different? class Point { class Point { public float x; public float r; public float y; public float theta; }} Different: can't replace one with the other Same: both classes implement the concept "2-d point" Goal of ADT methodology is to express the sameness Clients depend only on the concept "2-d point" Good because: Delay decisions Fix bugs Change algorithms (e.g., performance optimizations) Concept of 2-d point, as an ADT class Point { // A 2-d point exists somewhere in the plane, .. -
Csci 658-01: Software Language Engineering Python 3 Reflexive
CSci 658-01: Software Language Engineering Python 3 Reflexive Metaprogramming Chapter 3 H. Conrad Cunningham 4 May 2018 Contents 3 Decorators and Metaclasses 2 3.1 Basic Function-Level Debugging . .2 3.1.1 Motivating example . .2 3.1.2 Abstraction Principle, staying DRY . .3 3.1.3 Function decorators . .3 3.1.4 Constructing a debug decorator . .4 3.1.5 Using the debug decorator . .6 3.1.6 Case study review . .7 3.1.7 Variations . .7 3.1.7.1 Logging . .7 3.1.7.2 Optional disable . .8 3.2 Extended Function-Level Debugging . .8 3.2.1 Motivating example . .8 3.2.2 Decorators with arguments . .9 3.2.3 Prefix decorator . .9 3.2.4 Reformulated prefix decorator . 10 3.3 Class-Level Debugging . 12 3.3.1 Motivating example . 12 3.3.2 Class-level debugger . 12 3.3.3 Variation: Attribute access debugging . 14 3.4 Class Hierarchy Debugging . 16 3.4.1 Motivating example . 16 3.4.2 Review of objects and types . 17 3.4.3 Class definition process . 18 3.4.4 Changing the metaclass . 20 3.4.5 Debugging using a metaclass . 21 3.4.6 Why metaclasses? . 22 3.5 Chapter Summary . 23 1 3.6 Exercises . 23 3.7 Acknowledgements . 23 3.8 References . 24 3.9 Terms and Concepts . 24 Copyright (C) 2018, H. Conrad Cunningham Professor of Computer and Information Science University of Mississippi 211 Weir Hall P.O. Box 1848 University, MS 38677 (662) 915-5358 Note: This chapter adapts David Beazley’s debugly example presentation from his Python 3 Metaprogramming tutorial at PyCon’2013 [Beazley 2013a]. -
The Inheritance Anomaly: Ten Years After
The inheritance anomaly: ten years after Giuseppe Milicia Vladimiro Sassone Chi Spaces Technologies ltd. University of Sussex, UK Cambridge, UK [email protected] [email protected] ABSTRACT Clearly we must make sure that no object is removed from an The term inheritance anomaly was coined in 1993 by Matsuoka empty buffer and that no object is inserted into a full buffer. In a and Yonezawa [15] to refer to the problems arising by the coexis- sequential setting, the burden of ensuring such constraints resides tence of inheritance and concurrency in concurrent object oriented with the buffer’s user. Indeed the buffer is created and used by languages (COOLs). The quirks arising by such combination have one thread only, which is responsible for the state of the object. been observed since the early eighties, when the first experimen- To facilitate usage, the buffer’s methods might return certain er- tal COOLs were designed [3]. In the nineties COOLs turned from ror codes in case of misuse. This approach is not feasible in a research topic to widely used tools in the everyday programming concurrent setting. The buffer will be used concurrently by mul- practice, see e.g. the Java [9] experience. This expository paper ex- tiple clients, leaving each of them no idea on the buffer’s current tends the survey presented in [15] to account for new and widely state. Although it is possible to envisage ad-hoc protocols among used COOLs, most notably Java and C] [19]. Specifically, we il- clients to keep track of the buffer’s state, such a solution is com- lustrate some innovative approaches to COOL design relying on plex and hardly feasible in practice. -
Source-Code Instrumentation and Quantification of Events Robert E
Source-Code Instrumentation and Quantification of Events Robert E. Filman Klaus Havelund RIACS Kestrel Technology NASA Ames Research Center, MS 269/2 NASA Ames Research Center, MS 269/2 Moffett Field, CA 94035 U.S.A. Moffett Field, CA 94035 U.S.A +1 650–604–1250 +1 650–604–3366 [email protected] [email protected] ABSTRACT particularly with respect to debugging and validating concurrent Aspect-Oriented Programming is making quantified programmatic systems. assertions over programs that otherwise are not annotated to 2. EVENTS receive these assertions. Varieties of AOP systems are Quantification implies matching a predicate about a program. characterized by which quantified assertions they allow, what they Such a predicate must be over some domain. In the permit in the actions of the assertions (including how the actions quantification/implicit invocation papers, we distinguished interact with the base code), and what mechanisms they use to between static and dynamic quantification. achieve the overall effect. Here, we argue that all quantification is over dynamic events, and describe our preliminary work in Static quantification worked over the structure of the program. developing a system that maps dynamic events to transformations That is, with static quantification, one could reference the over source code. We discuss possible applications of this system, programming language structures in a system. Examples of such particularly with respect to debugging concurrent systems. structures include reference to program variables, calls to subprograms, loops, and conditional tests. Categories and Subject Descriptors Many common AOP implementation techniques can be D.3.3 [Programming Languages]: Language Constructs and understood in terms of quantified program manipulation on the Features – aspects. -
The Power of Interoperability: Why Objects Are Inevitable
The Power of Interoperability: Why Objects Are Inevitable Jonathan Aldrich Carnegie Mellon University Pittsburgh, PA, USA [email protected] Abstract 1. Introduction Three years ago in this venue, Cook argued that in Object-oriented programming has been highly suc- their essence, objects are what Reynolds called proce- cessful in practice, and has arguably become the dom- dural data structures. His observation raises a natural inant programming paradigm for writing applications question: if procedural data structures are the essence software in industry. This success can be documented of objects, has this contributed to the empirical success in many ways. For example, of the top ten program- of objects, and if so, how? ming languages at the LangPop.com index, six are pri- This essay attempts to answer that question. After marily object-oriented, and an additional two (PHP reviewing Cook’s definition, I propose the term ser- and Perl) have object-oriented features.1 The equiva- vice abstractions to capture the essential nature of ob- lent numbers for the top ten languages in the TIOBE in- jects. This terminology emphasizes, following Kay, that dex are six and three.2 SourceForge’s most popular lan- objects are not primarily about representing and ma- guages are Java and C++;3 GitHub’s are JavaScript and nipulating data, but are more about providing ser- Ruby.4 Furthermore, objects’ influence is not limited vices in support of higher-level goals. Using examples to object-oriented languages; Cook [8] argues that Mi- taken from object-oriented frameworks, I illustrate the crosoft’s Component Object Model (COM), which has unique design leverage that service abstractions pro- a C language interface, is “one of the most pure object- vide: the ability to define abstractions that can be ex- oriented programming models yet defined.” Academ- tended, and whose extensions are interoperable in a ically, object-oriented programming is a primary focus first-class way. -
On the Interaction of Object-Oriented Design Patterns and Programming
On the Interaction of Object-Oriented Design Patterns and Programming Languages Gerald Baumgartner∗ Konstantin L¨aufer∗∗ Vincent F. Russo∗∗∗ ∗ Department of Computer and Information Science The Ohio State University 395 Dreese Lab., 2015 Neil Ave. Columbus, OH 43210–1277, USA [email protected] ∗∗ Department of Mathematical and Computer Sciences Loyola University Chicago 6525 N. Sheridan Rd. Chicago, IL 60626, USA [email protected] ∗∗∗ Lycos, Inc. 400–2 Totten Pond Rd. Waltham, MA 02154, USA [email protected] February 29, 1996 Abstract Design patterns are distilled from many real systems to catalog common programming practice. However, some object-oriented design patterns are distorted or overly complicated because of the lack of supporting programming language constructs or mechanisms. For this paper, we have analyzed several published design patterns looking for idiomatic ways of working around constraints of the implemen- tation language. From this analysis, we lay a groundwork of general-purpose language constructs and mechanisms that, if provided by a statically typed, object-oriented language, would better support the arXiv:1905.13674v1 [cs.PL] 31 May 2019 implementation of design patterns and, transitively, benefit the construction of many real systems. In particular, our catalog of language constructs includes subtyping separate from inheritance, lexically scoped closure objects independent of classes, and multimethod dispatch. The proposed constructs and mechanisms are not radically new, but rather are adopted from a variety of languages and programming language research and combined in a new, orthogonal manner. We argue that by describing design pat- terns in terms of the proposed constructs and mechanisms, pattern descriptions become simpler and, therefore, accessible to a larger number of language communities. -
Software II: Principles of Programming Languages
Software II: Principles of Programming Languages Lecture 6 – Data Types Some Basic Definitions • A data type defines a collection of data objects and a set of predefined operations on those objects • A descriptor is the collection of the attributes of a variable • An object represents an instance of a user- defined (abstract data) type • One design issue for all data types: What operations are defined and how are they specified? Primitive Data Types • Almost all programming languages provide a set of primitive data types • Primitive data types: Those not defined in terms of other data types • Some primitive data types are merely reflections of the hardware • Others require only a little non-hardware support for their implementation The Integer Data Type • Almost always an exact reflection of the hardware so the mapping is trivial • There may be as many as eight different integer types in a language • Java’s signed integer sizes: byte , short , int , long The Floating Point Data Type • Model real numbers, but only as approximations • Languages for scientific use support at least two floating-point types (e.g., float and double ; sometimes more • Usually exactly like the hardware, but not always • IEEE Floating-Point Standard 754 Complex Data Type • Some languages support a complex type, e.g., C99, Fortran, and Python • Each value consists of two floats, the real part and the imaginary part • Literal form real component – (in Fortran: (7, 3) imaginary – (in Python): (7 + 3j) component The Decimal Data Type • For business applications (money) -
The Principles of Object-Oriented Javascript Zakas
TAKETAKE CONTROLCONTROL OFOF Foreword by Cody Lindley, Best-selling Author and Principal Frontend Architect JAVASCRIPT THE PRINCIPLES OF OBJECT-ORIENTED JAVASCRIPT JAVASCRIPT THE PRINCIPLES OF OBJECT-ORIENTED JAVASCRIPT THETHE PRINCIPLESPRINCIPLES OFOF OBJECTSOBJECTS at TandemSeven OBJECT-ORIENTEDOBJECT-ORIENTED If you’ve used a more traditional object-oriented • How to define your own constructors JAVASCRIPTJAVASCRIPT language, such as C++ or Java, JavaScript probably • How to work with and understand prototypes doesn’t seem object-oriented at all. It has no concept of classes, and you don’t even need to define any • Inheritance patterns for types and objects objects in order to write code. But don’t be fooled — The Principles of Object-Oriented JavaScript will leave NICHOLAS C. ZAKAS JavaScript is an incredibly powerful and expressive even experienced developers with a deeper understand- object-oriented language that puts many design ing of JavaScript. Unlock the secrets behind how objects decisions right into your hands. work in JavaScript so you can write clearer, more In The Principles of Object-Oriented JavaScript, flexible, and more efficient code. Nicholas C. Zakas thoroughly explores JavaScript’s object-oriented nature, revealing the language’s A B O U T T H E A U T H O R unique implementation of inheritance and other key characteristics. You’ll learn: Nicholas C. Zakas is a software engineer at Box and is known for writing on and speaking about the latest • The difference between primitive and reference in JavaScript best practices. He honed his experience values during his five years at Yahoo!, where he was principal • What makes JavaScript functions so unique frontend engineer for the Yahoo! home page.