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Concepts of Object Oriented Techniques with OO Issues


Object-oriented frameworks offer reuse at a high design level promising several benefits to the development of complex systems. This paper sought to 1) define the concepts of object oriented techniques in addition with the OO issues, development techniques and concepts of object oriented programming, it is also introduced the UML as an ordinary and key tool for object-oriented design, additionally 2) we look further into the frameworks from the perspective of object-oriented techniques. In this section, it is aimed to define a reasonable promise between object oriented technology and frameworks. At the end, some future horizons for object oriented technology and frameworks are presented.

I. Introduction

Computing power and network bandwidth have increased dramatically over the past decade. However, the design and implementation of complex software remains expensive and error-prone. Much of the cost and effort stems from the continuous re-discovery and re-invention of core concepts and components across the software industry. In particular, the growing heterogeneity of hardware architectures and diversity of operating system and communication platforms makes it hard to build correct, portable, efficient, and inexpensive applications from scratch. Object-oriented (OO) techniques and frameworks are promising technologies for reifying proven software designs and implementations in order to reduce the cost and improve the quality of software. A framework is a reusable, “semi-complete” application that can be specialized to produce custom applications [19]. In contrast to earlier OO reuse techniques based on class libraries, frameworks are targeted for particular business units (such as data processing or cellular communications[1]) and application domains (such as user interfaces or real-time avionics). Frameworks like MacApp, ET++, Interviews, ACE, Microsoft’s MFC and DCOM, JavaSoft’s RMI, and implementations of OMG’s CORBA play an increasingly important role in contemporary software development.

II. Object oriented concepts and techniques


The concept of objects and instances in computing had its first major breakthrough with the PDP-1 system at MIT which was probably the earliest example of ‘capability based’ architecture. Another early example was Sketchpad created by Ivan Sutherland in 1963; however, this was an application and not a programming paradigm. Objects as programming entities were introduced in the 1960s in Simula 67, a programming language designed for performing simulations, created by Ole-Johan Dahl and Kristen Nygaard of the Norwegian Computing Center in Oslo. (They were working on ship simulations, and were confounded by the combinatorial explosion of how the different attributes from different ships could affect one another. The idea occurred to them of grouping the different types of ships into different classes of objects; each class of objects being responsible for defining its own data and behavior.) Such an approach was a simple extrapolation of concepts earlier used in analog programming. On analog computers, mapping from real-world phenomena/objects to analog phenomena/objects (and conversely), was (and is) called ‘simulation’. Simula not only introduced the notion of classes, but also of instances of classes, which is probably the first explicit use of those notions. The ideas of Simula 67 influenced many later languages, especially Smalltalk and derivatives of Lisp and Pascal.

The Smalltalk language, which was developed at Xerox PARC[2] (by Alan Kay and others) in the 1970s, introduced the term object-oriented programming to represent the pervasive use of objects and messages as the basis for computation. Smalltalk creators were influenced by the ideas introduced in Simula 67, but Smalltalk was designed to be a fully dynamic system in which classes could be created and modified dynamically rather than statically as in Simula 67. Smalltalk and with it OOP were introduced to a wider audience by the August 1981 issue of Byte magazine.

In the 1970s, Kay’s Smalltalk work had influenced the Lisp community to incorporate object-based techniques which were introduced to developers via the Lisp machine. Experimentation with various extensions to Lisp (like LOOPS and Flavors introducing multiple inheritance and mixins), eventually led to the Common Lisp Object System (CLOS, a part of the first standardized object-oriented programming language, ANSI Common Lisp), which integrates functional programming and object-oriented programming and allows extension via a Meta-object protocol. In the 1980s, there were a few attempts to design processor architectures which included hardware support for objects in memory but these were not successful. Examples include the Intel iAPX 432 and the Linn Smart Rekursiv.

Object-oriented programming developed as the dominant programming methodology during the mid-1990s, largely due to the influence of Visual FoxPro 3.0 or possibly C++. Its dominance was further enhanced by the rising popularity of graphical user interfaces, for which object-oriented programming seems to be well-suited. An example of a closely related dynamic GUI library and OOP language can be found in the Cocoa frameworks on Mac OS X, written in Objective-C, an object-oriented, dynamic messaging extension to C based on Smalltalk. OOP toolkits also enhanced the popularity of event-driven programming (although this concept is not limited to OOP). Some feel that association with GUIs (real or perceived) was what propelled OOP into the programming mainstream.

At ETH Zürich, Niklaus Wirth and his colleagues had also been investigating such topics as data abstraction and modular programming (although this had been in common use in the 1960s or earlier). Modula-2 (1978) included both, and their succeeding design, Oberon, included a distinctive approach to object orientation, classes, and such. The approach is unlike Smalltalk, and very unlike C++.

Object-oriented features have been added to many existing languages during that time, including Ada, BASIC, Fortran, Pascal, and others. Adding these features to languages that were not initially designed for them often led to problems with compatibility and maintainability of code.

More recently, a number of languages have emerged that are primarily object-oriented yet compatible with procedural methodology, such as Python and Ruby. Probably the most commercially important recent object-oriented languages are Visual Basic.NET (VB.NET) and C#, both designed for Microsoft’s .NET platform, and Java, developed by Sun Microsystems. VB.NET and C# both support cross-language inheritance, allowing classes defined in one language to subclass classes defined in the other language.

Just as procedural programming led to refinements of techniques such as structured programming, modern object-oriented software design methods include refinements such as the use of design patterns, design by contract, and modeling languages (such as UML).

The term OOPS, which refers to an object-oriented programming system, was common in early development of object-oriented programming.

III. Fundamental concepts and features


Defines the abstract characteristics of a thing (object), including the thing’s characteristics (its attributes, fields or properties) and the thing’s behaviors (the things it can do, or methods, operations or features). One might say that a class is a blueprint or factory that describes the nature of something. For example, the class Dog would consist of traits shared by all dogs, such as breed and fur color (characteristics), and the ability to bark and sit (behaviors). Classes provide modularity and structure in an object-oriented computer program. A class should typically be recognizable to a non-programmer familiar with the problem domain, meaning that the characteristics of the class should make sense in context. Also, the code for a class should be relatively self-contained (generally using encapsulation). Collectively, the properties and methods defined by a class are called members.


A pattern (exemplar) of a class. The class Dog defines all possible dogs by listing the characteristics and behaviors they can have; the object Lassie is one particular dog, with particular versions of the characteristics. A Dog has fur; Lassie has brown-and-white fur.


One can have an instance of a class; the instance is the actual object created at runtime. In programmer jargon, the Lassie object is an instance of the Dog class. The set of values of the attributes of a particular object is called its state. The object consists of state and the behavior that’s defined in the object’s class.

More on Classes, Metaclasses, Parameterized Classes, and Exemplars

There are two broad categories of objects: classes and instances. Users of object-oriented technology usually think of classes as containing the information necessary to create instances, i.e., the structure and capabilities of an instance is determined by its corresponding class. There are three commonly used (and different) views on the definition for “class”:

  • A class is a pattern, template, or blueprint for a category of structurally identical items. The items created using the class are called instances. This is often referred to as the “class as a `cookie cutter'” view. As you might guess, the instances are the “cookies.”
  • A class is a thing that consists of both a pattern and a mechanism for creating items based on that pattern. This is the “class as an `instance factory'” view; instances are the individual items that are “manufactured” (created) using the class’s creation mechanism.
  • A class is the set of all items created using a specific pattern. Said another way, the class is the set of all instances of that pattern.

We should note that it is possible for an instance of a class to also be a class. A metaclass is a class whose instances themselves are classes. This means when we use the instance creation mechanism in a metaclass, the instance created will itself be a class. The instance creation mechanism of this class can, in turn, be used to create instances — although these instances may or may not themselves be classes.

A concept very similar to the metaclass is the parameterized class. A parameterized class is a template for a class wherein specific items have been identified as being required to create non-parameterized classes based on the template. In effect, a parameterized class can be viewed as a “fill in the blanks” version of a class. One cannot directly use the instance creation mechanism of a parameterized class. First, we must supply the required parameters, resulting in the creation of a non-parameterized class. Once we have a non-parameterized class, we can use its creation mechanisms to create instances.

In this paper, we will use the term “class” to mean metaclass, parameterized class, or a class that is neither a metaclass nor a parameterized class. We will make a distinction only when it is necessary to do so. Further, we will occasionally refer to “non-class instances.” A non-class instance is an instance of a class, but is itself not a class. An instance of a metaclass, for example, would not be a non-class instance.

In this paper, we will sometimes refer to “instantiation.” Instantiation has two common meanings:

  • as a verb, instantiation is the process of creating an instance of a class, and
  • as a noun, an instantiation is an instance of a class.

Some people restrict the use of the term “object” to instances of classes. For these people, classes are not objects. However, when these people are confronted with the concepts of metaclasses and parameterized classes, they have a difficulty attempting to resolve the “problems” these concepts introduce. For example, is a class that is an instance of a metaclass an object — even though it is itself a class? In this paper, we will use the term “object” to refer to both classes and their instances. We will only distinguish between the two when needed.

Black Boxes and Interfaces

Objects are “black boxes.” Specifically, the underlying implementations of objects are hidden from those that use the object. In object-oriented systems, it is only the producer (creator, designer, or builder) of an object that knows the details about the internal construction of that object. The consumers (users) of an object are denied knowledge of the inner workings of the object, and must deal with an object via one of its three distinct interfaces:

  • The “public” interface. This is the interface that is open (visible) to everybody.
  • The “inheritance” interface. This is the interface that is accessible only by direct specializations of the object. (We will discuss inheritance and specialization later in this chapter.) In class-based object-oriented systems, only classes can provide an inheritance interface.
  • The “parameter” interface. In the case of parameterized classes, the parameter interface defines the parameters that must be supplied to create an instance of the parameterized class.

Another way of saying that an item is in the public interface of an object is to say that the object “exports” that item. Similarly, when an object requires information from outside of itself (e.g., as with the parameters in a parameterized class), we can say that the object needs to “import” that information.


It is, of course, possible for objects to be composed of other objects. Aggregation is either:

  • The process of creating a new object from two or more other objects, or
  • An object that is composed of two or more other objects.

For example, a date object could be fashioned from a month object, a day object, and a year object. A list of names object, for example, can be thought of as containing many name objects.

A monolithic object is an object that has no externally-discernible structure. Said another way, a monolithic object does not appear to have been constructed from two or more other objects. Specifically, a monolithic object can only be treated as a cohesive whole. Those outside of a monolithic object cannot directly interact with any (real or imagined) objects within the monolithic object. A radio button in a graphical user interface (GUI) is an example of a monolithic object.

Composite objects are objects that have an externally-discernible structure, and the structure can be addressed via the public interface of the composite object. The objects that comprise a composite object are referred to as component objects. Composite objects meet one or both of the following criteria:

    • The state of a composite object is directly affected by the presence or absence of one or more of its component objects, and/or
    • The component objects can be directly referenced via the public interface of their corresponding composite object.

It is useful to divide composite objects into two subcategories: heterogeneous composite objects and homogeneous composite objects:

  • A heterogeneous composite object is a composite object that is conceptually composed of component objects that are not all conceptually the same. For example, a date (made up of a month object, a day object, and a year object) is a heterogeneous composite object.
  • A homogeneous composite object is a composite object that is conceptually composed of component objects that are all conceptually the same. For example, a list of addresses is a homogeneous composite object.

The rules for designing heterogeneous composite objects are different from the rules for designing homogeneous composite objects.

Specialization and Inheritance

Aggregation is not the only way in which two objects can be related. One object can be a specialization of another object. Specialization is either:

  • The process of defining a new object based on a (typically) more narrow definition of an existing object, or
  • An object that is directly related to, and more narrowly defined than, another object.

Specialization is usually associated with classes. It is usually only in the so-called “classless” object-oriented systems that we think of specialization for objects other than classes.

Depending on their technical background, there are a number of different ways in which people express specialization. For example, those who are familiar with an object-oriented programming language called Smalltalk refer to specializations as “subclasses” and to the corresponding generalizations of these specializations as “superclasses.” Those with a background in the C++ programming language use the term “derived class” for specialization and “base class” for corresponding generalizations.

It is common to say that everything that is true for a generalization is also true for its corresponding specialization. We can, for example, define “checking accounts” and “savings accounts” as specializations of “bank accounts.” Another way of saying this is that a checking account is a kind of bank account, and a savings account is a kind of bank account. Still another way of expressing this idea is to say that everything that was true for the bank account is also true for the savings account and the checking account.

In an object-oriented context, we speak of specializations as “inheriting” characteristics from their corresponding generalizations. Inheritance can be defined as the process whereby one object acquires (gets, receives) characteristics from one or more other objects. Some object-oriented systems permit only single inheritance, a situation in which a specialization may only acquire characteristics from a single generalization. Many object-oriented systems, however, allow for multiple inheritance, a situation in which a specialization may acquire characteristics from two or more corresponding generalizations.

Our previous discussion of the bank account, checking account, and savings account was an example of single inheritance. A telescope and a television set are both specializations of “device that enables one to see things far away.” A television set is also a kind of “electronic device.” You might say that a television set acquires characteristics from two different generalizations, “device that enables one to see things far away” and “electronic device.” Therefore, a television set is a product of multiple inheritance.

Abstract Classes

We usually think of classes as being complete definitions. However, there are situations where incomplete definitions are useful, and classes that represent these incomplete definitions are equally useful. For example, in everyday conversation, we might talk about such items as bank accounts, insurance policies, and houses. In object-oriented thinking, we often isolate useful, but incomplete, concepts such as these into their own special classes.

Abstract classes are classes that embody coherent and cohesive, but incomplete, concepts, and in turn, make these characteristics available to their specializations via inheritance. People sometimes use the terms “partial type” and “abstract superclass” as synonyms for abstract class. While we would never create instances of abstract classes, we most certainly would make their individual characteristics available to more specialized classes via inheritance.

For example, consider the concept of an automobile. On one hand, most people know what an automobile is. On the other hand, “automobile” is not a complete definition for any vehicle. It would be quite accurate to describe “automobile” as the set of characteristics that make a thing an automobile, in other words, the “essence of automobile-ness.”


The public interface of an object typically contains three different categories of items:

  • operations (sometimes referred to as “method selectors,” “method interfaces,” “messages,” or “methods”),
  • constants, and
  • exceptions.

An operation in the public interface of an object advertises a functional capability of that object. For example, “deposit” would be an operation in the public interface of a bank account object, “what is current temperature” would be an operation in the public interface of a temperature sensor object, and “increment” would be an operation in the public interface of a counter object.

The actual algorithm for accomplishing an operation is referred to as a method. Unlike operations, methods are not in the public interface for an object. Rather, methods are hidden on the inside of an object. So, while users of bank account objects would know that they could make a deposit into a bank account, they would be unaware of the details as to how that deposit actually got credited to the bank account.

We refer to the operations in the public interface of an object as “suffered operations.” Suffered operations are operations that meet two criteria: they are things that happen to an object, and they are in the public interface of that object. For example, we can say that a bank account “suffers” the operation of having a deposit made into it. The bank account can also “suffer” the operation of being queried as to its current balance. Some people also refer to suffered operations as “exported operations.”

There are three broad categories of suffered operations, i.e.:

  • A selector is an operation that tells us something about the state of an object, but cannot, by definition, change the state of the object. An operation that tells us the current balance of a bank account is an example of a selector operation.
  • A constructor is an operation that has the ability to change the state of an object. For example, an operation in the public interface to a mailbox object that added a message to the mailbox would be a constructor operation. (Please note that some people restrict the definition of the term “constructor” to those operations that cause instances of a class to come into existence.)
  • In the context of a homogeneous composite object, an iterator is an operation that allows its users to visit (access) each of the component objects that make up the homogeneous composite object. If we have a list of addresses, for example, and we wish to print the entire list, an iterator would allow us to visit each address object within the list and then, in turn, to print each address.

Iterators can be further divided into two broad categories: active (open) iterators and passive (closed) iterators. Active iterators are objects in their own right. Passive iterators are implemented as operations in the interface of the object over which they allow iteration. Passive iterators are further broken down into selective iterators and constructive iterators. Passive selective iterators do not allow their users to change the object over which the iteration takes place. Passive constructive iterators do allow users to change the object over which iteration takes place.

We can also describe suffered operations as primitive or composite. A primitive operation is an operation that cannot be accomplished simply, efficiently, and reliably without direct knowledge of the underlying (hidden) implementation of the object. As an example, we could argue that an operation that added an item to a list object, or an operation that deleted an item from a list object were primitive operations with respect to the list object.

Suppose that we wanted to create a “swap operation,” an operation that would swap in a new item in a list, while at the same time swapping out an old item in the same list. This is not a primitive operation since we can accomplish this with a simple combination of the delete operation (deleting the old item) followed by the add operation (adding the new item). The swap operation is an example of a composite operation. A composite operation is any operation that is composed, or can be composed, of two or more primitive operations.

Sometimes objects need help in maintaining their characteristics. Suppose, for example, that we wanted to create a “generic ordered list” object. An ordered list is a list that must order its contents from the smallest to the largest. Specifically, every time we add an item to our ordered list, that item would have to be placed in its proper position with respect to all the other items already in the list. By “generic,” we mean a template that can be instantiated with the category (class) of items we wish to place in the ordered list.

It would not be unreasonable to implement this object as a parameterized class. Obviously, one of the parameters would be the category of items (e.g., class) that we desired to place in the list. For example, could instantiate (make an instance) the generic ordered list with a “name class” resulting in the creation of an “ordered list of names class.”

There is a problem, however. Given that we could instantiate the generic ordered list with just about any category of items, how can we be sure that the ordered lists will know how to properly maintain order — no matter what we use to instantiate the generic ordered list? Suppose, for example, that we wanted an ordered list of “fazoomas.” How could the generic list class tell if one fazooma was greater than or less than another fazooma?

A solution would be for the generic ordered list to require a second parameter, a parameter over and above the category of items (class) that we desired to place in the list. This second parameter would be a “<” (less than) operation that worked with the category of items to be placed in the list. In the case of our ordered list of fazoomas, this second parameter would be a “<” that works with fazoomas.

The “<” that worked with fazoomas is an example of a required operation. A required operation is an operation that an object needs to maintain its outwardly observable characteristics, but which the object cannot supply itself. Some people refer to required operations as “imported operations.”


In addition to suffered operations, the public interface of an object can also contain constants. Constants are objects of constant state. Imagine that we want to create a “bounded list of addresses class.” A bounded list is a list that has a fixed maximum number of elements. A bounded list can be empty, and it can contain fewer than the maximum number of elements. It can even contain the maximum number of elements, but it can never contain more than the defined maximum number of elements.

Assume that we place a constant in the public interface of our bounded list of addresses. This constant represents the maximum number of elements that can be placed in the bounded list. Assume also that there is a suffered operation that will tell us how many elements (addresses, in our example) are currently in the bounded list. We can now determine how much room is available in the bounded list by inquiring how many addresses are already in the list, and then subtracting this from the previously-defined constant.

In some cases, as with the bounded list example above, constants are provided more for convenience than necessity. In other cases, such as in the case of encryption algorithms needing a “seed value,” constants are an absolute requirement.


A third category of items that can be found in the public interface of objects is exceptions. Exceptions have two different definitions:

  • an event that causes suspension of normal application execution, and
  • a set of information directly relating to the event that caused suspension of normal application execution.

Exceptions can be contrasted with an older, less reliable technology: “error codes.” The idea behind error codes was fairly simple. You would request that an application, or part of an application, accomplish some work. One of the pieces of information that would be returned to the requester would be an error code. If all had gone well, the error code would typically have a value of zero. If any problems had occurred, the error code would have a non-zero value. It was also quite common to associate different non-zero values of an error code with specific errors.

Error codes suffered from two major problems:

    • No one was forced to actually check the value of returned error codes.
    • Changes (additions, deletions, and modifications) in the meanings of the special values assigned to error codes were not automatically passed on to interested parties. Tracking the effects of a changed error code value often consumed a significant amount of resources.

To understand how exceptions directly address both of these issues, we first need to understand how exceptions typically work:

    • Exceptions may be defined by the environment or by the user.
    • When an exceptional (but not unforeseen) condition occurs, an appropriate exception is activated. (People use different terms to express the activation of an exception. The most common is “raise.” Less commonly, people use the terms “throw” or “activate.”) This activation may be automatic (controlled by the environment) or may be expressly requested by the designer of the object or application.

Examples of exceptional conditions include trying to remove something from an empty container, directing an elevator on the top floor to “go up,” and attempting to cause a date to take on an invalid value like “February 31, 1993.”

  • Once the exception is activated, normal application execution stops and control is transferred to a locally defined exception handler, if one is present. If no locally defined exception handler is present or if the exception handler is not equipped to handle the exception, the exception is propagated to the next higher level of the application. Exceptions cannot be ignored. An exception will continue to be sent to higher levels of the application until it is either turned off or the application ceases to function.
  • An exception handler checks to see what type of exception has been activated. If the exception is one that the handler recognizes, a specific set of actions is taken. Executing a set of actions in response to an exception is known as “handling the exception.” Handling an exception deactivates the exception; the exception will not be propagated any further.

Unlike error codes, exceptions cannot be ignored. Once an exception has been activated, it demands attention. In object-oriented systems, exceptions are placed in the public interfaces of objects. Changes in the public interfaces of objects very often require an automatic rechecking of all other objects that invoke operations in the changed objects. Thus, changes in exceptions result in at least a partially automated propagation of change information.

Object Coupling and Object Cohesion

Engineers have known for centuries that the less any one part of a system knows about any other part of that same system, the better the overall system. Systems whose components are highly independent of each other are easier to fix and enhance than systems where there are strong interdependencies among some or all of the components. Highly independent system components are possible when there is minimal coupling among the components, and each component is highly cohesive.

Coupling is a measure of the strength of the connection between any two system components. The more any one component knows about another component, the tighter (worse) the coupling is between those two components. Cohesion is a measure of how logically related the parts of an individual component are to each o

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