The progress of abstraction
All programming languages provide abstractions. It can be argued that the complexity of the problems you’re able to solve is directly related to the kind and quality of abstraction. By “kind” I mean, “What is it that you are abstracting?” Assembly language is a small abstraction of the underlying machine. Many so-called “imperative” languages that followed (such as FORTRAN, BASIC, and C) were abstractions of assembly language. These languages are big improvements over assembly language, but their primary abstraction still requires you to think in terms of the structure of the computer rather than the structure of the problem you are trying to solve. The programmer must establish the association between the machine model (in the “solution space,” which is the place where you’re modeling that problem, such as a computer) and the model of the problem that is actually being solved (in the “problem space,” which is the place where the problem exists). The effort required to perform this mapping, and the fact that it is extrinsic to the programming language, produces programs that are difficult to write and expensive to maintain, and as a side effect created the entire “programming methods” industry.
The alternative to modeling the machine is to model the problem you’re trying to solve. Early languages such as LISP and APL chose particular views of the world (“All problems are ultimately lists” or “All problems are algorithmic,” respectively). PROLOG casts all problems into chains of decisions. Languages have been created for constraint-based programming and for programming exclusively by manipulating graphical symbols. (The latter proved to be too restrictive.) Each of these approaches is a good solution to the particular class of problem they’re designed to solve, but when you step outside of that domain they become awkward.
The object-oriented approach goes a step further by providing tools for the programmer to represent elements in the problem space. This representation is general enough that the programmer is not constrained to any particular type of problem. We refer to the elements in the problem space and their representations in the solution space as “objects.” (You will also need other objects that don’t have problem-space analogs.) The idea is that the program is allowed to adapt itself to the lingo of the problem by adding new types of objects, so when you read the code describing the solution, you’re reading words that also express the problem. This is a more flexible and powerful language abstraction than what we’ve had before. Thus, OOP allows you to describe the problem in terms of the problem, rather than in terms of the computer where the solution will run. There’s still a connection back to the computer: each object looks quite a bit like a little computer—it has a state, and it has operations that you can ask it to perform. However, this doesn’t seem like such a bad analogy to objects in the real world—they all have characteristics and behaviors.
Alan Kay summarized five basic characteristics of Smalltalk, the first successful object-oriented language and one of the languages upon which Java is based. These characteristics represent a pure approach to object-oriented programming:
Everything is an object. Think of an object as a fancy variable; it stores data, but you can “make requests” to that object, asking it to perform operations on itself. In theory, you can take any conceptual component in the problem you’re trying to solve (dogs, buildings, services, etc.) and represent it as an object in your program.
A program is a bunch of objects telling each other what to do by sending messages. More concretely, you can think of a message as a request to call a method that belongs to a particular object.
Each object has its own memory made up of other objects. Put another way, you create a new kind of object by making a package containing existing objects. Thus, you can build complexity into a program while hiding it behind the simplicity of objects.
Every object has a type. Using the parlance, each object is an instance of a class, in which “class” is synonymous with “type.” The most important distinguishing characteristic of a class is “What messages can you send to it?”
All objects of a particular type can receive the same messages. This is actually a loaded statement, as you will see later. Because an object of type “circle” is also an object of type “shape,” a circle is guaranteed to accept shape messages. This means you can write code that talks to shapes and automatically handle anything that fits the description of a shape. This substitutability is one of the powerful concepts in OOP.
Booch offers an even more succinct description of an object:
An object has state, behavior and identity.
This means that an object can have internal data (which gives it state), methods (to produce behavior), and each object can be uniquely distinguished from every other object—to put this in a concrete sense, each object has a unique address in memory.
An object has an interface
Aristotle was probably the first to begin a careful study of the concept of type; he spoke of “the class of fishes and the class of birds.” The idea that all objects, while being unique, are also part of a class of objects that have characteristics and behaviors in common was used directly in the first object-oriented language, Simula-67, with its fundamental keyword class that introduces a new type into a program.
Simula, as its name implies, was created for developing simulations such as the classic “bank teller problem.” In this, you have a bunch of tellers, customers, accounts, transactions, and units of money—a lot of “objects.” Objects that are identical except for their state during a program’s execution are grouped together into “classes of objects” and that’s where the keyword class came from. Creating abstract data types (classes) is a fundamental concept in object-oriented programming. Abstract data types work almost exactly like built-in types: You can create variables of a type (called objects or instances in object-oriented parlance) and manipulate those variables (called sending messages or requests; you send a message and the object figures out what to do with it). The members (elements) of each class share some commonality: every teller can accept a deposit, etc. At the same time, each member has its own state: each account has a different balance, each teller has a name. Thus, the tellers, customers, accounts, transactions, etc., can each be represented with a unique entity in the computer program. This entity is the object, and each object belongs to a particular class that defines its characteristics and behaviors.
So, although what we really do in object-oriented programming is create new data types, virtually all object-oriented programming languages use the “class” keyword. When you see the word “type” think “class” and vice versa.
Since a class describes a set of objects that have identical characteristics (data elements) and behaviors (functionality), a class is really a data type because a floating point number, for example, also has a set of characteristics and behaviors. The difference is that a programmer defines a class to fit a problem rather than being forced to use an existing data type that was designed to represent a unit of storage in a machine. You extend the programming language by adding new data types specific to your needs. The programming system welcomes the new classes and gives them all the care and type-checking that it gives to built-in types.
The object-oriented approach is not limited to building simulations. Whether or not you agree that any program is a simulation of the system you’re designing, the use of OOP techniques can easily reduce a large set of problems to a simple solution.
Once a class is established, you can make as many objects of that class as you like, and then manipulate those objects as if they are the elements that exist in the problem you are trying to solve. Indeed, one of the challenges of object-oriented programming is to create a one-to-one mapping between the elements in the problem space and objects in the solution space.
But how do you get an object to do useful work for you? There must be a way to make a request of the object so that it will do something, such as complete a transaction, draw something on the screen, or turn on a switch. And each object can satisfy only certain requests. The requests you can make of an object are defined by its interface, and the type is what determines the interface. A simple example might be a representation of a light bulb:
Light
On()
Off()
Light lt = new Light();
lt.on();
The interface establishes what requests you can make for a particular object. However, there must be code somewhere to satisfy that request. This, along with the hidden data, comprises the implementation. From a procedural programming standpoint, it’s not that complicated. A type has a method associated with each possible request, and when you make a particular request to an object, that method is called. This process is usually summarized by saying that you “send a message” (make a request) to an object, and the object figures out what to do with that message (it executes code).
Here, the name of the type/class is Light, the name of this particular Light object is lt, and the requests that you can make of a Light object are to turn it on, turn it off, make it brighter, or make it dimmer. You create a Light object by defining a “reference” (lt) for that object and calling new to request a new object of that type. To send a message to the object, you state the name of the object and connect it to the message request with a period (dot). From the standpoint of the user of a predefined class, that’s pretty much all there is to programming with objects.
The preceding diagram follows the format of the Unified Modeling Language (UML). Each class is represented by a box, with the type name in the top portion of the box, any data members that you care to describe in the middle portion of the box, and the methods (the functions that belong to this object, which receive any messages you send to that object) in the bottom portion of the box. Often, only the name of the class and the public methods are shown in UML design diagrams, so the middle portion is not shown. If you’re interested only in the class name, then the bottom portion doesn’t need to be shown, either
An object provides services.
While you’re trying to develop or understand a program design, one of the best ways to think about objects is as “service providers.” Your program itself will provide services to the user, and it will accomplish this by using the services offered by other objects. Your goal is to produce (or even better, locate in existing code libraries) a set of objects that provide the ideal services to solve your problem.
A way to start doing this is to ask “if I could magically pull them out of a hat, what objects would solve my problem right away?” For example, suppose you are creating a bookkeeping program. You might imagine some objects that contain pre-defined bookkeeping input screens, another set of objects that perform bookkeeping calculations, and an object that handles printing of checks and invoices on all different kinds of printers. Maybe some of these objects already exist, and for the ones that don’t, what would they look like? What services would those objects provide, and what objects would they need to fulfill their obligations? Thinking of an object as a service provider has an additional benefit: it helps to improve the cohesiveness of the object. High cohesion is a fundamental quality of software design: It means that the various aspects of a software component (such as an object, although this could also apply to a method or a library of objects) “fit together” well. One problem people have when designing objects is cramming too much functionality into one object. For example, in your check printing module, you may decide you need an object that knows all about formatting and printing. You’ll probably discover that this is too much for one object, and that what you need is three or more objects. One object might be a catalog of all the possible check layouts, which can be queried for information about how to print a check. One object or set of objects could be a generic printing interface that knows all about different kinds of printers (but nothing about bookkeeping—this one is a candidate for buying rather than writing yourself). And a third object could use the services of the other two to accomplish the task. Thus, each object has a cohesive set of services it offers. In a good object-oriented design, each object does one thing well, but doesn’t try to do too much. As seen here, this not only allows the discovery of objects that might be purchased (the printer interface object), but it also produces the possibility of an object that might be reused somewhere else (the catalog of check layouts).
Treating objects as service providers is a great simplifying tool, and it’s very useful not only during the design process, but also when someone else is trying to understand your code or reuse an object—if they can see the value of the object based on what service it provides, it makes it much easier to fit it into the design.
