The progress of abstraction

Bruce Eckel's Thinking in Java Contents | Prev | Next

All programming languages provide abstractions. It can be argued that the complexity of the problems you can 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”) and the model of the problem that is actually being solved (in the “problem space”). 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 object-oriented approach takes a step farther 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.” (Of course, 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 the terms of the solution. There’s still a connection back to the computer, though. Each object looks quite a bit like a little computer; it has a state, and it has operations 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.

  1. Everything is an object. Think of an object as a fancy variable; it stores data, but you can also ask it to perform operations on itself by making requests. 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.
  2. A program is a bunch of objects telling each other what to do by sending messages . To make a request of an object, you “send a message” to that object. More concretely, you can think of a message as a request to call a function that belongs to a particular object.
  3. Each object has its own memory made up of other objects . Or, you make a new kind of object by making a package containing existing objects. Thus, you can build up complexity in a program while hiding it behind the simplicity of objects.
  4. Every object has a type . Using the parlance, each object is an instance of a class, where “class” is synonymous with “type.” The most important distinguishing characteristic of a class is “what messages can you send to it?”
  5. All objects of a particular type can receive the same messages . This is actually a very 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 receive 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 most powerful concepts in OOP.

[2] See Multiparadigm Programming in Leda by Timothy Budd (Addison-Wesley 1995).


  • There are no comments yet. Be the first to comment!

Leave a Comment
  • Your email address will not be published. All fields are required.

Top White Papers and Webcasts

  • As all sorts of data becomes available for storage, analysis and retrieval - so called 'Big Data' - there are potentially huge benefits, but equally huge challenges...
  • The agile organization needs knowledge to act on, quickly and effectively. Though many organizations are clamouring for "Big Data", not nearly as many know what to do with it...
  • Cloud-based integration solutions can be confusing. Adding to the confusion are the multiple ways IT departments can deliver such integration...

Most Popular Programming Stories

More for Developers

RSS Feeds

Thanks for your registration, follow us on our social networks to keep up-to-date