Code generation is not a new style or technique, it’s the path followed by programming languages to deal with complexity, from binary coding to first, second and next generation languages. It’s what compilers have been doing for ages.

The key subject here is “deal with complexity”, the more complex is your problem more abstract has to be your thinking. In other words, you need to raise the level of abstraction. And this rule applies equally to the tool used to solve the problem: the programming language.

Therefore, we can state that “raising the level of abstraction is the goal pursued by the evolution of programming languages”.

The common languages used today to solve the problems( Java, C#, C++, Delphi…), are known as general purpose languages (GPLs), and here is the problem, they are “general purpose”, it means they can solve “all” the problems but from a global perspective. They can solve them from a level of abstraction wide enough to reach the solution but not as high as we need on each particular problem. There is a gap between the level of abstraction we use to deal with the problem and the level of abstraction we use to solve it via GPLs.

How can we bridge that gap? Obviously, with code generation.

As a conclusion, to tackle properly a problem, we need to find a particular language to define the solution in the level of abstraction each particular problem requires. In order to make that solution computable, we need to generate code, usually in the nearest lower level: GPL’s.

Those particular languages are known as DSLs: Domain-Specific Languages, but this subject will be addressed in another post.

As a conclusion, we can note that this approach does not only apply to business problems but also to solving technical problems. For example, the new challenges offered desktop-web applications require a more abstract approach that integrates all technologies: HTML, CSS, JavaScrpit, AJAX and others.
 

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