Programming, in its broadest sense, is problem solving. It begins when we look out into the world and see problems that we want to solve, problems that we think can and should be solved using a digital computer. Understanding the problem well is the first – and probably the most important step in programming, because without that understanding we may find ourselves wandering aimlessly down a dead-end alley, or worse, down a fruitless alley with no end. “Solving the wrong problem” is a phrase often heard in many contexts, and we certainly don't want to be victims of that crime. So the first step in programming is answering the question, “What problem am I trying to solve?”

Once you understand the problem, then you must find a solution. This may not be easy, of course, and in fact you may discover several solutions, so we also need a way to measure success. There are various dimensions in which to do this, including correctness (“Will I get the right answer?”) and efficiency (“Will I have enough resources?”). But the distinction of which solution is better is not always clear, because the number of dimensions can be large, and programs will often excel in one dimension and do poorly in others. For example, there may be one solution that is fastest, one that uses the least amount of memory, and one that is easiest to understand. Choosing can be difficult and is one of the more interesting challenges that you will face in programming.

The last measure of success mentioned above – clarity of a program – is somewhat elusive, most difficult to measure, and, quite frankly, sometimes difficult to rationalize. But in large software systems clarity is an especially important goal, because the most important maxim about such systems is that they are never really finished! The process of continuing work on a software system after it is delivered to users is what software engineers call software maintenance, and is the most expensive phase of the so-called “software lifecycle.”