Today I'm full of questions. Software development and programming is hard. Is a close encounter with layers and layers of complexity. Once we master one level, we open a whole new level. To tackle it one must employ multiple techniques. But they always involve trade-offs. How to balance programming using standard and maybe cumbersome idioms vs more elegant but more obscure idioms? What if the programming style is too personal and strange to others? Shall we settle for the lowest common denominator ? How do we balance the conflict between something harder to understand at first but easier to extend and maintain against something more familiar but with exponential complexity growth after each change? How do we maintain the "conceptual integrity" (F. Brooks) through the life of the system? As the project complexity grows, the need for sophisticated techniques increases. (I'm coming to the conclusion that if a developer can't comprehend some level of complexity, shouldn't be allowed to participate in the project without close mentoring). Refactoring is necessary because entropy. Every code base starts to degrade and loose integrity as evolves. I wonder if there's a code entropy metric... At what point a refactoring is good enough? When do you stop? At least your architecture should be stable, or you didn't validate it. I guess complexity is in the eye of the beholder. I found that a system composed of smaller simple pieces with complex interactions is easier to evolve than bigger pieces with simple interactions because each piece is internally complex and the limited interactions means its harder to combinate them in new ways. Of course, gratuitous complexity should be avoided at all costs. Sometimes I look for a "zen" approach to coding. At the end, I always take a pragmatic approach and find a trade-off that balances the forces. Isn't coding about that? Each line you write is a choice you need to make... At some point we need to use "introspection" and "metaprogramming" but not the programming techniques: introspection on how we approach problem solving and programming and metaprogramming on what we can do to program better.
