On code duplication. I am "lazy" programmer. Every time I start writing a new code I don't care about code duplication. Human's brain tends to duplicate things, it's just tedious to think about good abstractions from the very beginning. However one day, as proper time comes or when I start getting tired of copy/paste (: I look at my code and start refactoring it making good abstractions and reducing code duplication.
I also am very in line with the "lazy" programming style. I think it's more intuitive, and helps to not fall on the trap of wrong abstractions, as Ricardo Rivas also commented
Once some of the code has already been written, the problem space and the solution become clearer, and then it's also easier - and makes more sense - to create abstractions.
It's best to realise that when you start programming, you only know about 40%, if that, of the problem space. As we create a fitting solution for the actual problem we learn the other 60% that we were ignorant about when we started. The more we know about the problem space, the better, or more precise, the abstractions are going to be.
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On code duplication. I am "lazy" programmer. Every time I start writing a new code I don't care about code duplication. Human's brain tends to duplicate things, it's just tedious to think about good abstractions from the very beginning. However one day, as proper time comes or when I start getting tired of copy/paste (: I look at my code and start refactoring it making good abstractions and reducing code duplication.
I love the concept in this post thanks Conlin :)
I also am very in line with the "lazy" programming style. I think it's more intuitive, and helps to not fall on the trap of wrong abstractions, as Ricardo Rivas also commented
Same here - I think you're a good programmer :)
Once some of the code has already been written, the problem space and the solution become clearer, and then it's also easier - and makes more sense - to create abstractions.
It's best to realise that when you start programming, you only know about 40%, if that, of the problem space. As we create a fitting solution for the actual problem we learn the other 60% that we were ignorant about when we started. The more we know about the problem space, the better, or more precise, the abstractions are going to be.