> Rule 5. Data dominates. If you've chosen the right data structures and organized things well, the algorithms will almost always be self-evident. Data structures, not algorithms, are central to programming.
If want to solve a problem - it's natural to think about logic flow and the code that implements that first and the data structures are an after thought, whereas Rule 5 is spot on.
Conputers are machines that transform an input to an output.
It is?
How can you conceive of a precise idea of how to solve a problem without a similarly precise idea of how you intend to represent the information fundamental to it? They are inseparable.
Do you start with the logical task first and structure the data second, or do you actually think about the data structures first?
Let's say I have a optimisation problem - I have a simple scoring function - and I just want to find the solution with the best score. Starting with the logic.
for all solutions, score, keep if max.
Simple eh? Problem is it's a combinatorial solution space. The key to solving this before the entropic death of the universe is to think about the structure of the solution space.
Neither data structures nor algorithms, but entities and tasks, from the user POV, one level up from any kind of implementation detail.
There's no point trying to do something if you have no idea what you're doing, or why.
When you know the what and why you can start worrying about the how.
Iff this is your 50th CRUD app you can probably skip this stage. But if it's green field development - no.
eg sort a list.
That's why a collection of "obvious" things formulated in a convincing way by a person with big street cred is still useful and worth elevating.
"Why quote someone who's just quoting someone else?" — Michael Scott — knorker