List of falsehoods programmers believe in

If we really aspire to be an information-driven culture who makes informed decisions about important topics, we really ought to curate lists like these down to actual informed discussions on the items in the list. Printing out a list of "falsehoods" littered with personal opinions and calling them "demonstrable" [1] without a shred of evidence is not going to contribute to general knowledge. There may be some utility in getting me thinking, but for the most part I just find…

> My system will never have to deal with names from China I work in a small French town where Chinese people were quite rare until a few years ago. Their passports have a translation of their names in Latin alphabet, same for Russians. However one day one of my user told me "hey I can't find some customers in your app, but I'm 100% sure I recorded them previously. Funnily they're all Chinese". It turns out that to avoid…

I think the lesson to take from these lists is that covering every edge case for many real-world situations becomes asymptotically difficult. You can get 95% with no effort at all, 99% with a bit of thought, 99.9% with some effort, 99.99% with a smart design, some research, and a lot of effort, and anything further requires making it your full-time job indefinitely. It gets thornier when it comes to personal things like names and gender. If you tell a…

I like this a lot and it’s well worth reading over. For a lot of programming tasks, it’s best to consider these kind of lists not as falsehoods but as edge cases or assumptions that should be made explicit. Handling every “falsehood” gracefully yields a combinatoric explosion in the complexity of your data model. Sometimes it’s the right or ethical thing to do it anyway, but other times it’s by far easiest to document the assumption and move on.