[fc417fc802]

No, it doesn't "depend on how you calculate statistics". Or rather you are not asking the right question. We do not care if a different person suffers a false negative. The question is if you, personally, are likely to suffer a false negative. In other words, will any given real world deployment of the solution be expected to suffer from an unacceptably high rate of false negatives?

Answering that requires figuring out two things. The sort of real world deployment you're designing for and what the acceptable false negative rate is. For an extremely conservative lower bound suppose 1 error per TiB per year and suppose 1000 TiB of storage. That gives a 99.99998% success rate for any given year. That translates to expecting 1 false negative every 4 million years.

I don't know about you but I certainly don't have anywhere near a petabyte of data, I don't suffer corruption at anywhere near a rate of 1 event per TiB per year, and I'm not in the business of archiving digital data on a geological timeframe.

32 bits is more than fit for purpose.

[zigzag312]

I can't say I agree with your logic here. We are not talking about any specific backup or anything like that. We are talking about the design of a file format that is going to be used globally.

Business running a lottery has to calculate the odds of anyone winning, not just the odds of a single person winning. Same, a designer of a file format has to consider chances for all users. What percent of users will be affected by any design decision.

For example, what if you would offer a guarantee that 32 bit hash will protect you from corruption, and compensate generously anyone who would get this type of corruption; how would you calculate probability then?

[fc417fc802]

If you offer compensation then of course you need to consider your risk exposure, ie total users. That's similar to a lottery where the central authority is concerned with all payouts while an individual is only concerned with their own payout.

Outside of brand reputation issues that is not how real world products are designed. You design a tool for the specific task it will be used for. You don't run your statistics in aggregate based on the expected number of customers.

Users are independent from one another. If the population doubles my filesystem doesn't suddenly become less reliable. If more people purchase the same laptop that I have the chance of mine failing doesn't suddenly go up. If more people deep fry things in their kitchen my own personal risk of a kitchen fire isn't increased regardless of how busy the fire department might become.