Sometimes, our algorithms seem to "make mistakes". This could be because of an underlying bug, flaw, or error, as explained below:
Bugs - arise when something a human authored (e.g., code or data) doesn't do what is intended (e.g., documented). They are fixed by correcting the implementation to fix what is intended.
Flaws - arise when the design of the software doesn't do what is desired by those who authored the design. Flaws are sometimes called 'conceptual bugs'.
Errors - arise when an inherent limitation of an algorithm is exposed despite the algorithm having been implemented as intended. For software that employs approximate algorithms these are common. Some errors are "howlers" – ones you're surprised the algorithm gets wrong or ones only a machine could make. They are fixed by changing the algorithm, possibly quite significantly.
If you find the errors seem to follow some pattern rather than being more random, we'd be glad for you to share any analysis of error patterns as well as data so that we can consider if it might be possible to improve the relevant statistical model in a future release.