It often doesn't to high degrees of precision and reliability. It works within some tolerance range and those tolerance ranges are managed or acceptable levels

It often doesn't to high degrees of precision and reliability. It works within some tolerance range and those tolerance ranges are managed or acceptable levels of error (often unnoticed). I recently helped move/port one fairly complex numeric model from a language and environment to another language and environment and there was an assumption made by upper management that this was simple and exact deterministic results would be easily had. I warned that this could be an involved process because of simple variations, lack of equivalent mappings between environments and languages, some of which pointed out in this article. Management were quite surprised with the level of effort needed to dig down layers of abstraction and identify all these sort of variations in numeric libraries from consistent high level abstractions they were familiar with, and why those high level abstractions simply didn't exist in the other language and environment. They were additionally surprised inthe level of effort needed to get satisfactory error tolerance ranges between the two models when having to recreate high level abstractions identically from the source language and environment to the target language and environment that simply didn't exist prior to the work. They didn't realize the variation until we performed a detailed analysis on results and found very small but statistically distinguishable results from the two versions. We ended up identifying a few dozen small assumptions they made about their high level abstractions from the source environment that were false and caused the variation.