Regular expression speed and error rates

This article revisits a seven-year-old post on using regular expressions to match ICD-10 diagnosis codes, focusing on speed and error rates. It compares a regex approach (18 ms for an 800kb file) against an exhaustive list search (386 seconds), highlighting regex's massive speed advantage. It also examines false negatives (3 out of 74,719 codes missed due to standard changes) and false positives, arguing regex is more future-proof than a static list. The article is relevant to programming, regex optimization, and tech best practices.