Our regex found 199 records in a 1,723-record corpus and reported no errors
We maintain a corpus of 456 role-specific resume examples in TypeScript. Someone asked me what a good bullet point actually looks like, and rather than answer from taste I decided to measure the thing I already had. Fifteen minutes later we had a script, a set of numbers, and a conclusion. The conclusion was wrong, because the script had silently read about twelve percent of the data. This is a…
A regex algorithm identified 199 job descriptions within a corpus of 1,723 resume examples written in TypeScript. The script that generated the results inadvertently overlooked about twelve percent of the data. The corpus consisted of 456 role-specific resume examples, with each role's description being a newline-delimited list of bullet points.
An issue arose when the regex algorithm only matched 199 description strings instead of the expected 1,723, as some file formatting left spaces after colons, causing the regex to fail. After correcting the formatting issue, the corpus expanded to 1,723 description blocks, with 1,267 using the bullet format and yielding a total of 3,815 individual bullet points.
The median bullet contained 14 words, while the 90th percentile had 17 words. The distribution of bullet openings was heavily skewed towards common verbs like "managed," "developed," and "led," with only a small proportion using unique verbs. The corpus also showed a high density of three bullets per position, with no duplicate text found across the 3,815 bullet points.
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