didi/dokit: technical due diligence, read from its repository

37% of commit subjects are exact repeats of another subject, and subject length varies by only 20.0 characters. A log written by someone explaining their reasoning to a future reader does not look like this. The log is therefore weak evidence of intent, whatever the code is like.

The median source file here is 52 lines. 17 files exceed 1,000 lines, the largest being 2,528. Size is not a defect on its own — some problems genuinely live in one place — but these are where merge conflicts, review fatigue and single-owner knowledge concentrate, and they are the first thing that slows an inheriting engineer down.

430 product files are in the new language and 715 are still in the old one, 64 months after the first new file appeared. The new language's share of the lines rose from 5% to 25%, and moved 0 percentage points in the last year. Two languages for one job doubles what an engineer has to know, and the unmoved half is usually what nobody wants to touch. Ask whether finishing it is planned, and what it costs.

Of five ordinary markers — CI workflows, CODEOWNERS, a pull-request template, pre-commit hooks, contribution guidance — 1 is present: contribution guidance. Branch protection itself is a GitHub setting rather than a file, so this is a reading of proxies and not of the rules themselves. What it does establish is that the process is not written down anywhere a new engineer would find it.

3 places read data with a deserialiser that executes what it reads (Java object streams). That is safe on data the system wrote itself and remote code execution on anything else. Ask where each one's input comes from.

6 places set HTML from a value that is neither a literal nor passed through a sanitiser. Where the value can come from a user, that is stored cross-site scripting, and it is the first thing a buyer's security review looks for in a frontend.