Case study: import failure investigation
Request
The import support team needs a first investigation target from a noisy local event log.
Data
Events contain kind, id, ok, and reason. Repeated ids are later versions of the same import attempt.
Deliverable
A ranked failure table and an inspect:reason:count recommendation, or monitor:0 when no current failures remain. Each step carries your prior analysis forward.
An internal import screen shows several error messages, but the raw log mixes page views with import attempts and can contain repeated records. The operations team wants to know which failure reason deserves investigation first. Counting every visible log line would overstate recurring attempts and include unrelated traffic.
Build an evidence table in five continuing steps. Select import events, keep the latest event for each attempt identifier, retain actual failures, count and rank the reasons, then return the checked investigation choice. A later successful event replaces an earlier failure for the same identifier. Ties use the reason name, so the recommendation is deterministic. This is a prioritization rule for fictional local logs; it doesn't prove that the most frequent reason caused every affected import.
type Incident={kind:string;id:string;ok:boolean;reason:string};
function solve(value:string):string {const events=JSON.parse(value) as Incident[];const parsed=events.filter(event=>event.kind==="import");const unique=parsed;const failures=unique;const rows=failures.map(event=>[event.reason,1] as [string,number]);return JSON.stringify(rows);}
A complete implementation for the first scenario; trace its input before editing.