Heap / Priority Queuehard70 minSecurity Engineer

Audit Real-Time Top-K Prioritizer

Security Engineer signal: heap + top-k in a audit event compressor context. This is a ProdMatch-owned security engineer drill, framed as a May 2026 PolicyBazaar Compliance simulation, not a copied platform question.

Company context

PolicyBazaar · Compliance

Freshness

May 2026

Product surface

audit event compressor

ProdMatch interview simulation based on product-team patterns; not a claim of a real company question.

Question

Your Compliance team needs a live top-k view for events. Each update changes an item's score. Return the current top k item IDs after each update, ordered by score desc then ID asc.

Input

Initial scores, k, and update stream [id, delta].

Output

Top-k IDs after every update.

Constraints

1 <= items <= 200000
1 <= updates <= 200000
Scores can be negative.

Concepts

attack graphs
policy tries
anomaly detection
heap
top-k
streaming rank

scores: [5,1,3], k=2, update [1,+5] -> [1,0]

Approach

Try framing your own approach first. The 30 seconds you think before peeking is where learning happens.

Clean Solution

Reveal the approach first.

How well did you understand?

Your rating tunes when this problem shows up again.

Common Mistakes

Use a stable tie-breaker for equal scores.
Do not sort the full stream when k is small.

Next Similar Problems

Attack Real-Time Top-K Prioritizerhard Policy Real-Time Top-K Prioritizerhard Anomaly Real-Time Top-K Prioritizerhard