Heap / Priority Queuehard70 minSecurity Engineer

Secrets Real-Time Top-K Prioritizer

Security Engineer signal: heap + top-k in a secret exposure scanner context. This is a ProdMatch-owned security engineer drill, framed as a April 2026 Oracle AppSec simulation, not a copied platform question.

Company context

Oracle · AppSec

Freshness

April 2026

Product surface

secret exposure scanner

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

Question

Your AppSec team needs a live top-k view for findings. 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