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Dynamic Programming / 1Dmedium45 minBackend Engineer

Cache Ranking Budget Optimizer

Backend Engineer signal: dynamic programming + knapsack in a multi-region cache context. This is a ProdMatch-owned backend engineer drill, framed as a April 2026 Salesforce Edge Platform simulation, not a copied platform question.

Company context

Salesforce · Edge Platform

Freshness

April 2026

Product surface

multi-region cache

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

Question

Your Edge Platform roadmap has candidate improvements for multi-region cache. Each improvement has cost, lift and risk. Maximize lift under budget while keeping total risk below a threshold.

Input

  • Items [cost, lift, risk], budget and maxRisk.

Output

  • Maximum lift achievable.

Constraints

  • 1 <= items.length <= 500
  • Budget <= 10000
  • maxRisk <= 10000

Concepts

  • idempotency
  • queues
  • rate limiting
  • dynamic programming
  • knapsack
  • ranking trade-off

items [[2,5,1],[4,9,4]], budget=4, risk=4 -> 9

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

  • Unclear state definition usually causes off-by-one bugs.
  • Do not overwrite a state before all consumers have used it.

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