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Dynamic Programming / 1Dhard70 minFull Stack Developer

Billing Ranking Budget Optimizer

Full Stack Developer signal: dynamic programming + knapsack in a subscription billing context. This is a ProdMatch-owned full stack engineer drill, framed as a April 2026 Atlassian Revenue Platform simulation, not a copied platform question.

Company context

Atlassian · Revenue Platform

Freshness

April 2026

Product surface

subscription billing

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

Question

Your Revenue Platform roadmap has candidate improvements for subscription billing. 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

  • workflow graphs
  • API pagination
  • cache invalidation
  • 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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