Algorithmsmedium

Boyer–Moore majority vote: what does it solve and what’s the core idea?

Answer

It finds the element that appears more than n/2 times (if it exists). The idea is to cancel pairs of different elements; the remaining candidate is the majority. It runs in O(n) time and O(1) space.

function majority(nums: number[]): number {
  let cand = 0;
  let count = 0;
  for (const x of nums) {
    if (count === 0) cand = x;
    count += x === cand ? 1 : -1;
  }
  return cand;
}

Advanced answer

Deep dive

Expanding on the short answer — what usually matters in practice:

Context (tags): majority-vote, array, linear-time, constant-space
Complexity: compare typical operations (average vs worst-case).
Invariants: what must always hold for correctness.
When the choice is wrong: production symptoms (latency, GC, cache misses).
Explain the "why", not just the "what" (intuition + consequences).
Trade-offs: what you gain/lose (time, memory, complexity, risk).
Edge cases: empty inputs, large inputs, invalid inputs, concurrency.

Examples

Here’s an additional example (building on the short answer):

function majority(nums: number[]): number {
  let cand = 0;
  let count = 0;
  for (const x of nums) {
    if (count === 0) cand = x;
    count += x === cand ? 1 : -1;
  }
  return cand;
}

Common pitfalls

Too generic: no concrete trade-offs or examples.
Mixing average-case and worst-case (e.g., complexity).
Ignoring constraints: memory, concurrency, network/disk costs.

Interview follow-ups

When would you choose an alternative and why?
What production issues show up and how do you diagnose them?