Binary Search on Answer | DSA Interview Patterns - Study Chapter | QuizMaker

Convert minimize-the-maximum and maximize-the-minimum problems into monotonic feasibility checks.

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Course

DSA Interview Patterns Roadmap

Topic

Binary Search

Learning Outcome

Convert minimize-the-maximum and maximize-the-minimum problems into monotonic feasibility checks.

Pattern Recognition

ItemDetail
Core signalThe answer is a number and if x works, then every larger or smaller value also works.
Use whenYou can write a deterministic check(candidate) with a true/false boundary.
Avoid whenThe required invariant is not monotonic or the input constraints point to a simpler direct scan.

Intuition

You are not searching the array; you are searching the answer space and using feasibility to discard half.

Exact Practice Question Names

Interview Approach

  1. Choose low/high bounds that definitely contain the answer.
  2. Write a monotonic helper.
  3. For minimum feasible answer, move high to mid when feasible.
  4. For maximum feasible answer, move low upward when feasible.
  5. Return the boundary value.

Pseudocode

low = smallest_possible
high = largest_possible
while low < high:
  mid = low + (high - low) // 2
  if feasible(mid):
    high = mid
  else:
    low = mid + 1
return low

Sample Dry Run

For shipping capacity, capacity 15 may need too many days, capacity 18 may fit, so the first feasible capacity lies between them and the search keeps tightening.

Edge Cases

Common Mistakes

Complexity

ItemDetail
Expected timeO(n log range) for integer answers; O(n log precision) for floating answers.
Expected spaceO(1) unless the helper builds extra state.

Java, C++ and Python Notes

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