Bird
Raised Fist0
DSA Javaprogramming~3 mins

Why Binary Search on Answer Technique in DSA Java?

Choose your learning style10 modes available
The Big Idea

What if you could find the perfect answer without trying every option?

The Scenario

Imagine you want to find the smallest size of a box that can hold all your items, but you only have a list of item sizes and no direct formula. You try different box sizes one by one, starting from the smallest, checking if all items fit.

The Problem

This trial-and-error method is slow and frustrating because you might test many sizes unnecessarily. It's easy to waste time checking sizes that are obviously too small or too big, and you might miss the optimal size.

The Solution

The Binary Search on Answer technique smartly guesses the answer by checking the middle size between a range. If the middle size works, it tries smaller sizes; if not, it tries bigger sizes. This way, it quickly narrows down to the best answer without testing every possibility.

Before vs After
✗ Before
int size = 1;
while (!canFit(items, size)) {
    size++;
}
return size;
✓ After
int low = 1, high = maxSize;
while (low < high) {
    int mid = low + (high - low) / 2;
    if (canFit(items, mid)) high = mid;
    else low = mid + 1;
}
return low;
What It Enables

This technique enables you to solve complex optimization problems efficiently by turning them into a search over possible answers.

Real Life Example

For example, when deciding the minimum time needed to complete tasks with limited workers, you can use this technique to quickly find the smallest time that works instead of guessing blindly.

Key Takeaways

Manual guessing is slow and error-prone.

Binary Search on Answer narrows down the solution quickly.

It turns optimization problems into efficient searches.

Practice

(1/5)
1. What is the main idea behind the Binary Search on Answer technique?
easy
A. We guess an answer and check if it satisfies the problem constraints, then adjust the guess.
B. We sort the array and then apply binary search to find an element.
C. We use binary search to find the maximum element in an unsorted array.
D. We divide the array into two halves and solve each half separately.

Solution

  1. Step 1: Understand the technique's approach

    Binary Search on Answer guesses a possible answer and checks if it meets the problem's conditions.
  2. Step 2: Adjust guess based on check

    If the guess is valid, we try smaller or larger guesses accordingly to find the best answer.
  3. Final Answer:

    We guess an answer and check if it satisfies the problem constraints, then adjust the guess. -> Option A
  4. Quick Check:

    Guess and check approach = We guess an answer and check if it satisfies the problem constraints, then adjust the guess. [OK]
Hint: Guess answer, check condition, adjust guess accordingly [OK]
Common Mistakes:
  • Confusing with normal binary search on sorted arrays
  • Thinking it only finds elements, not answers
  • Assuming it divides data instead of answer range
2. Which of the following is the correct way to initialize the search range for binary search on answer when finding minimum maximum load among workers?
easy
A. low = 0; high = maximum single load
B. low = minimum load; high = maximum load
C. low = 0; high = sum of all loads
D. low = average load; high = sum of all loads

Solution

  1. Step 1: Define search range for answer

    Minimum maximum load can be between 0 and sum of all loads because no worker can have load more than total.
  2. Step 2: Set low and high accordingly

    Set low = 0 and high = sum of all loads to cover all possible answers.
  3. Final Answer:

    low = 0; high = sum of all loads -> Option C
  4. Quick Check:

    Search range covers all loads = low = 0; high = sum of all loads [OK]
Hint: Set low to minimum possible, high to maximum possible answer [OK]
Common Mistakes:
  • Setting low to minimum load instead of 0
  • Setting high to max single load instead of sum
  • Using average load as boundary
3. Consider the following Java code snippet using binary search on answer to find minimum maximum pages assigned to students:
int[] pages = {10, 20, 30, 40};
int low = 40, high = 100;
while (low < high) {
  int mid = (low + high) / 2;
  if (canAllocate(pages, mid, 2)) {
    high = mid;
  } else {
    low = mid + 1;
  }
}
System.out.println(low);

// canAllocate checks if pages can be divided among 2 students with max pages mid
What will be the output?
medium
A. 70
B. 60
C. 90
D. 100

Solution

  1. Step 1: Understand the problem and initial range

    Pages array is {10,20,30,40}, low=40 (max single), high=100 (sum). We want minimum max pages for 2 students.
  2. Step 2: Trace binary search iterations

    Mid = 70: canAllocate true (10+20+30=60 <=70 for 1st student, 40 for 2nd). So high=70.
    Mid = 55: canAllocate false (10+20+30=60 >55). So low=56.
    Mid = 63: canAllocate true (10+20+30=60 <=63, 40 for 2nd). high=63.
    Mid = 59: canAllocate false (60 >59). low=60.
    Mid = 61: canAllocate true. high=61.
    Mid = 60: canAllocate true. high=60.
    Mid = 60 again, low=60, high=60 ends loop.
  3. Final Answer:

    60 -> Option B
  4. Quick Check:

    Minimum max pages = 60 [OK]
Hint: Check mid feasibility, adjust low/high until low meets high [OK]
Common Mistakes:
  • Not updating low/high correctly after canAllocate
  • Misunderstanding canAllocate logic
  • Incorrect mid calculation or loop condition
4. The following code attempts to find the minimum largest sum of subarrays using binary search on answer. Identify the bug:
int[] nums = {7, 2, 5, 10, 8};
int m = 2;
int low = 0, high = 32;
while (low <= high) {
  int mid = (low + high) / 2;
  if (canSplit(nums, mid, m)) {
    high = mid - 1;
  } else {
    low = mid + 1;
  }
}
System.out.println(low);

// canSplit checks if nums can be split into m subarrays with max sum <= mid
medium
A. The initial low should be max element, not 0
B. The loop condition should be low < high, not low <= high
C. The mid calculation should use (low + high + 1) / 2
D. The canSplit function should return false when sum equals mid

Solution

  1. Step 1: Check initial low value

    Low is set to 0, but minimum largest sum can't be less than max element (10).
  2. Step 2: Correct low initialization

    Set low = max element (10) to ensure valid search range and avoid infinite loop or wrong answer.
  3. Final Answer:

    The initial low should be max element, not 0 -> Option A
  4. Quick Check:

    Low must start at max element [OK]
Hint: Start low at max element to avoid invalid guesses [OK]
Common Mistakes:
  • Starting low at 0 causing invalid mid values
  • Using wrong loop condition causing infinite loop
  • Misunderstanding canSplit return values
5. You want to find the minimum time required to complete all jobs by k workers, where each job takes a certain time. Using binary search on answer, which approach correctly finds the answer? int[] jobs = {3, 6, 7, 11}; int k = 2; Options:
hard
A. Sort jobs ascending; assign jobs alternately to workers; return max load.
B. Set low = 0, high = max job time; assign jobs greedily without checking mid; return high.
C. Set low = sum of all jobs, high = max job time; use binary search to find minimum sum.
D. Set low = max job time, high = sum of all jobs; check if jobs can be assigned within mid time using k workers; adjust low/high accordingly.

Solution

  1. Step 1: Define search boundaries

    Low should be max job time (11), high sum of all jobs (3+6+7+11=27) to cover all possible times.
  2. Step 2: Use binary search with feasibility check

    Check if jobs can be assigned to k=2 workers within mid time. Adjust low/high based on feasibility.
  3. Final Answer:

    Set low = max job time, high = sum of all jobs; check if jobs can be assigned within mid time using k workers; adjust low/high accordingly. -> Option D
  4. Quick Check:

    Binary search on answer with feasibility check = Set low = max job time, high = sum of all jobs; check if jobs can be assigned within mid time using k workers; adjust low/high accordingly. [OK]
Hint: Set low=max job, high=sum; check feasibility; adjust range [OK]
Common Mistakes:
  • Setting wrong low/high boundaries
  • Not checking feasibility properly
  • Assigning jobs without binary search
Recommended

Ready to prove it?

Pass the test and this pattern moves unknown strong while earning +1 Grip toward your certificate.

10 questions~5 mineasy hard