Binary Search Questions at DoorDash: What to Expect

DoorDash’s technical interviews frequently include binary search because it’s a fundamental, efficient algorithm for searching in sorted data—a common requirement in logistics, delivery time estimation, and range-based queries. With 9 binary search questions in their question bank, it’s clear they value candidates who can implement optimized search solutions under constraints. Mastering binary search demonstrates you can think about optimization and edge cases, which is critical for scaling real-world delivery systems.

What to Expect — Types of Problems

DoorDash’s binary search problems often extend beyond basic array search. Expect variations that model real-world scenarios:

• Search in rotated or sorted arrays: Finding a target in a sorted array that’s been rotated, or finding a minimum/maximum in such an array.
• Aggressive problems: Finding the minimum or maximum of something (like time, distance, or capacity) that satisfies a condition. For example, “minimum speed to complete deliveries within H hours.”
• Range-based or boundary search: Problems where you search for a boundary, like the first bad version or the first occurrence of a target.
• Search in 2D spaces: Though less common, some problems may involve a matrix with sorted rows or columns.

These questions test your ability to adapt the core binary search pattern to constrained optimization and search spaces that aren’t strictly arrays.

How to Prepare — Study Tips with One Code Example

Focus on understanding the invariant in binary search: maintaining a range [left, right] where the answer lies, and narrowing it down. Always clarify:

• Is the array sorted or can it be sorted?
• What are you searching for? (a value, a minimum/maximum, a boundary)
• What condition determines if you go left or right?

Practice writing bug-free implementations. A common template uses while left < right and mid = left + (right - left) // 2 to avoid overflow. Here’s a key pattern for finding the first occurrence of a target (a boundary search):

def first_occurrence(arr, target):
    left, right = 0, len(arr) - 1
    while left < right:
        mid = left + (right - left) // 2
        if arr[mid] >= target:
            right = mid
        else:
            left = mid + 1
    return left if arr[left] == target else -1

Recommended Practice Order

1. Classic binary search: Implement searching in a sorted array.
2. Boundary searches: Find first/last occurrence, first bad version.
3. Rotated arrays: Search in rotated sorted array, find minimum in rotated array.
4. Aggressive problems: Koko eating bananas, capacity to ship packages.
5. Advanced adaptations: Search in a 2D matrix, median of two sorted arrays.

This progression builds from the basic pattern to its nuanced applications, solidifying your ability to recognize and solve DoorDash’s variations.

Practice Binary Search at DoorDash