Array Questions at Samsung: What to Expect

Array fundamentals are non-negotiable for Samsung technical interviews. With 43 out of their 69 total tagged problems focusing on arrays, this single data structure forms the core of their coding assessment. Samsung's engineering work, from embedded systems to large-scale applications, frequently involves processing sequences of sensor data, image pixels, or configuration parameters. Your ability to manipulate arrays efficiently demonstrates the low-level control and performance-oriented thinking required for their hardware-adjacent software roles. Expect the interview to test not just if you can solve a problem, but if you can do so with optimal memory usage and execution speed.

What to Expect — Types of Problems

Samsung's array problems tend to be practical and often involve multi-step logic rather than abstract academic puzzles. You can broadly categorize them into three types:

1. In-Place Manipulation: Tasks requiring you to modify the array without allocating significant extra space. This includes operations like moving zeros, removing duplicates, rotating arrays, and applying transformations directly on the given data structure.
2. Subarray & Range Analysis: Problems where you must find, count, or analyze contiguous segments of the array. Common themes include finding subarrays with a given sum, maximum product, or specific properties. These test your ability to manage sliding windows or prefix sums.
3. Simulation & Index Mapping: Many questions are essentially step-by-step simulations. You'll be given a set of rules (e.g., for merging intervals, jumping through indices, or arranging elements based on a pattern) and must implement the precise procedure, often requiring careful index management to avoid off-by-one errors.

How to Prepare — Study Tips with One Code Example

Focus on mastering a few core patterns that apply across dozens of problems. The Two-Pointer Technique is arguably the most critical for Samsung's array questions. It allows you to solve in-place manipulation and subarray problems in linear time with constant extra space. Always analyze the problem to see if ordering or pairing elements is involved.

Consider the classic problem: Move all zeros in an array to the end while maintaining the relative order of non-zero elements. A brute-force approach might use extra space. The optimal two-pointer solution does it in-place.

def moveZeroes(nums):
    # `last_non_zero` points to the position for the next non-zero element
    last_non_zero = 0
    for current in range(len(nums)):
        if nums[current] != 0:
            nums[last_non_zero], nums[current] = nums[current], nums[last_non_zero]
            last_non_zero += 1
    # No explicit return needed; modifying in-place

The pattern is simple: one pointer (current) iterates through the array, while the other (lastNonZero) marks the boundary for non-zero elements. When you find a non-zero element, you swap it into place and advance the boundary. This logic reappears in problems like removing duplicates, partitioning arrays, and segregating elements.

Recommended Practice Order

Build competence progressively. Start with foundational in-place operations (move zeros, remove duplicates, rotate array). Next, tackle subarray problems using sliding window and prefix sum techniques. Finally, practice simulation-heavy problems that require precise index tracking and multi-pass logic. For each problem, first ensure a correct brute-force solution, then optimize for the constraints typical at Samsung—often large input sizes requiring O(n) time and O(1) extra space.

Practice Array at Samsung