Array Questions at Accenture: What to Expect

Array questions make up over half of Accenture's technical interview problem set, with 73 out of 144 total questions. This heavy emphasis isn't arbitrary. Arrays are the foundational data structure for representing sequential data, a common pattern in real-world business data processing, ETL pipelines, and system operations that Accenture consultants and developers regularly handle. Mastering array manipulation demonstrates core competency in logical thinking, efficient data handling, and clean code—skills directly applicable to the client projects you'd work on. If you can't navigate array problems confidently, you're at a significant disadvantage.

What to Expect — Types of Problems

Accenture's array questions tend to focus on practical application over obscure algorithmic tricks. You can expect problems in these key categories:

1. Basic Traversal and Manipulation: Tasks like searching, inserting, deleting, reversing, or rotating elements. These test your fundamental loop control and index management.
2. Sorting and Searching: Implementing or leveraging sorts (like quicksort or mergesort) and search algorithms (binary search on sorted arrays). Questions often involve finding specific elements, pairs, or ranges.
3. Subarray and Prefix Sum Problems: Finding contiguous subarrays that meet a condition (e.g., maximum sum, target sum). These are common and test your ability to optimize from a brute-force O(n²) approach to an O(n) solution using techniques like the sliding window or prefix sums.
4. Two-Pointer Techniques: Used for problems involving sorted arrays, such as removing duplicates, finding pairs with a target sum, or merging two sorted arrays. This pattern is highly efficient and frequently tested.
5. In-Place Operations: Modifying the array without using significant extra space, such as moving zeroes to the end or segregating even/odd numbers. This demonstrates memory-aware programming.

How to Prepare — Study Tips with One Code Example

Focus on pattern recognition, not memorization. Understand the underlying technique for each problem type. Practice writing clean, readable code with clear variable names—communication is key. Always discuss time and space complexity. For each problem, start with the brute-force solution, then optimize.

A critical pattern is the Two-Pointer Technique for finding a pair in a sorted array that sums to a target. Instead of a nested loop (O(n²)), you use a pointer at the start and end, moving them inward based on the sum comparison (O(n)).

def two_sum_sorted(nums, target):
    left, right = 0, len(nums) - 1
    while left < right:
        current_sum = nums[left] + nums[right]
        if current_sum == target:
            return [left, right]
        elif current_sum < target:
            left += 1
        else:
            right -= 1
    return [-1, -1]  # No pair found

Recommended Practice Order

Build your skills progressively. Start with basic traversal and in-place operations to solidify fundamentals. Move on to sorting and searching algorithms next. Then, tackle two-pointer problems, as they are a cornerstone for efficiency. After that, focus on the more complex subarray and prefix sum problems. Finally, mix all categories in timed mock interviews to simulate the actual test environment.

Practice Array at Accenture