Sorting Questions at Wix: What to Expect

Sorting questions appear in 7 out of 56 technical problems at Wix, making them a core component of their interview process. For a company that manages vast amounts of user data, website elements, and real-time configurations, efficient sorting is not academic—it’s operational. The ability to order data is fundamental to features like search result ranking, dashboard analytics, inventory management for e-commerce stores, and organizing user-generated content. At Wix, you’re not just implementing a sort; you’re demonstrating you can choose the right tool to keep a complex, data-heavy platform performant at scale.

What to Expect — types of problems

Wix’s sorting questions typically extend beyond asking you to implement a basic algorithm like Quicksort from scratch. Instead, they integrate sorting as a critical step within a larger, practical problem. You can expect two main types:

1. Direct Application Problems: These require you to sort data as the primary solution, often with a twist. Examples include merging sorted lists, finding the Kth largest element, or sorting based on a custom comparator (e.g., ordering events by time, products by price and rating).
2. Sorting as an Enabler: Here, sorting is a pre-processing step that transforms the problem, making the subsequent logic simple and efficient. Classic patterns include using sorting to solve problems like "Two Sum" (using a two-pointer approach on a sorted array), finding the minimum difference between elements, or identifying non-overlapping intervals.

The focus is on your ability to recognize when sorting is the optimal approach, justify its O(n log n) complexity trade-off, and implement it cleanly within a broader solution.

How to Prepare — study tips with one code example

Master the standard sorting libraries and how to customize them. In interviews, you should use the language's built-in sort (e.g., sorted() in Python, .sort() in JavaScript, Arrays.sort() in Java) unless explicitly asked to implement the algorithm itself. Your study should focus on:

• Complexity Analysis: Know the time (O(n log n) average) and space complexity of your language's default sort.
• Custom Comparators: Practice writing comparator functions or lambda expressions to sort objects by multiple attributes or in a non-default order.
• Two-Pointer Technique: This is frequently used on sorted arrays. Drill problems that use sorting to then apply a two-pointer or sliding window solution.

A key pattern is modifying data before sorting to solve a problem efficiently. Consider the "Largest Number" problem: given a list of non-negative integers, arrange them to form the largest possible number.

The trick is to sort the numbers as strings based on custom comparison: for two numbers x and y, we compare the concatenations x+y and y+x. If y+x is lexicographically greater than x+y, then y should come before x.

def largestNumber(nums):
    # Convert numbers to strings for custom comparison
    nums = list(map(str, nums))

    # Custom comparator: sort based on concatenated result
    def compare(x, y):
        if x + y > y + x:
            return -1  # x should come before y
        else:
            return 1   # y should come before x

    # Sort using the custom comparator
    nums.sort(key=functools.cmp_to_key(compare))

    # Handle edge case where largest number is "0"
    largest = ''.join(nums)
    return '0' if largest[0] == '0' else largest

Recommended Practice Order

1. Foundation: Solidify your understanding of built-in sort functions and how to write custom comparators in your chosen language.
2. Basic Patterns: Solve problems where sorting is the direct answer (e.g., Kth Largest Element, Merge Intervals).
3. Enabler Patterns: Practice problems where sorting is a pre-processing step (e.g., Two Sum II, 3Sum, Minimum Difference).
4. Wix-Specific: Finally, tackle the actual sorting problems tagged from Wix's interview question bank to familiarize yourself with their style and difficulty.

Practice Sorting at Wix