Sorting Questions at Hashedin: What to Expect

Sorting questions appear in roughly 10% of Hashedin's technical interview problems. While this may seem like a small portion, their presence is significant. Hashedin, like many product-based companies, uses sorting problems to assess a candidate's grasp of fundamental algorithm efficiency and their ability to apply core computer science concepts to real-world data organization tasks. A strong performance here signals that you understand time/space complexity trade-offs and can choose the right tool for the job—skills critical for building scalable applications.

What to Expect — types of problems

You will rarely be asked to implement a basic sorting algorithm like Quicksort from scratch. Instead, Hashedin's problems typically use sorting as a key step in an optimal solution. Expect these categories:

1. Sorting as Pre-processing: The problem's core logic becomes trivial if the input array is sorted first. Examples include finding minimum absolute differences between elements, merging overlapping intervals, or grouping anagrams.
2. Custom Comparison Sorting: You'll need to sort objects or data pairs based on a non-standard rule. This tests your ability to define a comparator function to sort in a specific order (e.g., sort events by end time, or sort numbers by digit sum).
3. Hybrid Problems: These combine sorting with another core pattern, like the two-pointer technique, binary search, or greedy algorithms. A classic example is the "Two Sum" problem, which can be solved efficiently by sorting and then using two pointers.

The difficulty often lies in recognizing that sorting the data first unlocks the most efficient solution, which is typically O(n log n) time.

How to Prepare — study tips with one code example

Master the theory behind comparison-based sorts (Merge Sort, QuickSort) and their time/space complexities. Focus intensely on applying sorting to problems. For any array-related question, ask yourself: "Would sorting this input simplify the logic?"

Practice writing custom comparators in all three languages. This is a frequently tested skill. For example, a common problem is to sort an array to form the largest possible number by concatenating elements. This requires a custom comparator that compares a+b vs b+a as strings.

def largest_number(nums):
    # Convert to strings for custom comparison
    from functools import cmp_to_key
    def compare(a, b):
        # Compare concatenations
        if a + b > b + a:
            return -1  # a should come before b
        else:
            return 1   # b should come before a

    nums_str = list(map(str, nums))
    nums_str.sort(key=cmp_to_key(compare))

    # Handle edge case where result is multiple zeros
    result = ''.join(nums_str)
    return '0' if result[0] == '0' else result

Recommended Practice Order

Build your skills progressively:

1. Start with fundamental sorting algorithms (QuickSort, Merge Sort) to understand the O(n log n) baseline.
2. Solve easy LeetCode problems that use sorting as pre-processing (e.g., "Meeting Rooms", "Valid Anagram").
3. Practice custom comparator problems (like the "Largest Number" example above).
4. Tackle medium-level hybrid problems that combine sorting with two-pointers ("3Sum", "Merge Intervals") or greedy approaches ("Non-overlapping Intervals").
5. Finally, attempt Hashedin-specific or similar company problems to understand their style.

Practice Sorting at Hashedin