Most Frequent Even Element

Most Frequent Even Element

What is this problem about?

The Most Frequent Even Element problem gives you an integer array and asks you to return the most frequently occurring even number. If there's a tie, return the smallest such number. Return -1 if no even number exists. This Most Frequent Even Element coding problem is a clean frequency counting exercise with a simple tiebreaking rule.

Why is this asked in interviews?

Amazon, Google, and Bloomberg include this as a quick screening problem to test basic hash map usage and tiebreaking logic. It validates that candidates can implement frequency counting correctly and handle edge cases (no even elements, multiple elements tied for most frequent). The array, hash table, and counting interview pattern is directly applied.

Algorithmic pattern used

Hash map frequency count + linear scan. Iterate the array, counting frequencies of even numbers only (skip odd numbers). After building the frequency map, find the entry with the maximum frequency. On ties, return the smaller key.

Example explanation

Array: [0, 1, 2, 2, 4, 4, 1]. Even numbers: [0, 2, 2, 4, 4]. Frequencies: {0:1, 2:2, 4:2}.

• Max frequency = 2, tied by 2 and 4.
• Smaller of the two = 2.

Array: [1, 3, 5]: no even numbers → return -1.

Common mistakes candidates make

• Counting odd numbers instead of filtering to evens only.
• Not handling the tiebreaking (returning the first maximum found instead of the smallest).
• Returning 0 instead of -1 when no even elements exist.
• Using a sorted traversal when a simple min-tracking variable suffices.

Interview preparation tip

Frequency counting problems with tiebreaking rules are common easy-level interview questions. The pattern: build frequency map over filtered elements, find the maximum frequency, then find the minimum key with that frequency (or use min(key for key, freq in map.items() if freq == maxFreq)). This one-liner approach demonstrates clean Pythonic thinking. Practice similar problems with different tiebreaking conditions (e.g., largest, first occurrence, most recent) to handle all variants quickly.