Find the Prefix Common Array of Two Arrays
A medium-tier problem at 87% community acceptance, tagged with Array, Hash Table, Bit Manipulation. Reported in interviews at Yandex and 0 others.
You're given two permutation arrays and need to build a prefix common array where each position counts how many elements appear in both prefixes up to that index. It's a medium-difficulty problem with a high acceptance rate (87%), which tells you the solution isn't hidden in obscure theory but rather in clean execution. Yandex has asked this. The trap is overthinking the data structure: most candidates default to a hash table when a simpler approach exists. If this hits your live assessment and you freeze on optimization, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
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Find the Prefix Common Array of Two Arrays is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Made by a working Amazon engineer who got tired of watching qualified friends bomb OAs they'd solve cold in an IDE.
Get StealthCoderThe core insight is that you don't need to store full arrays and compare them at each step. Instead, track which elements you've seen in each array as you iterate through both in parallel. For each position, count how many elements have appeared in both arrays by that point. A hash table or set works fine for the basic version, but the cleanest approach uses bit manipulation: since the arrays are permutations of 1 to n, you can mark bits as you encounter elements and use XOR or AND to count overlaps. The common pitfall is recalculating the entire common count from scratch at each index instead of maintaining a running tally. Most candidates waste time on nested loops when a single pass with tracking suffices. StealthCoder is your hedge if the bit-manipulation optimization doesn't click in the moment.
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Find the Prefix Common Array of Two Arrays recycles across companies for a reason. It's medium-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Made by a working Amazon engineer who got tired of watching qualified friends bomb OAs they'd solve cold in an IDE. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Find the Prefix Common Array of Two Arrays interview FAQ
Is this really medium difficulty?+
The acceptance rate is 87%, which is high for a medium problem. It's medium because the naive solution is straightforward, but optimization requires knowing when to use bit manipulation instead of hash tables. The pattern recognition is what separates confident solves from slower ones.
What's the trick to avoiding a nested loop?+
Don't recount from scratch at each index. Maintain a set or bit mask of elements you've seen so far in array A and array B separately. As you iterate, track how many elements appear in both. Update this count incrementally, not by rescanning.
When does bit manipulation beat a hash table here?+
Since the arrays are permutations of 1 to n, you can use a single integer as a bitmask instead of allocating a set. Bit operations are faster and use constant space. It's not mandatory for passing, but it's the move if you're optimizing for time and space.
What if I use two hash sets?+
That works fine and is the standard O(n) time, O(n) space solution. Iterate both arrays once, track seen elements in each, and count overlaps at each position. It's clear, correct, and what most candidates ship. Not wrong at all.
How does this relate to the topics listed?+
Array is the input format. Hash Table is the reliable brute-force approach. Bit Manipulation is the flex optimization if you know permutations let you use a bitmask instead of sets. You only need Hash Table to pass; Bit Manipulation is the next level.
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