Linked List in Binary Tree
A medium-tier problem at 52% community acceptance, tagged with Linked List, Tree, Depth-First Search. Reported in interviews at SoundHound and 0 others.
Linked List in Binary Tree is a medium-difficulty problem that combines two separate data structures into one pattern-matching challenge. You're given a linked list and a binary tree, and you need to check if the linked list exists as a downward path in the tree. Half the candidates who see this don't solve it cleanly, so it's worth understanding the trick now rather than blanking on it during an assessment. SoundHound has asked it. The problem tests whether you can traverse both structures in tandem, which is less common than isolated tree or list problems. If you hit this live and haven't drilled the exact pattern, StealthCoder surfaces a working solution in seconds, invisible to your proctor.
Companies that ask "Linked List in Binary Tree"
Linked List in Binary Tree 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. Built by an engineer at a top-10 tech company who can solve these problems cold but didn't want to trust himself in a 90-minute screen share.
Get StealthCoderThe pattern is a DFS search where you're trying to match the entire linked list as a continuous downward path in the tree. Most candidates initially try to solve it recursively by comparing one node at a time, but the real trick is handling two recursive calls: one to advance down the linked list and one to explore different starting points in the tree. The failure case is not matching early enough, if you advance too far in the linked list and hit a leaf in the tree with no remaining list, you backtrack and try the next tree node as a fresh starting point. Common pitfall: confusing this with 'find a subtree that matches' or trying to match sideways or upward in the tree. The topics are Linked List, Tree, Depth-First Search, and Binary Tree, and you need to combine DFS discipline with list pointer arithmetic. StealthCoder hedges this because the dual-recursion structure isn't intuitive and wastes time under interview pressure.
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Linked List in Binary Tree 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. Built by an engineer at a top-10 tech company who can solve these problems cold but didn't want to trust himself in a 90-minute screen share. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Linked List in Binary Tree interview FAQ
What's the core trick if the linked list doesn't match starting from a specific tree node?+
You backtrack and try matching from the next tree node as a fresh starting point. If the list head doesn't match a tree node, recurse on the tree's left and right children separately, looking for any node that could start a valid match.
Why is this harder than a straightforward tree traversal?+
You're managing two separate recursion streams: one iterating the linked list and one exploring the binary tree. You can't just do a simple DFS; you need to decide at each tree node whether to advance the list pointer or abandon the match and search elsewhere.
Is this still asked at companies like SoundHound?+
Yes, SoundHound has reported asking it. It's a medium-difficulty problem, so it sits in the sweet spot for filtering candidates who understand both data structures but haven't memorized the pattern.
What's the acceptance rate and is that a red flag?+
About 52% acceptance rate, which is lower than average mediums. That means roughly half the people who attempt it fail, usually because they don't structure the dual recursion correctly or they miss the backtracking logic.
How does this relate to Depth-First Search specifically?+
DFS is your main tool. You use DFS on the binary tree to explore every possible starting point, and for each node, you recursively check if the linked list matches going downward. Without solid DFS fundamentals, the recursion gets tangled fast.
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