Is Binary Tree Longest Consecutive Sequence II easy or hard?

Binary Tree Longest Consecutive Sequence II is generally rated Medium difficulty. The traversal itself is straightforward, but combining increasing and decreasing sequences at each node requires careful reasoning. Recognizing the postorder DFS pattern is the main challenge.

Binary Tree Longest Consecutive Sequence II Python/Java solution

Most implementations define a DFS helper that returns a pair of integers representing increasing and decreasing sequence lengths. During traversal, the algorithm updates these values based on child node comparisons and tracks a global maximum. The same logic works consistently across Python, Java, C++, and Go with O(n) time complexity.

How to solve Binary Tree Longest Consecutive Sequence II in O(n)?

Perform a postorder DFS and return two values from each node: the longest increasing path and the longest decreasing path starting there. Compare the node's value with its children to extend either sequence. Combine both lengths at the current node using inc + dec - 1 to update the global maximum. This single traversal ensures O(n) runtime.

What is the best approach for Binary Tree Longest Consecutive Sequence II?

The best approach uses a postorder depth-first search that tracks two values for every node: the longest increasing sequence and the longest decreasing sequence starting from that node. By combining results from the left and right children, the algorithm can form paths that go child → parent → child. This processes each node once, giving O(n) time complexity and O(h) recursion space.

Is Binary Tree Longest Consecutive Sequence II asked at Google/Amazon/Meta?

Tree DFS problems that combine results from child nodes frequently appear in interviews at companies like Google, Amazon, and Meta. Variants of longest path or consecutive sequence problems test recursion, tree traversal, and dynamic programming on trees. Understanding how to merge increasing and decreasing paths is the key interview skill here.

What data structure is used in Binary Tree Longest Consecutive Sequence II?

The core data structure is a binary tree. The solution relies on depth-first search with recursion and uses simple integer tracking for increasing and decreasing path lengths. No additional complex structures are required beyond the recursion stack.

What is the time complexity of Binary Tree Longest Consecutive Sequence II?

The optimal DFS solution runs in O(n) time because every node in the binary tree is visited exactly once. During each visit, constant work is done to compare node values with its children and update increasing and decreasing path lengths. Space complexity is O(h), where h is the tree height due to the recursion stack.

Description Solution Video 8:54

549. Binary Tree Longest Consecutive Sequence II

Medium50.1% acceptance3 companiesPremium elsewhere, free here

Given the root of a binary tree, return the length of the longest consecutive path in the tree.

A consecutive path is a path where the values of the consecutive nodes in the path differ by one. This path can be either increasing or decreasing.

For example, [1,2,3,4] and [4,3,2,1] are both considered valid, but the path [1,2,4,3] is not valid.

On the other hand, the path can be in the child-Parent-child order, where not necessarily be parent-child order.

Example 1:

Input: root = [1,2,3]
Output: 2
Explanation: The longest consecutive path is [1, 2] or [2, 1].

Example 2:

Input: root = [2,1,3]
Output: 3
Explanation: The longest consecutive path is [1, 2, 3] or [3, 2, 1].

Constraints:

The number of nodes in the tree is in the range [1, 3 * 10⁴].
-3 * 10⁴ <= Node.val <= 3 * 10⁴

Asked at 3 companies

Topics

8:54

Still stuck?Read the written solution, or watch a walkthrough.

Open solution

549. Binary Tree Longest Consecutive Sequence II

Asked at 3 companies

Topics

Similar problems