Lazy Inorder Traversal Iterator for a Binary Tree
Question Details
Problem
Implement an inorder traversal iterator InorderIterator for a binary tree that returns node values in
Left → Node → Right order lazily (you must not store all nodes in advance).
Full Details
Problem
Implement an inorder traversal iterator InorderIterator for a binary tree that returns node values in
Left → Node → Right order lazily (you must not store all nodes in advance).
Implement:
- __init__(root): initialize with the root.
- hasNext() -> bool:
return true if there is a next node.
- next() -> int:
return the next node value and advance the iterator.
Requirements
- Lazy traversal: do not precompute/store the full traversal.
- Extra space should be
O(h)wherehis tree height. - Amortized time for
next()should beO(1).
Input/Output (one possible judge format)
Input: a binary tree in level-order with null for missing nodes, plus a sequence of operations init, hasNext, next.
Output: print results for each hasNext/next.
If your platform does not support interactive class design, implement an equivalent driver that simulates the operations.
Constraints
- 0 <= N <= 2 * 10^5
- Node values are 32-bit integers
Sample Input
Tree: [2,1,3]
Ops: init, hasNext, next, hasNext, next, hasNext, next, hasNext
Sample Output
true
1
true
2
true
3
false
Test Cases
Case 1
Input:
Tree: [2,1,3]
Ops: init, hasNext, next, hasNext, next, hasNext, next, hasNext
Output:
true
1
true
2
true
3
false
Case 2
Input:
Tree: []
Ops: init, hasNext
Output:
false
Case 3
Input:
Tree: [1,null,2,null,3]
Ops: init, next, next, next, hasNext
Output:
1
2
3
false
Case 4
Input:
Tree: [3,2,null,1]
Ops: init, next, next, next
Output:
1
2
3
Case 5
Input:
Tree: [1,1,1,1,1]
Ops: init, next, next, next, next, next, hasNext
Output:
1
1
1
1
1
false
About This Question
This is a reported interview question from a apple interview for a swe role during the coding round.
It covers the following topics: Binary Tree, Oop, Trees .
Topics
About Apple Interview Reports
This question was reported by a candidate who interviewed at Apple. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.
Use this question as one calibration data point, not a memorization target. Companies typically rotate their question pools every 2-4 months; the exact wording of a 2024 question may differ from what you encounter today. The underlying pattern, difficulty level, and follow-up depth at Apple are the higher-signal extractions to take from this report.
For broader preparation context, the Apple interview process typically includes a recruiter screen, one or two technical phone screens, and a 4-5 round on-site loop covering coding, system design (at L4+ levels), and behavioral. Reports tagged on LeakCode show the round-by-round distribution and typical difficulty calibration. To browse questions filtered by round type and seniority, use the company hub linked above.
How To Practice This Type of Question
Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.
Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in Apple reports consistently are the ones worth investing in; one-off niche problems are not.
During Your Apple Round
Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.
The single most predictive failure mode in Apple reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.