Evaluate Boolean Binary Tree
Time O(n) · Space O(h) · Official statement on LeetCode
Solutions
// Time: O(n)
// Space: O(h)
// dfs with stack
class Solution {
public:
bool evaluateTree(TreeNode* root) {
static unordered_map<int, function<int(int, int)>> OP = {
{2, [](int x, int y) { return x | y; }},
{3, [](int x, int y) { return x & y; }},
};
const auto& iter_dfs = [&]() {
using RET = int;
RET ret;
vector<tuple<int, TreeNode *, shared_ptr<RET>, shared_ptr<RET>, RET *>> stk;
stk.emplace_back(1, root, nullptr, nullptr, &ret);
while (!empty(stk)) {
auto [step, node, ret1, ret2, ret] = stk.back(); stk.pop_back();
if (step == 1) {
if (node->left == node->right) {
(*ret) = node->val;
continue;
}
auto ret1 = make_shared<RET>(), ret2 = make_shared<RET>();
stk.emplace_back(2, node, ret1, ret2, ret);
stk.emplace_back(1, node->right, nullptr, nullptr, ret2.get());
stk.emplace_back(1, node->left, nullptr, nullptr, ret1.get());
} else if (step == 2) {
*ret = OP[node->val](*ret1, *ret2);
}
}
return ret;
};
return iter_dfs();
}
};
// Time: O(n)
// Space: O(h)
// dfs with recursion
class Solution2 {
public:
bool evaluateTree(TreeNode* root) {
static unordered_map<int, function<int(int, int)>> OP = {
{2, [](int x, int y) { return x | y; }},
{3, [](int x, int y) { return x & y; }},
};
function<int (TreeNode*)> dfs = [&](TreeNode *node) {
if (node->left == node->right) {
return node->val;
}
return OP[node->val](dfs(node->left), dfs(node->right));
};
return dfs(root);
}
};
Beginner Explanation
What is Evaluate Boolean Binary Tree?
Evaluate Boolean Binary Tree (LeetCode #2331) is a Easy problem that primarily trains depth first search.
How to think about it
- Restate the goal in your own words before coding.
- Work a tiny example by hand so the invariant becomes obvious.
- Identify the pattern — this problem aligns with dfs backtracking.
- Only then translate the idea into code.
Why this problem matters
It builds core muscle memory you will reuse on harder variants. Official solution notes mention: DFS.
AlgoForge explanations are original teaching notes. Always open the official problem statement on LeetCode for constraints and examples.
Interview Walkthrough
Interview approach for Evaluate Boolean Binary Tree
Opening (30–60 seconds)
- Clarify inputs/outputs and edge cases (empty input, single element, duplicates, overflow).
- State a brute force so the interviewer knows you can solve it naively.
- Propose the optimal direction tied to dfs backtracking.
Core solution narrative
- Define the state you track (pointers, DP cell, set membership, stack top, etc.).
- Explain the transition when you process the next element.
- Call out time (O(n)) and space (O(h)) before coding.
- Code cleanly; narrate variable names.
What interviewers listen for
- Correctness on edge cases
- Complexity honesty
- Ability to discuss trade-offs (e.g., hash map space vs. sort + two pointers)
Follow-up questions they may ask
- Can you solve it with less memory?
- What if the input stream is infinite / doesn't fit in RAM?
- How would tests look for adversarial inputs?
Optimized Approach
Optimized solution notes
The reference solutions on AlgoForge target O(n) time and O(h) space.
Pattern focus: dfs backtracking
Use the pattern as a checklist:
- dfs backtracking — confirm the invariant holds after each step
Multiple methods appear in the source solutions — compare them and explain when each is preferable.
Implementation tips
- Prefer readable names over micro-optimizations in interviews.
- Extract helpers only when they clarify (e.g., expand-around-center, DFS visit).
- After AC-level logic, re-scan for off-by-one and null checks.
Complexity Analysis
Complexity
| Measure | Bound |
|---|---|
| Time | O(n) |
| Space | O(h) |
How to justify this in an interview
- Time: count loops, map/set operations, and recursive branching; state average vs worst case if relevant.
- Space: include hash maps, recursion stack, and output allocation when the problem asks for it.
If your implementation differs from the reference, re-derive big-O from your code — never memorize a complexity you cannot defend.
Common Mistakes
Common mistakes on Evaluate Boolean Binary Tree
- Skipping edge cases — empty collections, single-element inputs, max constraints.
- Wrong invariant for dfs backtracking — updating state too early or too late.
- Mutating input unexpectedly when the problem forbids it.
- Off-by-one in windows, ranges, or binary search bounds.
- Ignoring overflow / precision for integer arithmetic problems.
- Overengineering — jumping to an advanced structure when a simpler approach works.
Alternative Approaches
Alternatives
The source file includes more than one method. Compare:
- Primary optimized path — best complexity for typical interviews.
- Secondary approach — often brute force, sorting-based, or space-optimized variant.
Practice articulating when you would pick each (constraints, readability, follow-ups).
Edge Cases
Edge cases checklist
- Minimum input size
- Maximum input size / time limits
- Duplicates and already-sorted input
- Negative numbers / zeros (if applicable)
- Disconnected structures (graphs/trees)
- Single path vs branching recursion depth
Pattern Recognition
Spotting this pattern
Signal phrases that point to dfs backtracking:
- Sorted input or ability to sort without changing the answer class
- Need for contiguous subarray / substring → consider sliding window
- Need for O(1) membership → hash set/map
- Optimal substructure + overlapping subproblems → DP
- Connectivity / components → graph DFS/BFS or Union-Find
Primary topics: depth first search.
Follow-up Interview Questions
Follow-ups
- How does the solution change if the input is a stream?
- Can you solve it in-place?
- What if duplicates must be handled differently?
- How would you parallelize the approach?
- Design tests that would break a buggy implementation.
Practice Recommendations
What to practice next
- Re-solve Evaluate Boolean Binary Tree in a second language (cpp, python).
- Drill 3–5 more problems tagged depth first search.
- Teach the solution out loud in under 5 minutes.
- Add this problem to your revision calendar in 3 days and 14 days.
Visualization
Study checklist
- Read the official problem statement on LeetCode
- Solve on paper / whiteboard first
- Implement the dfs backtracking approach
- Verify edge cases from the checklist
- State time and space complexity aloud
- Compare with the AlgoForge reference solution
- Schedule a revision session
Revision notes
Evaluate Boolean Binary Tree (#2331) — Easy. Pattern: dfs backtracking. Complexity: O(n) time / O(h) space. Re-derive the invariant before coding.
FAQs
What is the time complexity of Evaluate Boolean Binary Tree?+
The reference solutions aim for O(n) time and O(h) space. Always re-derive complexity from the code you write in the interview.
What pattern does Evaluate Boolean Binary Tree use?+
It primarily maps to dfs backtracking, within the broader topic of depth first search.
Is Evaluate Boolean Binary Tree good for interviews?+
Yes — as a Easy problem it is a solid practice target. Pair it with related problems in the same pattern family for spaced repetition.
Where can I read the official statement?+
Open the official LeetCode page for constraints and examples: https://leetcode.com/problems/evaluate-boolean-binary-tree/