Minimum Area Rectangle II
Time O(n^2) ~ O(n^3) · Space O(n^2) · Official statement on LeetCode
Solutions
// Time: O(n^2) ~ O(n^3)
// Space: O(n^2)
class Solution {
public:
template <typename T>
struct PairHash {
size_t operator()(const pair<T, T>& p) const {
size_t seed = 0;
seed ^= std::hash<T>{}(p.first) + 0x9e3779b9 + (seed<<6) + (seed>>2);
seed ^= std::hash<T>{}(p.second) + 0x9e3779b9 + (seed<<6) + (seed>>2);
return seed;
}
};
double minAreaFreeRect(vector<vector<int>>& points) {
sort(points.begin(), points.end());
unordered_map<pair<double, double>, vector<pair<double, double>>, PairHash<double>> lookup;
for (int i = 0; i < points.size() - 1; ++i) {
for (int j = i + 1; j < points.size(); ++j) {
lookup[make_pair(points[i][0] - points[j][0],
points[i][1] - points[j][1])].emplace_back(
(points[i][0] + points[j][0]) / 2,
(points[i][1] + points[j][1]) / 2
);
}
}
double result = numeric_limits<double>::infinity();
for (const auto& kvp : lookup) {
for (int i = 0; i < kvp.second.size() - 1; ++i) {
for (int j = i + 1; j < kvp.second.size(); ++j) {
auto x1 = kvp.first.first;
auto y1 = kvp.first.second;
auto x2 = kvp.second[i].first - kvp.second[j].first;
auto y2 = kvp.second[i].second - kvp.second[j].second;
if (x1 * x2 + y1 * y2 == 0.0) {
result = min(result, sqrt((x1 * x1 + y1 * y1) *
(x2 * x2 + y2 * y2)));
}
}
}
}
return result != numeric_limits<double>::infinity() ? result : 0.0;
}
};
Beginner Explanation
What is Minimum Area Rectangle II?
Minimum Area Rectangle II (LeetCode #963) is a Medium problem that primarily trains math.
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 general problem-solving.
- Only then translate the idea into code.
Why this problem matters
It sits in the sweet spot of interview difficulty: multiple valid approaches, clear trade-offs.
AlgoForge explanations are original teaching notes. Always open the official problem statement on LeetCode for constraints and examples.
Interview Walkthrough
Interview approach for Minimum Area Rectangle II
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 general problem-solving.
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^2) ~ O(n^3)) and space (O(n^2)) 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^2) ~ O(n^3) time and O(n^2) space.
Pattern focus: general problem-solving
Use the pattern as a checklist:
- Identify the dominant pattern and stick to one clear invariant
Start from the primary solution, then rewrite from memory to lock it in.
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^2) ~ O(n^3) |
| Space | O(n^2) |
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 Minimum Area Rectangle II
- Skipping edge cases — empty collections, single-element inputs, max constraints.
- Wrong invariant for general problem-solving — 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
AI expand laterAlternatives
Placeholder for multi-approach comparison. Future AI content generation can expand:
- Brute force baseline
- Optimal general problem-solving solution
- Space-optimized rewrite
Prompt slot: expand alternatives for minimum-area-rectangle-ii.
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 general problem-solving:
- 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: math.
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 Minimum Area Rectangle II in a second language (cpp, python).
- Drill 3–5 more problems tagged math.
- 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 general problem-solving 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
Minimum Area Rectangle II (#963) — Medium. Pattern: general problem-solving. Complexity: O(n^2) ~ O(n^3) time / O(n^2) space. Re-derive the invariant before coding.
FAQs
What is the time complexity of Minimum Area Rectangle II?+
The reference solutions aim for O(n^2) ~ O(n^3) time and O(n^2) space. Always re-derive complexity from the code you write in the interview.
What pattern does Minimum Area Rectangle II use?+
It primarily maps to general problem-solving, within the broader topic of math.
Is Minimum Area Rectangle II good for interviews?+
Yes — as a Medium 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/minimum-area-rectangle-ii/