Determine if a Simple Graph Exists
Time O(nlogn) · Space O(1) · Official statement on LeetCode
Solutions
// Time: O(nlogn)
// Space: O(1)
// Erdős–Gallai theorem, sort, prefix sum, two pointers
class Solution {
public:
bool simpleGraphExists(vector<int>& degrees) {
// reference: https://en.wikipedia.org/wiki/Erd%C5%91s%E2%80%93Gallai_theorem
const auto& total = accumulate(cbegin(degrees), cend(degrees), 0LL);
if (total % 2) {
return false;
}
sort(begin(degrees), end(degrees), greater<int>());
int64_t lhs = 0, suffix1 = total, suffix2 = 0;
for (int k = 1, i = size(degrees) - 1; k <= size(degrees); ++k) {
lhs += degrees[k - 1];
suffix1 -= degrees[k - 1];
for (; i >= 0 && degrees[i] < k; --i) {
suffix2 += degrees[i];
};
const auto& rhs = static_cast<int64_t>(k) * (k - 1) + ((i - k + 1 > 0) ? static_cast<int64_t>(i - k + 1) * k + suffix2: suffix1);
if (!(lhs <= rhs)) {
return false;
}
}
return true;
}
};
Beginner Explanation
What is Determine if a Simple Graph Exists?
Determine if a Simple Graph Exists (LeetCode #3656) is a Medium problem that primarily trains graph.
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 graph, sort, prefix sum, and two pointers.
- 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. Official solution notes mention: Graph, Erdős–Gallai Theorem, Sort, Prefix sum.
AlgoForge explanations are original teaching notes. Always open the official problem statement on LeetCode for constraints and examples.
Interview Walkthrough
Interview approach for Determine if a Simple Graph Exists
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 graph, sort, prefix sum, and two pointers.
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(nlogn)) and space (O(1)) 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(nlogn) time and O(1) space.
Pattern focus: graph, sort, prefix sum, and two pointers
Use the pattern as a checklist:
- graph — confirm the invariant holds after each step
- sort — confirm the invariant holds after each step
- prefix sum — confirm the invariant holds after each step
- two pointers — confirm the invariant holds after each step
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(nlogn) |
| Space | O(1) |
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 Determine if a Simple Graph Exists
- Skipping edge cases — empty collections, single-element inputs, max constraints.
- Wrong invariant for graph, sort, prefix sum, and two pointers — 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 graph, sort, prefix sum, and two pointers solution
- Space-optimized rewrite
Prompt slot: expand alternatives for determine-if-a-simple-graph-exists.
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 graph, sort, prefix sum, and two pointers:
- 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: graph.
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 Determine if a Simple Graph Exists in a second language (cpp, python).
- Drill 3–5 more problems tagged graph.
- 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 graph, sort, prefix sum, and two pointers 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
Determine if a Simple Graph Exists (#3656) — Medium. Pattern: graph, sort, prefix sum, and two pointers. Complexity: O(nlogn) time / O(1) space. Re-derive the invariant before coding.
FAQs
What is the time complexity of Determine if a Simple Graph Exists?+
The reference solutions aim for O(nlogn) time and O(1) space. Always re-derive complexity from the code you write in the interview.
What pattern does Determine if a Simple Graph Exists use?+
It primarily maps to graph, sort, prefix sum, and two pointers, within the broader topic of graph.
Is Determine if a Simple Graph Exists 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/determine-if-a-simple-graph-exists/