Design Snake Game
Time O(1) · Space O(s) · Official statement on LeetCode
Solutions
// Time: O(1) per move
// Space: O(s), s is the current length of the snake.
class SnakeGame {
public:
/** Initialize your data structure here.
@param width - screen width
@param height - screen height
@param food - A list of food positions
E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. */
SnakeGame(int width, int height, vector<vector<int>>& food)
: food_(food)
, f_{0}
, width_{width}
, height_{height}
, score_{0}
, snake_{{0, 0}}
, lookup_{{0}} {
}
/** Moves the snake.
@param direction - 'U' = Up, 'L' = Left, 'R' = Right, 'D' = Down
@return The game's score after the move. Return -1 if game over.
Game over when snake crosses the screen boundary or bites its body. */
int move(string direction) {
const auto x = snake_.back()[0] + direction_[direction].first;
const auto y = snake_.back()[1] + direction_[direction].second;
const auto tail = snake_.front();
lookup_.erase(hash(tail[0], tail[1]));
snake_.pop_front();
if (!valid(x, y)) {
return -1;
} else if (f_ != size(food_) && food_[f_][0] == x && food_[f_][1] == y) {
++score_;
++f_;
snake_.push_front(tail);
lookup_.emplace(hash(tail[0], tail[1]));
}
snake_.push_back({x, y});
lookup_.emplace(hash(x, y));
return score_;
}
private:
bool valid(int x, int y) {
if (x < 0 || x >= height_ || y < 0 || y >= width_) {
return false;
}
return !lookup_.count(hash(x, y));
}
int hash(int x, int y) {
return x * width_ + y;
}
const vector<vector<int>>& food_;
int f_, width_, height_, score_;
deque<vector<int>> snake_;
unordered_set<int> lookup_;
unordered_map<string, pair<int, int>> direction_ = {{"U", {-1, 0}}, {"L", {0, -1}},
{"R", {0, 1}}, {"D", {1, 0}}};
};
Beginner Explanation
What is Design Snake Game?
Design Snake Game (LeetCode #353) is a Medium problem that primarily trains design.
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. Official solution notes mention: Deque.
AlgoForge explanations are original teaching notes. Always open the official problem statement on LeetCode for constraints and examples.
Interview Walkthrough
Interview approach for Design Snake Game
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(1)) and space (O(s)) 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(1) time and O(s) space.
Pattern focus: general problem-solving
Use the pattern as a checklist:
- Identify the dominant pattern and stick to one clear invariant
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(1) |
| Space | O(s) |
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 Design Snake Game
- 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
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 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: design.
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 Design Snake Game in a second language (cpp, python).
- Drill 3–5 more problems tagged design.
- 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
Design Snake Game (#353) — Medium. Pattern: general problem-solving. Complexity: O(1) time / O(s) space. Re-derive the invariant before coding.
FAQs
What is the time complexity of Design Snake Game?+
The reference solutions aim for O(1) time and O(s) space. Always re-derive complexity from the code you write in the interview.
What pattern does Design Snake Game use?+
It primarily maps to general problem-solving, within the broader topic of design.
Is Design Snake Game 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/design-snake-game/