How do you solve Teemo Attacking on LeetCode?

Teemo Attacking (LeetCode #495) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(1) space complexity. Key insight: Understanding the overlap of poison durations is crucial for optimizing the solution.

What is the brute force solution for Teemo Attacking?

The brute force approach for Teemo Attacking is Brute Force, with O(n²) time complexity and O(n) space complexity. The brute force approach involves calculating the poisoned seconds for each attack individually. We check for overlaps in poison durations and count the total unique seconds Ashe is poisoned. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Teemo Attacking?

Teemo Attacking uses the following concepts: Array, Simulation. The recommended patterns to study are: Array, Simulation.

What are the interview tips for Teemo Attacking?

Always start with the simplest solution to show your thought process. Explain your reasoning clearly, especially when transitioning to the optimal solution. Practice dry runs of your code with examples to ensure you understand the flow.

What are common mistakes when solving Teemo Attacking?

Confusing the total poisoned time with the number of attacks. Forgetting to handle the case where attacks overlap correctly.

#495

Teemo Attacking

Easy

ArraySimulationArraySimulation

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(n)	O(1)

💡

Intuition

Time O(n)Space O(1)

The optimal approach leverages the fact that we can track the end of the poison effect without needing to store every second. We only need to check if the next attack overlaps with the current poison duration.

⚙️

Algorithm

4 steps

1Step 1: Initialize a variable to track total poisoned time and another to track the end of the current poison effect.
2Step 2: Iterate through the timeSeries. For each attack, check if it overlaps with the current poison effect.
3Step 3: If it overlaps, only add the additional poisoned time. If it doesn't overlap, add the full duration.
4Step 4: Update the end of the poison effect after each attack.

solution.py12 lines

1# Full working Python code
2
3def totalPoisonedTime(timeSeries, duration):
4    total_time = 0
5    poison_end = 0
6    for attack_time in timeSeries:
7        if attack_time < poison_end:
8            total_time += attack_time + duration - poison_end
9        else:
10            total_time += duration
11        poison_end = attack_time + duration
12    return total_time

ℹ

Complexity note: This complexity is linear because we only make a single pass through the timeSeries array, performing constant-time operations for each attack.

1Understanding the overlap of poison durations is crucial for optimizing the solution.
2Using a set to track unique seconds can be inefficient; instead, track the total time directly.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.