How do you solve The Employee That Worked on the Longest Task on LeetCode?

The Employee That Worked on the Longest Task (LeetCode #2432) can be solved using Optimal Solution. The optimal approach is Optimal Solution with Unknown time complexity and Unknown space complexity. Key insight: In the optimal solution, we keep track of the total time each employee worked using a single pass through the logs. This approach is efficient and avoids unnecessary computations.

What is the time complexity of The Employee That Worked on the Longest Task?

The optimal solution for The Employee That Worked on the Longest Task runs in Unknown time and uses Unknown space.

What algorithm or data structure is used to solve The Employee That Worked on the Longest Task?

The Employee That Worked on the Longest Task uses the following concepts: Array. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for The Employee That Worked on the Longest Task?

Tip 1: Always clarify the problem requirements before coding. Tip 2: Think about edge cases, such as when all employees have the same task duration. Tip 3: Explain your thought process while coding to show your understanding.

What are common mistakes when solving The Employee That Worked on the Longest Task?

Mistake 1: Forgetting to track the start time correctly. Mistake 2: Not handling ties properly.

The Employee That Worked on the Longest Task — LeetCode #2432 (Easy)

Tags: Array

Related patterns: Hash Map, Array

Optimal Solution approach

Time complexity: Unknown. Space complexity: Unknown.

In the optimal solution, we keep track of the total time each employee worked using a single pass through the logs. This approach is efficient and avoids unnecessary computations.

Step 1: Initialize an array to store the total time for each employee.
Step 2: Initialize a variable to keep track of the start time of the current task.
Step 3: Iterate through the logs, calculating the duration of each task and updating the corresponding employee's total time.
Step 4: After processing all logs, find the employee with the maximum time worked.
Step 5: If there's a tie, return the employee with the smallest ID.

Common Mistakes

Mistake 1: Forgetting to track the start time correctly.
Mistake 2: Not handling ties properly.

Interview Tips

Tip 1: Always clarify the problem requirements before coding.
Tip 2: Think about edge cases, such as when all employees have the same task duration.
Tip 3: Explain your thought process while coding to show your understanding.

#2432

The Employee That Worked on the Longest Task

Easy

Array↗Hash Map↗Array↗

LeetCode ↗

Approaches

💡

Intuition

Time UnknownSpace Unknown

In the optimal solution, we keep track of the total time each employee worked using a single pass through the logs. This approach is efficient and avoids unnecessary computations.

⚙️

Algorithm

5 steps

1Step 1: Initialize an array to store the total time for each employee.
2Step 2: Initialize a variable to keep track of the start time of the current task.
3Step 3: Iterate through the logs, calculating the duration of each task and updating the corresponding employee's total time.
4Step 4: After processing all logs, find the employee with the maximum time worked.
5Step 5: If there's a tie, return the employee with the smallest ID.

solution.py12 lines

1# Full working Python code
2n = 10
3logs = [[0,3],[2,5],[0,9],[1,15]]
4times = [0] * n
5start_time = 0
6for id, leaveTime in logs:
7    duration = leaveTime - start_time
8    times[id] += duration
9    start_time = leaveTime
10max_time = max(times)
11result = min(i for i, t in enumerate(times) if t == max_time)
12print(result)

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