#2224

Easy

auto_awesomeGreedy choice plus invariant validation

LeetCode Problem Workspace

Minimum Number of Operations to Convert Time

The problem asks to find the minimum number of operations to convert one time string to another using specific time increments.

string greedy

Problem Statement

You are given two strings, current and correct, representing times in a 24-hour format "HH:MM". You need to determine the minimum number of operations to convert the current time to the correct time. The only allowed operations are adding 1, 5, 15, or 60 minutes to the current time.

Both the current and correct times are in the format "HH:MM", and current is guaranteed to be less than or equal to correct. The challenge is to calculate how to achieve the transformation in the least number of operations using a greedy approach.

Examples

Example 1

Input: current = "02:30", correct = "04:35"

Output: 3

We can convert current to correct in 3 operations as follows:

Add 60 minutes to current. current becomes "03:30".
Add 60 minutes to current. current becomes "04:30".
Add 5 minutes to current. current becomes "04:35". It can be proven that it is not possible to convert current to correct in fewer than 3 operations.

Example 2

Input: current = "11:00", correct = "11:01"

Output: 1

We only have to add one minute to current, so the minimum number of operations needed is 1.

Constraints

current and correct are in the format "HH:MM"
current <= correct

Solution Approach

Convert Times to Minutes

Start by converting both the current and correct times into minutes since midnight. This simplifies the problem to finding the difference in minutes between the two times.

Greedy Approach

Apply a greedy approach by using the largest possible operation (60 minutes) first, then 15 minutes, 5 minutes, and finally 1 minute. This ensures you minimize the number of operations required.

Handle the Difference Efficiently

After calculating the difference in minutes, reduce the difference using the allowed increments in a greedy manner. Each time you subtract one of the increments, you count it as an operation.

Complexity Analysis

Metric	Value
Time	Depends on the final approach
Space	Depends on the final approach

The time complexity is O(1) because the problem involves only a fixed number of operations to compute the difference and apply the greedy approach. The space complexity is also O(1) as we only need a few variables to store the times and the difference.

What Interviewers Usually Probe

Can the candidate identify the correct greedy choice for minimizing operations?
Does the candidate understand how to convert times to a simpler representation (minutes)?
Is the candidate able to effectively implement a greedy strategy?

Common Pitfalls or Variants

Common pitfalls

Failing to convert times to minutes, which complicates the difference calculation.
Not choosing the largest increment first, which leads to a higher number of operations.
Misunderstanding the constraints, particularly the ordering of the current and correct times.

Follow-up variants

What if you were allowed to decrease the current time instead of only increasing it?
What if you could use different increments for each operation (e.g., 1, 2, 3, 4 minutes)?
What if the times were provided in a different format, such as 12-hour time?

FAQ

How does the greedy approach work in this problem?

The greedy approach starts by using the largest allowed increment (60 minutes), then progressively uses smaller increments (15, 5, and 1 minute) to reduce the difference in the minimum number of operations.

What should I do if the times are in 12-hour format instead of 24-hour format?

First, convert the 12-hour format into 24-hour time. Then, proceed with the same approach as in the problem description.

What is the time complexity of this solution?

The time complexity is O(1) because the solution involves a constant number of operations, irrespective of the size of the input times.

What if the difference between the current and correct time is zero?

If the difference is zero, no operations are needed, and the answer is 0.

Can this approach be optimized further?

The greedy approach used here is already optimal for this problem, as it minimizes the number of operations by always using the largest increments first.

terminal

Solution

Solution 1

#### Python3

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class Solution:
    def convertTime(self, current: str, correct: str) -> int:
        a = int(current[:2]) * 60 + int(current[3:])
        b = int(correct[:2]) * 60 + int(correct[3:])
        ans, d = 0, b - a
        for i in [60, 15, 5, 1]:
            ans += d // i
            d %= i
        return ans

Continue Practicing

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