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How to Solve Minimum Initial Energy to Finish Tasks Problem
Master the Minimum Initial Energy to Finish Tasks LeetCode problem with undetectable real-time assistance. Get instant solutions and explanations during your coding interviews.
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LeetCode ProblemMinimum Initial Energy to Finish Tasks
You are given an array tasks where tasks[i] = [actuali, minimumi]: For example, if the task is [10, 12] and your current energy is 11, you cannot start this task. However, if your current energy is 13, you can complete this task, and your energy will be 3 after finishing it. You can finish the tasks in any order you like. Return the minimum initial amount of energy you will need to finish all the tasks.
ArrayGreedySorting
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Problem Breakdown
Understanding the Minimum Initial Energy to Finish Tasks Problem
Let's break down this LeetCode problem and understand what makes it challenging in interview settings.
Problem Statement
You are given an array tasks where tasks[i] = [actuali, minimumi]: For example, if the task is [10, 12] and your current energy is 11, you cannot start this task. However, if your current energy is 13, you can complete this task, and your energy will be 3 after finishing it. You can finish the tasks in any order you like. Return the minimum initial amount of energy you will need to finish all the tasks.
HardProblem #1665
LeetCodeMinimum Initial Energy to Finish Tasks
Related Topics
ArrayGreedySorting
How Phantom Code Helps
Get real-time assistance for Minimum Initial Energy to Finish Tasks problems during coding interviews. Phantom Code provides instant solutions and explanations.
Examples
# Example 1
Input
tasks = [[1,2],[2,4],[4,8]]
Output
8
# Example 2
Input
tasks = [[1,3],[2,4],[10,11],[10,12],[8,9]]
Output
32
# Example 3
Input
tasks = [[1,7],[2,8],[3,9],[4,10],[5,11],[6,12]]
Output
27
Constraints
1 <= tasks.length <= 105
1 <= actuali <= minimumi <= 104
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Solve Minimum Initial Energy to Finish Tasks — You are given an array tasks where tasks[i] = [actuali, minimumi]: For example, ...
Here's the optimal approach using Array:
def solve(input):
# Optimal O(n) solution
return result
Time: O(n) | Space: O(n)
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Frequently Asked Questions
Common questions about solving Minimum Initial Energy to Finish Tasks and using Phantom Code during coding interviews.
How does Phantom Code help me solve coding problems like Minimum Initial Energy to Finish Tasks during interviews?
Phantom Code generates complete solutions instantly with proper complexity analysis, letting you focus on explaining your approach and demonstrating problem-solving skills rather than getting stuck on implementation details during high-pressure situations.
What if the interviewer asks follow-up questions or modifications to problems like Minimum Initial Energy to Finish Tasks?
Phantom Code adapts in real-time. Screenshot the modified problem or use audio mode to capture the interviewer's follow-up, and get an updated solution within seconds — including edge cases and optimizations.
Can Phantom Code help me communicate my solution for problems like Minimum Initial Energy to Finish Tasks?
Yes. Phantom Code provides step-by-step approach explanations with 3 progressive thoughts, so you can walk through your solution naturally. It also provides time and space complexity analysis to discuss trade-offs.
How does Phantom Code assist with different programming languages for Minimum Initial Energy to Finish Tasks type problems?
Phantom Code supports 11 programming languages including Python, Java, C++, JavaScript, TypeScript, Go, Rust, Ruby, Swift, Kotlin, and C#. Set your preferred language and get idiomatic solutions.
What coding mistakes does Phantom Code help me avoid during Minimum Initial Energy to Finish Tasks interviews?
Phantom Code catches common mistakes like off-by-one errors, missing edge cases, incorrect base conditions, and suboptimal approaches. It provides clean, well-structured code that handles all edge cases.
Is Phantom Code detectable when solving problems like Minimum Initial Energy to Finish Tasks during live interviews?
No. Phantom Code runs as an invisible desktop overlay that doesn't appear in screen shares, recordings, or proctoring software. It works with Zoom, HackerRank, CodeSignal, CoderPad, and all major platforms.
How does Phantom Code help when I'm struggling with Minimum Initial Energy to Finish Tasks style questions under pressure?
The AI provides structured guidance: first the approach (what algorithm/data structure to use and why), then the implementation with clean code, and finally complexity analysis. This helps you think clearly even under pressure.
Does Phantom Code work for the coding platforms used in Minimum Initial Energy to Finish Tasks interviews?
Yes. Phantom Code works with all major coding platforms including LeetCode, HackerRank, CodeSignal, CoderPad, HackerEarth, and any browser-based coding environment.
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