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How to Solve Search Suggestions System Problem
Master the Search Suggestions System LeetCode problem with undetectable real-time assistance. Get instant solutions and explanations during your coding interviews.
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Start Free for WindowsMedium#1268
LeetCode ProblemSearch Suggestions System
You are given an array of strings products and a string searchWord. Design a system that suggests at most three product names from products after each character of searchWord is typed. Suggested products should have common prefix with searchWord. If there are more than three products with a common prefix return the three lexicographically minimums products. Return a list of lists of the suggested products after each character of searchWord is typed.
ArrayStringBinary SearchTrieSortingHeap (Priority Queue)
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Problem Breakdown
Understanding the Search Suggestions System Problem
Let's break down this LeetCode problem and understand what makes it challenging in interview settings.
Problem Statement
You are given an array of strings products and a string searchWord. Design a system that suggests at most three product names from products after each character of searchWord is typed. Suggested products should have common prefix with searchWord. If there are more than three products with a common prefix return the three lexicographically minimums products. Return a list of lists of the suggested products after each character of searchWord is typed.
MediumProblem #1268
LeetCodeSearch Suggestions System
Related Topics
ArrayStringBinary SearchTrieSortingHeap (Priority Queue)
How Phantom Code Helps
Get real-time assistance for Search Suggestions System problems during coding interviews. Phantom Code provides instant solutions and explanations.
Examples
# Example 1
Input
products = ["mobile","mouse","moneypot","monitor","mousepad"], searchWord = "mouse"
Output
[["mobile","moneypot","monitor"],["mobile","moneypot","monitor"],["mouse","mousepad"],["mouse","mousepad"],["mouse","mousepad"]]
# Example 2
Input
products = ["havana"], searchWord = "havana"
Output
[["havana"],["havana"],["havana"],["havana"],["havana"],["havana"]]
Constraints
1 <= products.length <= 1000
1 <= products[i].length <= 3000
1 <= sum(products[i].length) <= 2 * 104
All the strings of products are unique.
products[i] consists of lowercase English letters.
1 <= searchWord.length <= 1000
searchWord consists of lowercase English letters.
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Solve Search Suggestions System — You are given an array of strings products and a string searchWord. Design a sys...
Here's the optimal approach using Array:
def solve(input):
# Optimal O(n) solution
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Time: O(n) | Space: O(n)
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Frequently Asked Questions
Common questions about solving Search Suggestions System and using Phantom Code during coding interviews.
How does Phantom Code help me solve coding problems like Search Suggestions System 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 Search Suggestions System?
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 Search Suggestions System?
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 Search Suggestions System 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 Search Suggestions System 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 Search Suggestions System 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 Search Suggestions System 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 Search Suggestions System 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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