Cracking Coding Interviews: How to Choose Between Prefix Hashing and Sliding Window

Описание: Are you struggling to decide when to use a Sliding Window versus Prefix Hashing? In this video, we break down the conceptual transition between these two powerful techniques for solving array and string problems.
What You’ll Learn:
• Quick Recap: How prefix hashing tracks a running state using counts or sums.
• The "Exactly K" Problem: A deep dive into counting substrings where characters occur exactly k times using modulo states.
• The Transition: Why sliding window is better for monotone properties (like max sum or distinct characters), while prefix hashing handles global/complex constraints.
• The Decision Framework: 3 questions to ask before writing a single line of code to ensure you pick the right approach.
Timestamps:
• 0:00 – Intro: Bridging the Logic
• 0:30 – Prefix Hashing Recap & Dry Run
• 1:30 – Why Sliding Window? (Constraints & Violations)
• 3:00 – The Decision Framework: 3 Questions to Ask
• 4:00 – Practical Comparison & Next Steps
Featured Code Example: We explore a specific implementation for finding substrings where all characters occur exactly k times. This involves encoding states into a hash map to find valid windows efficiently.
Quick look at the Prefix Hashing Logic
for ch in s:
prefix[index_map[ch]] += 1
mod_state = tuple(x % k for x in prefix)
ans += state_count[mod_state]

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#leetcode , #codinginterviews , #datastructures , #competitiveprogramming , #softwareengineer
#SubstringProblems, #ArrayAlgorithms, #timecomplexity , #StateEncoding