DSA pattern
Sliding Window
Sliding window maintains a subset of elements (window) and slides it through the data structure. Perfect for finding subarrays or substrings that meet certain criteria like maximum sum, minimum length, or containing specific characters.
When to use
5 signals- 01Finding subarrays with a target sum
- 02Longest/shortest substring problems
- 03Maximum sum of k consecutive elements
- 04String permutation or anagram checks
- 05Minimum window substring
In interviews, call out the pattern early. It helps interviewers follow your reasoning and keeps your implementation focused. After solving, explain tradeoffs in plain language: why this approach is efficient, where it can break, and what edge cases you would test first.
Practice problems
4 listed- 01Maximum SubarrayPractice →
- 02Longest Substring Without RepeatingPractice →
- 03Minimum Window SubstringPractice →
- 04Sliding Window MaximumPractice →
Build a review loop
Treat each pattern as a repeating cycle, not a one-time read. Solve a fresh problem today, revisit the same pattern in 2-3 days, and run one timed attempt at the end of the week. This turns short-term familiarity into reliable recall for live interviews.
When reviewing, re-derive the core steps from scratch before checking a reference solution. If you can explain the state transitions and edge cases clearly, you are much more likely to execute well under interview pressure.