ALT ⏱️ Time & Space Complexity: ⌚ T.C: O(n × m) n = number of strings, m = length of each string 🫙 S.C: O(1) Only a counter used

ALT ✅ 📌 Time & Space Complexity ⌚ Time Complexity: O(M log M M) Sorting/grouping meetings by time → log M BFS visits each meeting edge once 🫙 Space Complexity: O(N M) knowsSecret[] for people and Temporary graph per time slot

ALT 📌 Time & Space Complexity ⌚ T.C: O(n × k) 🫙 S.C: O(k) (space optimized using 2 DP arrays)

ALT ⏱️ Time & Space Complexity ⌚ T.C: O(N) — single pass 🫙 S.C: O(1) — constant extra space

ALT 📌 Time & Space Complexity ⌚ Time Complexity: O(n) 🫙 Space Complexity: O(1)

ALT ✅ 📌 Time & Space Complexity ⌚ T.C: O(n * u) n = events, u = users (HERE/ALL scans) 🫙 S.C: O(u) online/offline tracking map

ALT ⏱️ Time & Space Complexity ⌚ T.C: O(m) — m = number of buildings (just two passes) 🫙 S.C: O(n) — storing row/column boundaries

ALT ⌚ Time & Space Complexity T.C: O(n) S.C: O(1)

ALT ⏱️ Complexity: T.C: O(n) S.C: O(n)

ALT 📌 Time & Space ⏱️ Time Complexity: O(n√n) 🗃️ Space Complexity: O(1)

ALT 📌 Time & Space Complexity ⌚ T.C: O(1) 🫙 S.C: O(1)

ALT ⏳ Time & Space Time Complexity: O(n) Space Complexity: O(n)

ALT ⌚ T.C: O(n) 🫙 S.C: O(1)

ALT ✅ 📌 Time & Space Complexity ⌚ T.C: O(n) — single pass through the array 🫙 S.C: O(1) — constant extra space

ALT ✅ 📌 Time & Space Complexity ⌚ T.C: O(26 * n) → O(n) Because: You iterate over all unique letters (max 26) For each, you scan the string twice → 26 × n 🫙 S.C: O(26) → O(1) Because: Set of unique letters = max 26 Middle set also max 26 → Constant extra space