5 — String Matching Advanced
Purpose
[stub: string-matching-advanced]
Metadata
| Author | Amit Singh |
| Scope | data-structures-algorithms |
Local graph
Linked from 3 notes
8 — String Algorithms
Palindrome checks via two pointers and expand-around-center, anagram detection by counting vs. sorting, the naive O(n·m) substring search baseline, and why Python's string immutability turns 'reverse in place' into a trick question.
10 — Suffix Trie
Suffix-indexed trie variant for substring and pattern-matching queries.
Data Structures & Algorithms
A book-shaped table of contents for MAANG-interview DSA prep: Python language foundations, mathematical and algorithmic foundations, arrays/strings, linked structures, stacks/queues, trees, graphs, sorting/searching, dynamic programming, greedy algorithms, backtracking, bit manipulation, advanced data structures, advanced algorithms, interview problem patterns, and MAANG interview mastery — a book-length progression from fundamentals to Google/Meta/Amazon/Apple/Netflix/Microsoft (L4–L6) interview readiness.
Related notes
7 — Matrix Exponentiation
Representing a linear recurrence as matrix multiplication to compute the n-th term in O(log n).
8 — Fast Exponentiation
Binary exponentiation for computing a^n (or a^n mod m) in O(log n) instead of O(n).
9 — Randomized Algorithms
Algorithms that use randomness for expected-case guarantees — randomized QuickSelect, Monte Carlo vs. Las Vegas framing.
1 — Divide & Conquer Optimization
Speeding up a DP transition using divide-and-conquer or monotonic-decision-boundary tricks (e.g. the DC optimization, Knuth's optimization).