5 — Algorithm Design Principles

A field guide to recognizing which of the five recurring design paradigms — brute force, divide and conquer, greedy, dynamic programming, backtracking — a new problem is calling for, before you write a line of implementation.

9 — Eulerian & Hamiltonian Paths

Why an Eulerian path (every edge once) is checkable in O(V) by counting degrees while a Hamiltonian path (every vertex once) is NP-complete with no known shortcut — Hierholzer's algorithm, backtracking search, and why identical phrasing hides opposite tractability.

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.

2 — N Queens

Placing N non-attacking queens via backtracking with row/column/diagonal constraint tracking.

3 — Sudoku Solver

Constraint-propagation backtracking over a 9×9 grid with row/column/box validity checks.

4 — Permutations

Generating all orderings of a set via backtracking, including the handling of duplicate elements.

5 — Combinations

Generating all fixed-size subsets via backtracking, and its relation to subset/power-set generation.