Data Structures & Algorithms

roadmap.sh: https://roadmap.sh/datastructures-and-algorithms

Suggested path through the Data Structures & Algorithms nodes. Each node links to its lesson when written.

Nodes

Language & foundations

• pick-a-language
• language-syntax
• control-structures
• functions
• programming-paradigms
• basic-data-structures

Algorithmic complexity

• time-and-space-complexity
• asymptotic-notation
• asymptotic-notation
• asymptotic-notation
• asymptotic-notation
• time-and-space-complexity
• time-and-space-complexity

Common runtimes

• common-runtimes
• common-runtimes
• common-runtimes
• common-runtimes
• common-runtimes
• common-runtimes
• common-runtimes

Basic data structures

• arrays-and-dynamic-arrays
• linked-lists
• stacks-and-queues
• stacks-and-queues
• hash-tables
• string

Complex / advanced data structures

• complex-data-structures
• complex-data-structures
• heaps-and-priority-queues
• graphs
• graphs
• graphs
• graphs
• tries
• disjoint-set-union-find
• fenwick-trees
• segment-trees
• suffix-arrays
• suffix-trees

Tree data structures

• trees
• trees
• avl-trees
• b-trees
• 2-3-trees
• red-black-trees
• trees
• isam
• indexing

Tree traversal

• tree-traversal
• tree-traversal
• tree-traversal
• tree-traversal

Search algorithms

• searching
• searching
• graph-algorithms
• graph-algorithms

Sorting algorithms

• sorting
• sorting
• sorting
• sorting
• sorting
• sorting
• sorting
• shell-sort
• radix-sort
• cyclic-sort
• graph-algorithms
• random-shuffle

Graph algorithms

• graph-algorithms
• graph-algorithms
• a-algorithm
• minimum-spanning-tree
• kruskal-s-algorithm
• graph-algorithms

Problem-solving techniques

• brute-force
• backtracking
• divide-and-conquer
• greedy-algorithms
• dynamic-programming
• recursion
• two-pointers
• fast-and-slow-pointers
• sliding-window
• merge-intervals
• kth-element
• island-matrix-traversal
• concurrency-and-deadlocks

Practice

• platforms-to-practice
• leetcode
• edabit

Resources

See resources.md.

Project ideas

• Build a small DSA library in playgrounds/rust/ implementing core structures from scratch: linked list, dynamic array, hash table, binary search tree, and a min/max heap — each with unit tests covering edge cases.
• Implement a graph library in playgrounds/go/ with adjacency-list storage, then add BFS, DFS, Dijkstra, and Kruskal’s MST; visualize a sample network and shortest paths.
• Write a benchmarking harness (Go or Rust) that races the sorting algorithms (bubble, insertion, merge, quick, heap, radix) across input sizes/distributions and charts the empirical Big-O curves against theory.