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Here Be Dragons

Computer Science

Topics

  • Data Structures, the top 10 data structures that show up in coding interviews, with time complexity tables, 5 common DSA uses, and Python code for each
  • Coding Problems, walkthroughs of all 150 NeetCode problems across 18 categories, each with brute-force, improved, and optimal approaches in Python
  • Coding Concepts, approach tactics behind coding problems: two pointers, sliding windows, greedy proofs, DP states, graph traversal, monotonic structures, and more
  • Haversine Distance, great-circle distance between lat/lon points, with Python/SQL/JavaScript implementations and notes on when to upgrade to Vincenty or Karney
  • Vehicle Routing Problem, CVRP, VRPTW, pickup-and-delivery, and what Google OR-Tools actually does
  • Functional Core, Imperative Shell, Gary Bernhardt’s architecture pattern: pure logic at the center, I/O at the edges
  • Flight Itinerary with Transfers, find a valid trip through a flight graph with departure and arrival times: DFS, BFS for fewest layovers, Dijkstra for earliest arrival, plus the time-expanded graph framework that subsumes all three
  • Named Algorithms, the canon worth knowing by sight: Kadane’s, Floyd’s, Dijkstra’s, KMP, and the rest
  • Technology Laws, named laws and principles every software engineer will encounter: Conway, Brooks, Amdahl, Little, Goodhart, Hyrum, Gall, Schneier, and more
  • Graph Theory, terminology, graph types, components, SCCs, DAGs, bipartite graphs, weighted-graph problem modeling
  • Sentinel Values, the “impossible” placeholder pattern across DP, shortest-path, search, and linked-list problems
  • Design Patterns, the 23 Gang of Four patterns grouped by intent: creational, structural, and behavioral, with TypeScript, Python, and Go implementations
  • Kademlia DHT, XOR metric, k-buckets, iterative lookup, and the four RPCs behind BitTorrent mainline DHT, IPFS, and Ethereum devp2p, with Python, TypeScript, and Go implementations

How the topics connect

Each LeetCode problem page links back to neighboring problems and, when useful, to the approach pages under Coding Concepts. Concept pages link back to representative problems so a learner can drill the tactic directly. The geospatial topics (haversine + VRP) share the distance-matrix foundation, VRP solvers typically consume haversine output.

Why the name "Here Be Dragons"?