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Title: Code to Architecture
This roadmap turns the DSA pattern series into a deliberate reading sequence instead of a loose archive. The goal is not to memorize isolated tricks. The goal is to recognize problem signals quickly, choose the right pattern, and explain the invariant behind the solution in an interview-ready way.
What This Roadmap CoversThe series is organized to move in a practi...
Union-Find solves dynamic connectivity problems efficiently. It supports two core operations:
find(x) -> representative of component union(a, b) -> merge components DSU TemplateWhat we are doing actually:
Start with every node as its own parent. find compresses paths so future lookups are faster. union merges two roots and keeps the tree shallo...Choose shortest-path algorithm based on edge weights:
unweighted: BFS non-negative weighted: Dijkstra negative edges: Bellman-Ford (advanced) Pattern 1: BFS Shortest Path (Unweighted)Problem description: Find the shortest number of edges from src to dst in an unweighted graph.
What we are doing actually:
BFS explores nodes in increasing distan...Graph traversal is foundational for connectivity, reachability, and component analysis. The two primary techniques are DFS and BFS.
Graph Representation List<List<Integer>> g = new ArrayList<>(); for (int i = 0; i < n; i++) g.add(new ArrayList<>()); for (int[] e : edges) { g.get(e[0]).add(e[1]); g.get(e[1]).add(e[0]); // undirected } D...BFS traverses trees level by level. It is ideal for shortest-level decisions and level-grouped output.
Core IdeaUse queue and process nodes by level size.
What we are doing actually:
Put the root in a queue. Snapshot the current queue size before each level. Process exactly that many nodes to keep levels separated. Enqueue children for the next r...