Jumped straight to Dijkstra which was the right call, but I fumbled the input parsing longer than I should have.
First, clarify the problem constraints (e.g., non-negative weights, graph size) and choose Dijkstra's algorithm with a min-heap for efficiency. Then, outline the parsing of the input string, construction of the adjacency list, and execution of the algorithm to compute distances. Finally, discuss handling edge cases and complexity.
Pro tip: Mention that you would use a priority queue and a visited set to avoid redundant processing, and note that if negative weights were allowed, you'd switch to Bellman-Ford. This shows awareness of algorithm trade-offs.
Ask about graph size, weight ranges (negative?), and whether the graph is connected. Confirm the input format and expected output.
Split the input string by semicolons and spaces to extract edges, then build an adjacency list (or matrix) for efficient traversal.
Select Dijkstra's algorithm for non-negative weights, justifying its O((V+E) log V) time with a binary heap. If negative weights, mention Bellman-Ford.
Use a min-heap for unvisited nodes, a distance array initialized to infinity, and update distances via edge relaxation. Track visited nodes to avoid reprocessing.
Discuss time/space complexity, handle disconnected nodes (distance remains infinity), and consider early termination if only a target node is needed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.