210. Course Schedule II
At a Glance
- Topic: graphs
- Pattern: Topological Sort
- Difficulty: Medium
- Companies: Amazon, Google, Meta, Microsoft, Apple
- Frequency: Very High
- LeetCode: 210
Problem (one-liner)
Return one valid order to take all numCourses given prerequisite pairs bi → ai (must take bi before ai), or [] if impossible (cycle).
Core Basics
- Opening move: classify the object (interval, multiset, trie node, bitmask, overlapping sub-intervals…) and whether the answer lives in an enumeration, ordering, partition, graph walk, DP table, etc.
- Contracts: spell what a valid partial solution looks like at each step—the thing you inductively preserve.
- Complexity anchors: state the brute upper bound and the structural fact (sorting, monotonicity, optimal substructure, greedy exchange, hashability) that should beat it.
Understanding
- Why brute hurts: name the repeated work or state explosion in one sentence.
- Why optimal is safe: the invariant / exchange argument / optimal-subproblem story you would tell a staff engineer.
Memory Hooks
- One chant / rule: a single memorable handle (acronym, operator trick, or shape) you can recall under time pressure.
Recognition Cues
- Same as 207 but need actual order (Kahn or DFS postorder reversed)
Study Pattern (SDE3+)
- 0–3 min: restate I/O and brittle edges aloud, then verbalize two approaches with time/space before you touch the keyboard.
- Implementation pass: one-line invariant above the tight loop; state what progress you make each iteration.
- 5 min extension: pick one constraint twist (immutable input, stream, bounded memory, parallel readers) and explain what in your solution breaks without a refactor.
Diagram
At-a-glance flow (replace with problem-specific Mermaid as you refine this note). camelCase node IDs; no spaces in IDs.
Loading diagram…
Approaches
- Kahn — pop indegree
0, append to order —O(V+E). - DFS — postorder on reversed graph or three-color + build reverse of finish order—
O(V+E).
Optimal Solution
Go
func findOrder(numCourses int, prerequisites [][]int) []int {
adjacency := make([][]int, numCourses)
indegree := make([]int, numCourses)
for _, edge := range prerequisites {
course := edge[0]
prerequisite := edge[1]
adjacency[prerequisite] = append(adjacency[prerequisite], course)
indegree[course]++
}
queue := make([]int, 0)
for course := 0; course < numCourses; course++ {
if indegree[course] == 0 {
queue = append(queue, course)
}
}
order := make([]int, 0, numCourses)
head := 0
for head < len(queue) {
current := queue[head]
head++
order = append(order, current)
for _, neighbor := range adjacency[current] {
indegree[neighbor]--
if indegree[neighbor] == 0 {
queue = append(queue, neighbor)
}
}
}
if len(order) != numCourses {
return []int{}
}
return order
}JavaScript
function findOrder(numCourses, prerequisites) {
const adjacency = Array.from({ length: numCourses }, () => []);
const indegree = new Array(numCourses).fill(0);
for (const edge of prerequisites) {
const course = edge[0];
const prerequisite = edge[1];
adjacency[prerequisite].push(course);
indegree[course] += 1;
}
const queue = [];
for (let course = 0; course < numCourses; course += 1) {
if (indegree[course] === 0) {
queue.push(course);
}
}
const order = [];
let head = 0;
while (head < queue.length) {
const current = queue[head];
head += 1;
order.push(current);
for (const neighbor of adjacency[current]) {
indegree[neighbor] -= 1;
if (indegree[neighbor] === 0) {
queue.push(neighbor);
}
}
}
if (order.length !== numCourses) {
return [];
}
return order;
}Walkthrough
Kahn queue drains all indegree-zero nodes; order length short iff cycle.
Invariant: Any node still with positive indegree after process lies on a directed cycle or unreachable sink component.
Edge Cases
- Linear chain — unique order modulo compatible swaps
- Empty prereqs — any permutation works; Kahn may output
0,1,2,...
Pitfalls
- Same edge direction mistake as 207
Similar Problems
- 207. Course Schedule — boolean feasibility, same edge direction
- 269. Alien Dictionary — topo output as letters
- 329. Longest Increasing Path in a Matrix — DAG DP after implicit edges
Variants
- Multiple valid orders — Kahn can emit different sequences; verify lexical smallest if asked.
- Detect cycle and print edge — combine with union-find or DFS edge classification.
Mind-Map Tags
#topological-sort #kahn #ordering #bfs-level #course-plan
Mark this page when you finish learning it.
Last updated on
Spotted something unclear or wrong on this page?