Off-by-one on range boundaries
Wrong move: Loop endpoints miss first/last candidate.
Usually fails on: Fails on minimal arrays and exact-boundary answers.
Fix: Re-derive loops from inclusive/exclusive ranges before coding.
Break down a hard problem into reliable checkpoints, edge-case handling, and complexity trade-offs.
You are given an integer n, which indicates that there are n courses labeled from 1 to n. You are also given a 2D integer array relations where relations[j] = [prevCoursej, nextCoursej] denotes that course prevCoursej has to be completed before course nextCoursej (prerequisite relationship). Furthermore, you are given a 0-indexed integer array time where time[i] denotes how many months it takes to complete the (i+1)th course.
You must find the minimum number of months needed to complete all the courses following these rules:
Return the minimum number of months needed to complete all the courses.
Note: The test cases are generated such that it is possible to complete every course (i.e., the graph is a directed acyclic graph).
Example 1:
Input: n = 3, relations = [[1,3],[2,3]], time = [3,2,5] Output: 8 Explanation: The figure above represents the given graph and the time required to complete each course. We start course 1 and course 2 simultaneously at month 0. Course 1 takes 3 months and course 2 takes 2 months to complete respectively. Thus, the earliest time we can start course 3 is at month 3, and the total time required is 3 + 5 = 8 months.
Example 2:
Input: n = 5, relations = [[1,5],[2,5],[3,5],[3,4],[4,5]], time = [1,2,3,4,5] Output: 12 Explanation: The figure above represents the given graph and the time required to complete each course. You can start courses 1, 2, and 3 at month 0. You can complete them after 1, 2, and 3 months respectively. Course 4 can be taken only after course 3 is completed, i.e., after 3 months. It is completed after 3 + 4 = 7 months. Course 5 can be taken only after courses 1, 2, 3, and 4 have been completed, i.e., after max(1,2,3,7) = 7 months. Thus, the minimum time needed to complete all the courses is 7 + 5 = 12 months.
Constraints:
1 <= n <= 5 * 1040 <= relations.length <= min(n * (n - 1) / 2, 5 * 104)relations[j].length == 21 <= prevCoursej, nextCoursej <= nprevCoursej != nextCoursej[prevCoursej, nextCoursej] are unique.time.length == n1 <= time[i] <= 104Problem summary: You are given an integer n, which indicates that there are n courses labeled from 1 to n. You are also given a 2D integer array relations where relations[j] = [prevCoursej, nextCoursej] denotes that course prevCoursej has to be completed before course nextCoursej (prerequisite relationship). Furthermore, you are given a 0-indexed integer array time where time[i] denotes how many months it takes to complete the (i+1)th course. You must find the minimum number of months needed to complete all the courses following these rules: You may start taking a course at any time if the prerequisites are met. Any number of courses can be taken at the same time. Return the minimum number of months needed to complete all the courses. Note: The test cases are generated such that it is possible to complete every course (i.e., the graph is a directed acyclic graph).
Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.
Pattern signal: Array · Dynamic Programming · Topological Sort
3 [[1,3],[2,3]] [3,2,5]
5 [[1,5],[2,5],[3,5],[3,4],[4,5]] [1,2,3,4,5]
course-schedule-iii)parallel-courses)single-threaded-cpu)process-tasks-using-servers)maximum-employees-to-be-invited-to-a-meeting)Source-backed implementations are provided below for direct study and interview prep.
// Accepted solution for LeetCode #2050: Parallel Courses III
class Solution {
public int minimumTime(int n, int[][] relations, int[] time) {
List<Integer>[] g = new List[n];
Arrays.setAll(g, k -> new ArrayList<>());
int[] indeg = new int[n];
for (int[] e : relations) {
int a = e[0] - 1, b = e[1] - 1;
g[a].add(b);
++indeg[b];
}
Deque<Integer> q = new ArrayDeque<>();
int[] f = new int[n];
int ans = 0;
for (int i = 0; i < n; ++i) {
int v = indeg[i], t = time[i];
if (v == 0) {
q.offer(i);
f[i] = t;
ans = Math.max(ans, t);
}
}
while (!q.isEmpty()) {
int i = q.pollFirst();
for (int j : g[i]) {
f[j] = Math.max(f[j], f[i] + time[j]);
ans = Math.max(ans, f[j]);
if (--indeg[j] == 0) {
q.offer(j);
}
}
}
return ans;
}
}
// Accepted solution for LeetCode #2050: Parallel Courses III
func minimumTime(n int, relations [][]int, time []int) int {
g := make([][]int, n)
indeg := make([]int, n)
for _, e := range relations {
a, b := e[0]-1, e[1]-1
g[a] = append(g[a], b)
indeg[b]++
}
f := make([]int, n)
q := []int{}
ans := 0
for i, v := range indeg {
if v == 0 {
q = append(q, i)
f[i] = time[i]
ans = max(ans, time[i])
}
}
for len(q) > 0 {
i := q[0]
q = q[1:]
for _, j := range g[i] {
indeg[j]--
if indeg[j] == 0 {
q = append(q, j)
}
f[j] = max(f[j], f[i]+time[j])
ans = max(ans, f[j])
}
}
return ans
}
# Accepted solution for LeetCode #2050: Parallel Courses III
class Solution:
def minimumTime(self, n: int, relations: List[List[int]], time: List[int]) -> int:
g = defaultdict(list)
indeg = [0] * n
for a, b in relations:
g[a - 1].append(b - 1)
indeg[b - 1] += 1
q = deque()
f = [0] * n
ans = 0
for i, (v, t) in enumerate(zip(indeg, time)):
if v == 0:
q.append(i)
f[i] = t
ans = max(ans, t)
while q:
i = q.popleft()
for j in g[i]:
f[j] = max(f[j], f[i] + time[j])
ans = max(ans, f[j])
indeg[j] -= 1
if indeg[j] == 0:
q.append(j)
return ans
// Accepted solution for LeetCode #2050: Parallel Courses III
/**
* [2050] Parallel Courses III
*
* You are given an integer n, which indicates that there are n courses labeled from 1 to n. You are also given a 2D integer array relations where relations[j] = [prevCoursej, nextCoursej] denotes that course prevCoursej has to be completed before course nextCoursej (prerequisite relationship). Furthermore, you are given a 0-indexed integer array time where time[i] denotes how many months it takes to complete the (i+1)^th course.
* You must find the minimum number of months needed to complete all the courses following these rules:
*
* You may start taking a course at any time if the prerequisites are met.
* Any number of courses can be taken at the same time.
*
* Return the minimum number of months needed to complete all the courses.
* Note: The test cases are generated such that it is possible to complete every course (i.e., the graph is a directed acyclic graph).
*
* Example 1:
* <img alt="" src="https://assets.leetcode.com/uploads/2021/10/07/ex1.png" style="width: 392px; height: 232px;" />
*
* Input: n = 3, relations = [[1,3],[2,3]], time = [3,2,5]
* Output: 8
* Explanation: The figure above represents the given graph and the time required to complete each course.
* We start course 1 and course 2 simultaneously at month 0.
* Course 1 takes 3 months and course 2 takes 2 months to complete respectively.
* Thus, the earliest time we can start course 3 is at month 3, and the total time required is 3 + 5 = 8 months.
*
* Example 2:
* <img alt="" src="https://assets.leetcode.com/uploads/2021/10/07/ex2.png" style="width: 500px; height: 365px;" />
*
* Input: n = 5, relations = [[1,5],[2,5],[3,5],[3,4],[4,5]], time = [1,2,3,4,5]
* Output: 12
* Explanation: The figure above represents the given graph and the time required to complete each course.
* You can start courses 1, 2, and 3 at month 0.
* You can complete them after 1, 2, and 3 months respectively.
* Course 4 can be taken only after course 3 is completed, i.e., after 3 months. It is completed after 3 + 4 = 7 months.
* Course 5 can be taken only after courses 1, 2, 3, and 4 have been completed, i.e., after max(1,2,3,7) = 7 months.
* Thus, the minimum time needed to complete all the courses is 7 + 5 = 12 months.
*
*
* Constraints:
*
* 1 <= n <= 5 * 10^4
* 0 <= relations.length <= min(n * (n - 1) / 2, 5 * 10^4)
* relations[j].length == 2
* 1 <= prevCoursej, nextCoursej <= n
* prevCoursej != nextCoursej
* All the pairs [prevCoursej, nextCoursej] are unique.
* time.length == n
* 1 <= time[i] <= 10^4
* The given graph is a directed acyclic graph.
*
*/
pub struct Solution {}
// problem: https://leetcode.com/problems/parallel-courses-iii/
// discuss: https://leetcode.com/problems/parallel-courses-iii/discuss/?currentPage=1&orderBy=most_votes&query=
// submission codes start here
impl Solution {
pub fn minimum_time(n: i32, relations: Vec<Vec<i32>>, time: Vec<i32>) -> i32 {
0
}
}
// submission codes end
#[cfg(test)]
mod tests {
use super::*;
#[test]
#[ignore]
fn test_2050_example_1() {
let n = 3;
let relations = vec![vec![1, 3], vec![2, 3]];
let time = vec![3, 2, 5];
let result = 8;
assert_eq!(Solution::minimum_time(n, relations, time), result);
}
#[test]
#[ignore]
fn test_2050_example_2() {
let n = 5;
let relations = vec![vec![1, 5], vec![2, 5], vec![3, 5], vec![3, 4], vec![4, 5]];
let time = vec![1, 2, 3, 4, 5];
let result = 12;
assert_eq!(Solution::minimum_time(n, relations, time), result);
}
}
// Accepted solution for LeetCode #2050: Parallel Courses III
function minimumTime(n: number, relations: number[][], time: number[]): number {
const g: number[][] = Array(n)
.fill(0)
.map(() => []);
const indeg: number[] = Array(n).fill(0);
for (const [a, b] of relations) {
g[a - 1].push(b - 1);
++indeg[b - 1];
}
const q: number[] = [];
const f: number[] = Array(n).fill(0);
let ans: number = 0;
for (let i = 0; i < n; ++i) {
if (indeg[i] === 0) {
q.push(i);
f[i] = time[i];
ans = Math.max(ans, f[i]);
}
}
while (q.length > 0) {
const i = q.shift()!;
for (const j of g[i]) {
f[j] = Math.max(f[j], f[i] + time[j]);
ans = Math.max(ans, f[j]);
if (--indeg[j] === 0) {
q.push(j);
}
}
}
return ans;
}
Use this to step through a reusable interview workflow for this problem.
Pure recursion explores every possible choice at each step. With two choices per state (take or skip), the decision tree has 2ⁿ leaves. The recursion stack uses O(n) space. Many subproblems are recomputed exponentially many times.
Each cell in the DP table is computed exactly once from previously solved subproblems. The table dimensions determine both time and space. Look for the state variables — each unique combination of state values is one cell. Often a rolling array can reduce space by one dimension.
Review these before coding to avoid predictable interview regressions.
Wrong move: Loop endpoints miss first/last candidate.
Usually fails on: Fails on minimal arrays and exact-boundary answers.
Fix: Re-derive loops from inclusive/exclusive ranges before coding.
Wrong move: An incomplete state merges distinct subproblems and caches incorrect answers.
Usually fails on: Correctness breaks on cases that differ only in hidden state.
Fix: Define state so each unique subproblem maps to one DP cell.