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 hoursBefore, the number of hours you have to travel to your meeting. To arrive at your meeting, you have to travel through n roads. The road lengths are given as an integer array dist of length n, where dist[i] describes the length of the ith road in kilometers. In addition, you are given an integer speed, which is the speed (in km/h) you will travel at.
After you travel road i, you must rest and wait for the next integer hour before you can begin traveling on the next road. Note that you do not have to rest after traveling the last road because you are already at the meeting.
1.4 hours, you must wait until the 2 hour mark before traveling the next road. If traveling a road takes exactly 2 hours, you do not need to wait.However, you are allowed to skip some rests to be able to arrive on time, meaning you do not need to wait for the next integer hour. Note that this means you may finish traveling future roads at different hour marks.
1.4 hours and traveling the second road takes 0.6 hours. Skipping the rest after the first road will mean you finish traveling the second road right at the 2 hour mark, letting you start traveling the third road immediately.Return the minimum number of skips required to arrive at the meeting on time, or -1 if it is impossible.
Example 1:
Input: dist = [1,3,2], speed = 4, hoursBefore = 2 Output: 1 Explanation: Without skipping any rests, you will arrive in (1/4 + 3/4) + (3/4 + 1/4) + (2/4) = 2.5 hours. You can skip the first rest to arrive in ((1/4 + 0) + (3/4 + 0)) + (2/4) = 1.5 hours. Note that the second rest is shortened because you finish traveling the second road at an integer hour due to skipping the first rest.
Example 2:
Input: dist = [7,3,5,5], speed = 2, hoursBefore = 10 Output: 2 Explanation: Without skipping any rests, you will arrive in (7/2 + 1/2) + (3/2 + 1/2) + (5/2 + 1/2) + (5/2) = 11.5 hours. You can skip the first and third rest to arrive in ((7/2 + 0) + (3/2 + 0)) + ((5/2 + 0) + (5/2)) = 10 hours.
Example 3:
Input: dist = [7,3,5,5], speed = 1, hoursBefore = 10 Output: -1 Explanation: It is impossible to arrive at the meeting on time even if you skip all the rests.
Constraints:
n == dist.length1 <= n <= 10001 <= dist[i] <= 1051 <= speed <= 1061 <= hoursBefore <= 107Problem summary: You are given an integer hoursBefore, the number of hours you have to travel to your meeting. To arrive at your meeting, you have to travel through n roads. The road lengths are given as an integer array dist of length n, where dist[i] describes the length of the ith road in kilometers. In addition, you are given an integer speed, which is the speed (in km/h) you will travel at. After you travel road i, you must rest and wait for the next integer hour before you can begin traveling on the next road. Note that you do not have to rest after traveling the last road because you are already at the meeting. For example, if traveling a road takes 1.4 hours, you must wait until the 2 hour mark before traveling the next road. If traveling a road takes exactly 2 hours, you do not need to wait. However, you are allowed to skip some rests to be able to arrive on time, meaning you do not need to
Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.
Pattern signal: Array · Dynamic Programming
[1,3,2] 4 2
[7,3,5,5] 2 10
[7,3,5,5] 1 10
minimum-speed-to-arrive-on-time)minimum-time-to-finish-the-race)Source-backed implementations are provided below for direct study and interview prep.
// Accepted solution for LeetCode #1883: Minimum Skips to Arrive at Meeting On Time
class Solution {
public int minSkips(int[] dist, int speed, int hoursBefore) {
int n = dist.length;
double[][] f = new double[n + 1][n + 1];
for (int i = 0; i <= n; i++) {
Arrays.fill(f[i], 1e20);
}
f[0][0] = 0;
double eps = 1e-8;
for (int i = 1; i <= n; ++i) {
for (int j = 0; j <= i; ++j) {
if (j < i) {
f[i][j] = Math.min(
f[i][j], Math.ceil(f[i - 1][j]) + 1.0 * dist[i - 1] / speed - eps);
}
if (j > 0) {
f[i][j] = Math.min(f[i][j], f[i - 1][j - 1] + 1.0 * dist[i - 1] / speed);
}
}
}
for (int j = 0; j <= n; ++j) {
if (f[n][j] <= hoursBefore + eps) {
return j;
}
}
return -1;
}
}
// Accepted solution for LeetCode #1883: Minimum Skips to Arrive at Meeting On Time
func minSkips(dist []int, speed int, hoursBefore int) int {
n := len(dist)
f := make([][]float64, n+1)
for i := range f {
f[i] = make([]float64, n+1)
for j := range f[i] {
f[i][j] = 1e20
}
}
f[0][0] = 0
eps := 1e-8
for i := 1; i <= n; i++ {
for j := 0; j <= i; j++ {
if j < i {
f[i][j] = math.Min(f[i][j], math.Ceil(f[i-1][j]+float64(dist[i-1])/float64(speed)-eps))
}
if j > 0 {
f[i][j] = math.Min(f[i][j], f[i-1][j-1]+float64(dist[i-1])/float64(speed))
}
}
}
for j := 0; j <= n; j++ {
if f[n][j] <= float64(hoursBefore) {
return j
}
}
return -1
}
# Accepted solution for LeetCode #1883: Minimum Skips to Arrive at Meeting On Time
class Solution:
def minSkips(self, dist: List[int], speed: int, hoursBefore: int) -> int:
n = len(dist)
f = [[inf] * (n + 1) for _ in range(n + 1)]
f[0][0] = 0
eps = 1e-8
for i, x in enumerate(dist, 1):
for j in range(i + 1):
if j < i:
f[i][j] = min(f[i][j], ceil(f[i - 1][j] + x / speed - eps))
if j:
f[i][j] = min(f[i][j], f[i - 1][j - 1] + x / speed)
for j in range(n + 1):
if f[n][j] <= hoursBefore + eps:
return j
return -1
// Accepted solution for LeetCode #1883: Minimum Skips to Arrive at Meeting On Time
/**
* [1883] Minimum Skips to Arrive at Meeting On Time
*
* You are given an integer hoursBefore, the number of hours you have to travel to your meeting. To arrive at your meeting, you have to travel through n roads. The road lengths are given as an integer array dist of length n, where dist[i] describes the length of the i^th road in kilometers. In addition, you are given an integer speed, which is the speed (in km/h) you will travel at.
* After you travel road i, you must rest and wait for the next integer hour before you can begin traveling on the next road. Note that you do not have to rest after traveling the last road because you are already at the meeting.
*
* For example, if traveling a road takes 1.4 hours, you must wait until the 2 hour mark before traveling the next road. If traveling a road takes exactly 2 hours, you do not need to wait.
*
* However, you are allowed to skip some rests to be able to arrive on time, meaning you do not need to wait for the next integer hour. Note that this means you may finish traveling future roads at different hour marks.
*
* For example, suppose traveling the first road takes 1.4 hours and traveling the second road takes 0.6 hours. Skipping the rest after the first road will mean you finish traveling the second road right at the 2 hour mark, letting you start traveling the third road immediately.
*
* Return the minimum number of skips required to arrive at the meeting on time, or -1 if it is impossible.
*
* Example 1:
*
* Input: dist = [1,3,2], speed = 4, hoursBefore = 2
* Output: 1
* Explanation:
* Without skipping any rests, you will arrive in (1/4 + 3/4) + (3/4 + 1/4) + (2/4) = 2.5 hours.
* You can skip the first rest to arrive in ((1/4 + <u>0</u>) + (3/4 + 0)) + (2/4) = 1.5 hours.
* Note that the second rest is shortened because you finish traveling the second road at an integer hour due to skipping the first rest.
*
* Example 2:
*
* Input: dist = [7,3,5,5], speed = 2, hoursBefore = 10
* Output: 2
* Explanation:
* Without skipping any rests, you will arrive in (7/2 + 1/2) + (3/2 + 1/2) + (5/2 + 1/2) + (5/2) = 11.5 hours.
* You can skip the first and third rest to arrive in ((7/2 + <u>0</u>) + (3/2 + 0)) + ((5/2 + <u>0</u>) + (5/2)) = 10 hours.
*
* Example 3:
*
* Input: dist = [7,3,5,5], speed = 1, hoursBefore = 10
* Output: -1
* Explanation: It is impossible to arrive at the meeting on time even if you skip all the rests.
*
*
* Constraints:
*
* n == dist.length
* 1 <= n <= 1000
* 1 <= dist[i] <= 10^5
* 1 <= speed <= 10^6
* 1 <= hoursBefore <= 10^7
*
*/
pub struct Solution {}
// problem: https://leetcode.com/problems/minimum-skips-to-arrive-at-meeting-on-time/
// discuss: https://leetcode.com/problems/minimum-skips-to-arrive-at-meeting-on-time/discuss/?currentPage=1&orderBy=most_votes&query=
// submission codes start here
impl Solution {
pub fn min_skips(dist: Vec<i32>, speed: i32, hours_before: i32) -> i32 {
0
}
}
// submission codes end
#[cfg(test)]
mod tests {
use super::*;
#[test]
#[ignore]
fn test_1883_example_1() {
let dist = vec![1, 3, 2];
let speed = 4;
let hours_before = 2;
let result = 1;
assert_eq!(Solution::min_skips(dist, speed, hours_before), result);
}
#[test]
#[ignore]
fn test_1883_example_2() {
let dist = vec![7, 3, 5, 5];
let speed = 2;
let hours_before = 10;
let result = 2;
assert_eq!(Solution::min_skips(dist, speed, hours_before), result);
}
#[test]
#[ignore]
fn test_1883_example_3() {
let dist = vec![7, 3, 5, 5];
let speed = 1;
let hours_before = 10;
let result = -1;
assert_eq!(Solution::min_skips(dist, speed, hours_before), result);
}
}
// Accepted solution for LeetCode #1883: Minimum Skips to Arrive at Meeting On Time
function minSkips(dist: number[], speed: number, hoursBefore: number): number {
const n = dist.length;
const f = Array.from({ length: n + 1 }, () => Array.from({ length: n + 1 }, () => Infinity));
f[0][0] = 0;
const eps = 1e-8;
for (let i = 1; i <= n; ++i) {
for (let j = 0; j <= i; ++j) {
if (j < i) {
f[i][j] = Math.min(f[i][j], Math.ceil(f[i - 1][j] + dist[i - 1] / speed - eps));
}
if (j) {
f[i][j] = Math.min(f[i][j], f[i - 1][j - 1] + dist[i - 1] / speed);
}
}
}
for (let j = 0; j <= n; ++j) {
if (f[n][j] <= hoursBefore + eps) {
return j;
}
}
return -1;
}
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.