Reach a Number - Practice Coding Problems

Reach a Number - Problem

You are standing at position 0 on an infinite number line. There is a destination at position target.

You can make some number of moves numMoves so that:

On each move, you can either go left or right.
During the i^th move (starting from i == 1 to i == numMoves), you take i steps in the chosen direction.

Given the integer target, return the minimum number of moves required (i.e., the minimum numMoves) to reach the destination.

Input & Output

Example 1 — Basic Case

$ Input: target = 3

› Output: 2

💡 Note: Move 1: go right 1 step (position = 1). Move 2: go right 2 steps (position = 3). Total: 2 moves to reach target 3.

Example 2 — Requires Backtracking

$ Input: target = 2

› Output: 3

💡 Note: Move 1: go right 1 step (position = 1). Move 2: go right 2 steps (position = 3). Move 3: go left 3 steps (position = 0). But we can do better: Move 1: go right 1 step, Move 2: go left 2 steps (position = -1), Move 3: go right 3 steps (position = 2). Total: 3 moves.

Example 3 — Negative Target

$ Input: target = -2

› Output: 3

💡 Note: Same as target = 2 due to symmetry. We can reach -2 by going left instead of right in the same number of moves.

Constraints

-10⁹ ≤ target ≤ 10⁹
target ≠ 0

Visualization

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Understanding the Visualization

Starting Position

Begin at position 0 on number line

Move Pattern

Each move i takes exactly i steps, choose left or right

Goal

Find minimum moves to reach target position

Key Takeaway

🎯 Key Insight: Use mathematical analysis of cumulative sums and parity to avoid exponential search

Asked in

G Google 25 M Microsoft 18 a Amazon 12

The key insight is recognizing that we can flip any rightward move to leftward by changing its sign. The optimal approach uses mathematical analysis: find the minimum moves where the sum equals or exceeds the target, then check if we can adjust by flipping moves. Time: O(√n), Space: O(1)

Common Approaches

Approach	Time	Space	Notes
✓ Brute Force Simulation	O(2ⁿ)	O(n)	Try all possible left/right combinations using recursion
Mathematical Approach	O(√n)	O(1)	Use mathematical insight about sum patterns and parity

Brute Force Simulation — Algorithm Steps

Start at position 0 with move number 1
For each move, try both left (-i) and right (+i)
Recursively explore until target is reached
Return minimum moves among all successful paths

Visualization

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Step-by-Step Walkthrough

Start

Begin at position 0, first move is size 1

Branch

For each move, try both left and right directions

Explore

Recursively continue until target is reached

Code -

solution.c — C

#include <stdio.h>
#include <stdlib.h>
#include <limits.h>

int abs_val(int x) {
    return x < 0 ? -x : x;
}

int min(int a, int b) {
    return a < b ? a : b;
}

int dfs(int pos, int move, int target) {
    if (pos == target) {
        return 0;
    }
    if (move > abs_val(target) + 10) { // Pruning
        return INT_MAX;
    }
    
    // Try right (+move)
    int right = dfs(pos + move, move + 1, target);
    // Try left (-move)
    int left = dfs(pos - move, move + 1, target);
    
    if (right == INT_MAX && left == INT_MAX) {
        return INT_MAX;
    }
    
    return 1 + min(right, left);
}

int solution(int target) {
    return dfs(0, 1, target);
}

int main() {
    int target;
    scanf("%d", &target);
    int result = solution(target);
    printf("%d\n", result);
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(2ⁿ)

Each move has 2 choices (left/right), creating 2^n possible paths

✓ Linear Growth

Space Complexity

O(n)

Recursion stack depth proportional to number of moves

⚡ Linearithmic Space

28.0K Views

Medium Frequency

~25 min Avg. Time

850 Likes

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Smart Actions

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Input & Output

Constraints

Visualization

Related Problems

Common Approaches

Brute Force Simulation — Algorithm Steps

Visualization

Code -

Time & Space Complexity

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