Check if Two Chessboard Squares Have the Same Color

Check if Two Chessboard Squares Have the Same Color - Problem

Math String Easy

Chess Square Color Checker

Given two chessboard coordinates like "a1" and "h3", determine if they represent squares of the same color on a standard 8×8 chessboard.

🏁 Goal: Return true if both squares have the same color (both black or both white), false otherwise.

📝 Input: Two strings representing valid chessboard coordinates
• First character: column letter ('a' to 'h')
• Second character: row number ('1' to '8')

📤 Output: Boolean indicating if squares have the same color

Fun fact: On a chessboard, square 'a1' is always a dark square, and colors alternate in a checkerboard pattern!

Input & Output

example_1.py — Basic Different Colors

$ Input: coordinate1 = "a1", coordinate2 = "c3"

› Output: true

💡 Note: Square 'a1': column a(1) + row 1 = 2 (even) → white. Square 'c3': column c(3) + row 3 = 6 (even) → white. Both are white, so return true.

example_2.py — Different Colors

$ Input: coordinate1 = "a1", coordinate2 = "h3"

› Output: false

💡 Note: Square 'a1': column a(1) + row 1 = 2 (even) → white. Square 'h3': column h(8) + row 3 = 11 (odd) → black. Different colors, so return false.

example_3.py — Same Square

$ Input: coordinate1 = "a1", coordinate2 = "a1"

› Output: true

💡 Note: Both coordinates refer to the same square 'a1', so they obviously have the same color. Return true.

Constraints

coordinate1.length == coordinate2.length == 2
First character is a lowercase letter from 'a' to 'h'
Second character is a digit from '1' to '8'
Coordinates always represent valid chessboard squares

Visualization

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Understanding the Visualization

Coordinate System

Columns a-h map to 1-8, rows are already 1-8

Sum Calculation

Add column number and row number for each square

Color Rule

Even sum = white square, odd sum = black square

Comparison

Same parity means same color

Key Takeaway

🎯 Key Insight: Chessboard colors follow a simple mathematical pattern - the sum of coordinate numbers determines the color, making this an O(1) problem!

Asked in

a Amazon 15 G Google 12 ⊞ Microsoft 8 f Meta 6

The optimal solution uses coordinate arithmetic to determine square colors. Convert each coordinate to numbers, sum them, and check if the parity (even/odd) matches. Key insight: Chessboard colors alternate based on the sum of coordinates - no need to simulate the entire board pattern!

Common Approaches

Approach	Time	Space	Notes
✓ Coordinate Mapping Approach	O(1)	O(1)	Convert coordinates to positions and check color pattern

Coordinate Mapping Approach — Algorithm Steps

Parse first coordinate to get column (a-h) and row (1-8) numbers
Parse second coordinate similarly
For each coordinate, calculate if (column + row) is even or odd
Compare the parity (even/odd) of both coordinates

Visualization

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Step-by-Step Walkthrough

Parse Coordinates

Convert letter to number (a=1, b=2, ..., h=8)

Calculate Sum

Add column number and row number

Check Parity

Even sum = white, odd sum = black

Compare

Return true if both have same parity

Code -

solution.c — C

#include <stdio.h>
#include <stdbool.h>

int getColor(char* coord) {
    int col = coord[0] - 'a' + 1; // Convert 'a'-'h' to 1-8
    int row = coord[1] - '0';     // Convert '1'-'8' to 1-8
    return (col + row) % 2;       // 0 for one color, 1 for another
}

bool checkTwoChessboards(char* coordinate1, char* coordinate2) {
    return getColor(coordinate1) == getColor(coordinate2);
}

int main() {
    char coord1[3], coord2[3];
    scanf("%s %s", coord1, coord2);
    printf("%s\n", checkTwoChessboards(coord1, coord2) ? "true" : "false");
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(1)

Constant time operations regardless of input

✓ Linear Growth

Space Complexity

O(1)

Only using a few variables for calculations

✓ Linear Space

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Medium Frequency

~8 min Avg. Time

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Smart Actions

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Input & Output

Constraints

Visualization

Related Problems

Common Approaches

Coordinate Mapping Approach — Algorithm Steps

Visualization

Code -

Time & Space Complexity

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