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Adding dynamic programming solution for unique paths problem #2992

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122 changes: 122 additions & 0 deletions dynamic_programming/unique_paths.cpp
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Original file line number Diff line number Diff line change
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/**
* @file
* @brief Implementation of Unique Paths problem using Dynamic Programming.
* @details
* A robot is located at the top-left corner of an m ×ばつ n grid.
* The robot can move either down or right at any point in time.
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@realstealthninja realstealthninja Sep 4, 2025

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could add a brief comparison between memoization and tabulation?

* This program computes the total number of unique paths to reach
* the bottom-right corner.
*
* Approaches:
* - **Memoization (Top-Down)**: Recursively explores solutions while
* storing intermediate results in a cache (`memoization_table`) to avoid redundant
* computation. Typically more intuitive and easy to write, but
* relies on recursion and has associated call-stack overhead.
*
* - **Tabulation (Bottom-Up)**: Iteratively builds the solution using
* a DP table, starting from the base cases and filling up the table.
* Offers consistent performance without recursion overhead and
* is generally more space-efficient when optimized.
*
* @see https://leetcode.com/problems/unique-paths/
*/

#include <iostream>
#include <vector>
#include <cassert>

/**
* @namespace dynamic_programming
* @brief Dynamic Programming algorithms
*/
namespace dynamic_programming {

/**
* @class UniquePathsSolver
* @brief Solves the Unique Paths problem using both memoization and tabulation.
*/
class UniquePathsSolver {
private:
std::vector<std::vector<int>> memoization_table; ///< Memoization table
int m, n;

/**
* @brief Bottom-up Tabulation solution.
* @return int Number of unique paths from (0, 0) to (m-1, n-1)
*/
int solveTabulation() {
std::vector<std::vector<int>> table(m, std::vector<int>(n, 0));

for (int i = 0; i < m; i++) table[i][n - 1] = 1; ///< last column
for (int j = 0; j < n; j++) table[m - 1][j] = 1; ///< last row

for (int i = m - 2; i >= 0; i--) {
for (int j = n - 2; j >= 0; j--) {
table[i][j] = table[i + 1][j] + table[i][j + 1];
}
}
return table[0][0];
}

public:
/**
* @brief Constructor initializes dimensions and memoization table
*/
UniquePathsSolver(int rows, int cols) : m(rows), n(cols) {
memoization_table.assign(m, std::vector<int>(n, -1));
}

/**
* @brief Get number of unique paths using Memoization (Top-Down)
*/
int uniquePathsMemo(int i = 0, int j = 0) {
if (i >= m || j >= n) return 0;
if (i == m - 1 && j == n - 1) return 1;
if (memoization_table.at(i).at(j) != -1) return memoization_table.at(i).at(j);

memoization_table.at(i).at(j) =
uniquePathsMemo(i + 1, j) + uniquePathsMemo(i, j + 1);
return memoization_table.at(i).at(j);
}

/**
* @brief Get number of unique paths using Tabulation (Bottom-Up)
*/
int uniquePathsTabulation() { return solveTabulation(); }
};

} // namespace dynamic_programming

/**
* @brief Self-test implementations
*/
static void test() {
using namespace dynamic_programming;

UniquePathsSolver solver1(3, 7);
assert(solver1.uniquePathsMemo() == 28);
assert(solver1.uniquePathsTabulation() == 28);

UniquePathsSolver solver2(3, 2);
assert(solver2.uniquePathsMemo() == 3);
assert(solver2.uniquePathsTabulation() == 3);

UniquePathsSolver solver3(1, 1);
assert(solver3.uniquePathsMemo() == 1);
assert(solver3.uniquePathsTabulation() == 1);

UniquePathsSolver solver4(2, 2);
assert(solver4.uniquePathsMemo() == 2);
assert(solver4.uniquePathsTabulation() == 2);

std::cout << "All tests have successfully passed!\n";
}

/**
* @brief Main function
* @returns 0 on successful execution
*/
int main() {
test(); // run self-tests
return 0;
}

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