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* [N Queens All Solution Optimised](https://github.com/TheAlgorithms/C-Plus-Plus/blob/master/backtracking/n_queens_all_solution_optimised.cpp) * [N Queens All Solution Optimised](https://github.com/TheAlgorithms/C-Plus-Plus/blob/master/backtracking/n_queens_all_solution_optimised.cpp)
* [Nqueen Print All Solutions](https://github.com/TheAlgorithms/C-Plus-Plus/blob/master/backtracking/nqueen_print_all_solutions.cpp) * [Nqueen Print All Solutions](https://github.com/TheAlgorithms/C-Plus-Plus/blob/master/backtracking/nqueen_print_all_solutions.cpp)
* [Rat Maze](https://github.com/TheAlgorithms/C-Plus-Plus/blob/master/backtracking/rat_maze.cpp) * [Rat Maze](https://github.com/TheAlgorithms/C-Plus-Plus/blob/master/backtracking/rat_maze.cpp)
* [Subset Sum](https://github.com/TheAlgorithms/C-Plus-Plus/blob/master/backtracking/subset_sum.cpp)
* [Sudoku Solve](https://github.com/TheAlgorithms/C-Plus-Plus/blob/master/backtracking/sudoku_solve.cpp) * [Sudoku Solve](https://github.com/TheAlgorithms/C-Plus-Plus/blob/master/backtracking/sudoku_solve.cpp)
## Bit Manipulation ## Bit Manipulation

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/**
* @file
* @brief Implementation of the [Subset
* Sum](https://en.wikipedia.org/wiki/Subset_sum_problem) problem.
* @details
* We are given an array and a sum value. The algorithm finds all
* the subsets of that array with sum equal to the given sum and return such
* subsets count. This approach will have exponential time complexity.
* @author [Swastika Gupta](https://github.com/Swastyy)
*/
#include <cassert> /// for assert
#include <iostream> /// for IO operations
#include <vector> /// for std::vector
/**
* @namespace backtracking
* @brief Backtracking algorithms
*/
namespace backtracking {
/**
* @namespace Subsets
* @brief Functions for the [Subset
* Sum](https://en.wikipedia.org/wiki/Subset_sum_problem) problem.
*/
namespace subset_sum {
/**
* @brief The main function implements count of subsets
* @param sum is the required sum of any subset
* @param in_arr is the input array
* @returns count of the number of subsets with required sum
*/
uint64_t number_of_subsets(int32_t sum, const std::vector<int32_t> &in_arr) {
int32_t nelement = in_arr.size();
uint64_t count_of_subset = 0;
for (int32_t i = 0; i < (1 << (nelement)); i++) {
int32_t check = 0;
for (int32_t j = 0; j < nelement; j++) {
if (i & (1 << j)) {
check += (in_arr[j]);
}
}
if (check == sum) {
count_of_subset++;
}
}
return count_of_subset;
}
} // namespace subset_sum
} // namespace backtracking
/**
* @brief Test implementations
* @returns void
*/
static void test() {
// 1st test
std::cout << "1st test ";
std::vector<int32_t> array1 = {-7, -3, -2, 5, 8}; // input array
assert(backtracking::subset_sum::number_of_subsets(0, array1) ==
2); // first argument in subset_sum function is the required sum and
// second is the input array
std::cout << "passed" << std::endl;
// 2nd test
std::cout << "2nd test ";
std::vector<int32_t> array2 = {1, 2, 3, 3};
assert(backtracking::subset_sum::number_of_subsets(6, array2) ==
3); // here we are expecting 3 subsets which sum up to 6 i.e.
// {(1,2,3),(1,2,3),(3,3)}
std::cout << "passed" << std::endl;
// 3rd test
std::cout << "3rd test ";
std::vector<int32_t> array3 = {1, 1, 1, 1};
assert(backtracking::subset_sum::number_of_subsets(1, array3) ==
4); // here we are expecting 4 subsets which sum up to 1 i.e.
// {(1),(1),(1),(1)}
std::cout << "passed" << std::endl;
// 4th test
std::cout << "4th test ";
std::vector<int32_t> array4 = {3, 3, 3, 3};
assert(backtracking::subset_sum::number_of_subsets(6, array4) ==
6); // here we are expecting 6 subsets which sum up to 6 i.e.
// {(3,3),(3,3),(3,3),(3,3),(3,3),(3,3)}
std::cout << "passed" << std::endl;
// Test 5
std::cout << "5th test ";
std::vector<int32_t> array5 = {};
assert(backtracking::subset_sum::number_of_subsets(6, array5) ==
0); // here we are expecting 0 subsets which sum up to 6 i.e. we
// cannot select anything from an empty array
std::cout << "passed" << std::endl;
}
/**
* @brief Main function
* @returns 0 on exit
*/
int main() {
test(); // run self-test implementations
return 0;
}