What is the main goal of the Partition Equal Subset Sum problem?
To determine if a given list of positive integers can be split into two subsets with equal sums.
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beginner
Why do we check if the total sum of the array is even before proceeding?
Because if the total sum is odd, it is impossible to split the array into two equal sum subsets.
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intermediate
What does the dynamic programming table represent in the Partition Equal Subset Sum solution?
It represents whether a subset with a certain sum is possible using the first few elements of the array.
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intermediate
In the DP approach, what does dp[i][j] = true mean?
It means that using the first i elements, it is possible to form a subset with sum j.
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intermediate
What is the time complexity of the dynamic programming solution for Partition Equal Subset Sum?
O(n * sum/2), where n is the number of elements and sum is the total sum of the array.
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What should you do first when solving Partition Equal Subset Sum?
ASort the array
BFind the maximum element
CCheck if the total sum is even
DCalculate the product of all elements
✗ Incorrect
Checking if the total sum is even helps decide if partitioning is possible at all.
If the total sum of the array is 15, can it be partitioned into two equal subsets?
AYes, always
BNo, because 15 is odd
CYes, if the array has duplicates
DNo, unless the array is sorted
✗ Incorrect
An odd total sum means equal partition is impossible.
In the DP table, what does a 'true' value at dp[i][j] indicate?
ASubset sum j is possible with first i elements
BSum j is greater than total sum
CSubset sum j is not possible with first i elements
DElement i is equal to j
✗ Incorrect
True means a subset with sum j can be formed using first i elements.
What is the target sum we try to find a subset for in this problem?
ASum of the smallest element
BTotal sum of the array
CSum of the largest element
DHalf of the total sum
✗ Incorrect
We try to find a subset with sum equal to half the total sum.
Which technique is commonly used to solve Partition Equal Subset Sum efficiently?
ADynamic programming
BGreedy algorithm
CDivide and conquer
DBacktracking without memoization
✗ Incorrect
Dynamic programming efficiently checks subset sums up to half the total sum.
Explain the steps to solve the Partition Equal Subset Sum problem using dynamic programming.
Start by checking the sum, then build a table to track possible sums.
You got /5 concepts.
Describe what the DP table represents and how it helps in solving the Partition Equal Subset Sum problem.
Think of the table as a map of which sums can be made with which elements.
You got /5 concepts.
Practice
(1/5)
1. What does the Partition Equal Subset Sum problem ask you to find?
easy
A. If the array contains any duplicate elements
B. If the array is sorted in ascending order
C. If the array can be split into two subsets with equal sums
D. If the array contains only positive numbers
Solution
Step 1: Understand the problem statement
The problem asks whether the given array can be divided into two parts where the sum of elements in both parts is the same.
Step 2: Identify the key requirement
We need to check if there exists a subset whose sum is half of the total sum of the array.
Final Answer:
If the array can be split into two subsets with equal sums -> Option C
Quick Check:
Partition Equal Subset Sum = Split array equally [OK]
Hint: Check if total sum is even first to proceed [OK]
Common Mistakes:
Thinking the problem is about sorting
Checking for duplicates instead of sums
Assuming all numbers must be positive
2. Which of the following is the correct way to declare a boolean array in C for dynamic programming in Partition Equal Subset Sum?
easy
A. boolean dp[sum+1];
B. int dp[sum+1];
C. bool dp = new bool[sum+1];
D. bool dp[sum+1];
Solution
Step 1: Identify correct C syntax for boolean arrays
In C, bool is available via stdbool.h and arrays are declared as bool dp[size];.
Step 2: Check options for correctness
bool dp[sum+1]; uses correct syntax. int dp[sum+1]; uses int, which is not boolean. bool dp = new bool[sum+1]; uses Java/C++ style dynamic allocation, not valid in C. boolean dp[sum+1]; uses 'boolean' which is not a C keyword.
Final Answer:
bool dp[sum+1]; -> Option D
Quick Check:
Use bool dp[size]; in C [OK]
Hint: Use stdbool.h and declare bool arrays with bool dp[size]; [OK]
Common Mistakes:
Using 'boolean' instead of 'bool' in C
Trying Java-style dynamic allocation in C
Using int instead of bool for DP array
3. What will be the output of the following code snippet for array nums = {1, 5, 11, 5}?
#include
#include
bool canPartition(int* nums, int numsSize) {
int sum = 0;
for (int i = 0; i < numsSize; i++) sum += nums[i];
if (sum % 2 != 0) return false;
int target = sum / 2;
bool dp[target + 1];
for (int i = 0; i <= target; i++) dp[i] = false;
dp[0] = true;
for (int i = 0; i < numsSize; i++) {
for (int j = target; j >= nums[i]; j--) {
dp[j] = dp[j] || dp[j - nums[i]];
}
}
return dp[target];
}
int main() {
int nums[] = {1, 5, 11, 5};
printf("%d\n", canPartition(nums, 4));
return 0;
}
medium
A. 1
B. 0
C. Compilation error
D. Runtime error
Solution
Step 1: Calculate total sum and check parity
Sum = 1 + 5 + 11 + 5 = 22, which is even, so proceed.
Step 2: Use DP to check subset sum equals 11
The DP array tracks sums achievable. The subset {11} and {1,5,5} both sum to 11, so dp[11] becomes true.
Final Answer:
1 -> Option A
Quick Check:
Subset sum exists = 1 [OK]
Hint: Check if half sum subset exists using DP [OK]
Common Mistakes:
Not checking if total sum is even
Incorrect DP initialization
Looping forward instead of backward in DP
4. Identify the bug in this Partition Equal Subset Sum code snippet:
bool canPartition(int* nums, int numsSize) {
int sum = 0;
for (int i = 0; i < numsSize; i++) sum += nums[i];
if (sum % 2 != 0) return false;
int target = sum / 2;
bool dp[target + 1];
for (int i = 0; i < target; i++) dp[i] = false;
dp[0] = true;
for (int i = 0; i < numsSize; i++) {
for (int j = target; j >= nums[i]; j--) {
dp[j] = dp[j] || dp[j - nums[i]];
}
}
return dp[target];
}
medium
A. Loop initializing dp should run till target inclusive
B. The sum calculation is incorrect
C. The inner loop should run forward, not backward
D. dp[0] should be false initially
Solution
Step 1: Check dp array initialization loop
The loop runs from 0 to target-1, missing dp[target] initialization, which should be set to false.
Step 2: Correct the loop to include target index
Change loop condition to i <= target to initialize all dp elements properly.
Final Answer:
Loop initializing dp should run till target inclusive -> Option A
Quick Check:
Initialize dp array fully including dp[target] [OK]
Hint: Initialize dp array fully including last index [OK]
Common Mistakes:
Forgetting to initialize dp[target]
Running inner loop forward causing wrong results
Setting dp[0] to false instead of true
5. Given an array nums = {2, 2, 3, 5}, which of the following modifications will correctly determine if it can be partitioned into two subsets with equal sum using dynamic programming?
hard
A. Change the DP array to track counts of subsets instead of booleans
B. Use a 2D DP array where dp[i][j] means if sum j is possible with first i elements
C. Sort the array first and then apply the existing 1D DP approach
D. Only check if the largest element is less than half the total sum
Solution
Step 1: Understand limitations of 1D DP for some cases
1D DP works but 2D DP is clearer and handles subset sums by tracking elements used.
Step 2: Use 2D DP where dp[i][j] shows if sum j is possible using first i elements
This approach explicitly considers each element and sum, making it easier to debug and understand.
Step 3: Sorting or counting subsets is not necessary or sufficient
Sorting doesn't affect subset sums. Counting subsets is more complex and not required for yes/no answer.
Final Answer:
Use a 2D DP array where dp[i][j] means if sum j is possible with first i elements -> Option B
Quick Check:
2D DP tracks sums per element [OK]
Hint: Use 2D DP for clear subset sum tracking [OK]
Common Mistakes:
Sorting array expecting it to solve partition
Counting subsets instead of checking existence
Only checking largest element against half sum
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