Complete Cmopetitive-Coding2

[paridhimalviya]

Problem 1 - Two elements sum to target
Problem 2 - : 0-1 Knapsack Problem

[super30admin]

Interview Problem : Two elements sum to target (TwoSum.swift)

Your solution is efficient and uses a good approach with a hash map to achieve O(n) time complexity. However, there are a few areas for improvement:

1. The problem expects the return type to be an array of integers (int[] in Java), but your function returns a tuple (Int, Int). You should return an array [Int] to match the problem requirements.
2. Building the dictionary in a separate pass might lead to overwriting duplicate numbers. For example, if the array has duplicates like [3, 3] and target 6, your dictionary will store the last index of 3 (index 1). Then when j=0, the complement is 3 and map[3] is 1 (which is not equal to j=0), so it returns (0,1). This works, but if the solution involved an earlier duplicate, it might not be found. However, the problem states there is exactly one solution, so this is acceptable. But note: if you build the dictionary in the same pass as the check, you can avoid this potential issue and also do it in one iteration.
3. Consider optimizing by doing the check in a single pass: while iterating, for each number, check if the complement is already in the dictionary. If not, add the current number to the dictionary. This way, you avoid the case where the complement might be the current element itself (since it hasn't been added yet). This also handles duplicates better and is more efficient (one pass instead of two).
4. The code includes a lot of comments and example code for other problems (like 3Sum), which is not relevant to this solution. It's good to think about related problems, but for clarity, focus on the current problem.

Here's an improved version in Swift:

func twoSum(_ nums: [Int], _ target: Int) -> [Int] {
    var map = [Int: Int]()
    for (index, num) in nums.enumerated() {
        let complement = target - num
        if let complementIndex = map[complement] {
            return [complementIndex, index]
        }
        map[num] = index
    }
    return []
}

VERDICT: PASS

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Interview Problem: 0-1 Knapsack Problem (0-1Knapsack.swift)

Your solution demonstrates a good understanding of the problem and both the recursive and DP approaches. Here are some strengths and areas for improvement:

Strengths:

• You correctly identified that greedy doesn't work and implemented the exhaustive recursive approach.
• The DP solution is correctly implemented with a 2D DP table, and the logic for filling the table is accurate.
• Code comments are helpful and explain your thought process.

Areas for Improvement:

1. Hardcoded Arrays: The profit and weight arrays are hardcoded as properties of the class. It would be better to pass these as parameters to the methods to make the code more flexible and reusable. For example, findMaximumProfitUsingDP() should take profit, weight, and capacity as arguments.
2. Initializer Calls: The initializer calls both the recursive helper and DP method. This might be unnecessary and could lead to confusion. Consider having a separate test method or main function to demonstrate usage.
3. Recursive Helper Parameters: The recursive helper function helper(profit:weight:capacity:i:totalProfit:) uses totalProfit as a parameter, which accumulates the profit. This is correct, but note that the recursive approach is inefficient for large inputs due to exponential time complexity. You might want to mention that it's only for educational purposes.
4. Edge Cases: Ensure your solution handles edge cases, such as zero capacity or empty arrays. The current DP solution should handle these since the DP table is initialized with zeros.
5. Variable Naming: Use more descriptive variable names. For example, in the DP method, m and n are clear (number of items and capacity), but in the recursive method, i could be renamed to index for clarity.
6. Efficiency: The DP solution uses O(m*n) space. If you want to optimize further, you could reduce the space complexity to O(n) by using a 1D array for the DP table, since each row only depends on the previous row.

Overall, your solution is correct and efficient for the DP part. With minor adjustments to improve flexibility and code structure, it would be even better.

VERDICT: PASS