explanation.md

Results Array Problem - Step-by-Step Explanation

This README provides a step-by-step explanation of the solution to the problem "Results Array" in multiple programming languages, written in a friendly and engaging tone.

Each language follows the same logical flow, but the implementation syntax differs. We'll break it down without showing the full code here. Instead, you’ll find clear and concise explanations of what each part of the code does.

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C++ Code

Steps

1. Input and Initialization:

   • We take a vector of integers (nums) and an integer k as input.
   • A result vector is initialized to store the output values.

2. Sliding Window Iteration:

   • Loop through the array from index 0 to n - k (where n is the size of nums).
   • For each iteration, create a subarray of size k using slicing techniques.

3. Sort the Subarray:

   • Make a copy of the subarray and sort it using C++'s sort function.

4. Consecutive Check:

   • Iterate through the sorted subarray to check if adjacent elements differ by exactly 1.

5. Compare with Original:

   • Ensure the original subarray matches the sorted subarray to confirm it’s already sorted.

6. Result Evaluation:

   • If both conditions (consecutive and sorted) are satisfied, add the maximum value of the subarray to the result vector.
   • Otherwise, append -1.

7. Output the Result:

   • Return the result vector containing the outputs for all possible subarrays.

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Java Code

Steps

1. Input and Initialization:

   • Accept an integer array (nums) and a window size (k) as input.
   • Prepare an output array of size n - k + 1 to store results.

2. Sliding Window Iteration:

   • Use a for loop to iterate through the array, extracting subarrays of size k.
   • Use Arrays.copyOfRange to extract subarrays dynamically.

3. Sort the Subarray:

   • Clone the subarray and sort it using Java’s Arrays.sort() method.

4. Consecutive Check:

   • Traverse the sorted subarray to ensure all adjacent elements differ by 1.

5. Compare with Original:

   • Use Arrays.equals to confirm that the original subarray matches the sorted one.

6. Result Evaluation:

   • If both checks pass, store the maximum value of the subarray in the result array.
   • Otherwise, store -1.

7. Output the Result:

   • Return the result array after completing all iterations.

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JavaScript Code

Steps

1. Input and Initialization:

   • Accept an array nums and a number k as input.
   • Initialize an empty array result to store the final outputs.

2. Sliding Window Iteration:

   • Use a for loop to iterate over all subarrays of size k using JavaScript's slice method.

3. Sort the Subarray:

   • Create a sorted copy of the current subarray using the sort function with a comparator.

4. Consecutive Check:

   • Use a loop to verify if adjacent elements in the sorted subarray differ by 1.

5. Compare with Original:

   • Use the every method to compare the original subarray with the sorted one.

6. Result Evaluation:

   • Push the maximum value of the subarray to result if both checks pass.
   • Otherwise, append -1.

7. Output the Result:

   • Return the result array containing all evaluations.

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Python Code

Steps

1. Input and Initialization:

   • Accept a list nums and an integer k.
   • Initialize an empty list result to store the outputs.

2. Sliding Window Iteration:

   • Use a for loop to iterate from index 0 to n - k.
   • Slice the list to extract subarrays of size k.

3. Sort the Subarray:

   • Use Python’s sorted() function to create a sorted version of the current subarray.

4. Consecutive Check:

   • Use the all() function with a generator expression to verify that all adjacent elements in the sorted subarray differ by 1.

5. Compare with Original:

   • Use the equality operator (==) to check if the original subarray matches the sorted version.

6. Result Evaluation:

   • Append the maximum value of the subarray to result if both conditions are met.
   • Otherwise, append -1.

7. Output the Result:

   • Return the result list containing all outputs.

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Go Code

Steps

1. Input and Initialization:

   • Accept a slice of integers nums and a window size k.
   • Initialize a slice result to store the outputs.

2. Sliding Window Iteration:

   • Use a for loop to iterate through the slice, extracting subarrays of size k.

3. Sort the Subarray:

   • Create a copy of the subarray and sort it using Go's sort.Ints() function.

4. Consecutive Check:

   • Use a for loop to check if adjacent elements in the sorted subarray differ by 1.

5. Compare with Original:

   • Use a helper function to compare the original subarray with the sorted one.

6. Result Evaluation:

   • Append the maximum value of the subarray to result if both checks pass.
   • Otherwise, append -1.

7. Output the Result:

   • Return the result slice containing all evaluations.

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Summary

Each solution uses a sliding window approach to extract subarrays, validates their properties (sorted and consecutive), and evaluates the maximum value or -1 based on the conditions. The solutions are optimized to minimize redundant operations while keeping the code readable and maintainable.

Feel free to explore each implementation and tweak it to suit your preferences! 🚀