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Krishna Pankhania
Krishna Pankhania

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Mastering JavaScript Sorting: 4 Essential Exercises for Job Interviews with Examples

Introduction:

In the fast-paced world of programming interviews, JavaScript skills play a crucial role. Sorting algorithms are a common topic that interviewers love to explore. To help you ace your JavaScript interviews, here are 3 essential sorting exercises along with sample solutions.

1: Bubble Sort Basics:

Exercise: Implement the Bubble Sort algorithm in JavaScript and explain its time complexity.

Sample Solution:

function bubbleSort(arr) {
  let n = arr.length;

  // Outer loop for each pass
  for (let i = 0; i < n - 1; i++) {
    // Inner loop for pairwise comparisons
    for (let j = 0; j < n - i - 1; j++) {
      // Swap if the element found is greater than the next element
      if (arr[j] > arr[j + 1]) {
        let temp = arr[j];
        arr[j] = arr[j + 1];
        arr[j + 1] = temp;
      }
    }
  }
  return arr;
}
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2: Merge Sort Mastery:

Exercise: Write a JavaScript function to perform Merge Sort and discuss its advantages over other sorting algorithms.

Sample Solution:

<!-- Exercise: Write a JavaScript function to perform Merge Sort and discuss its advantages over other sorting algorithms. -->

function mergeSort(arr) {
  if (arr.length <= 1) return arr;

  // Split the array into halves
  const middle = Math.floor(arr.length / 2);
  const left = arr.slice(0, middle);
  const right = arr.slice(middle);

  // Recursively apply mergeSort to both halves and merge them
  return merge(mergeSort(left), mergeSort(right));
}

function merge(left, right) {
  let result = [];
  let leftIndex = 0;
  let rightIndex = 0;

  // Merge the two sorted arrays
  while (leftIndex < left.length && rightIndex < right.length) {
    if (left[leftIndex] < right[rightIndex]) {
      result.push(left[leftIndex]);
      leftIndex++;
    } else {
      result.push(right[rightIndex]);
      rightIndex++;
    }
  }

  // Add remaining elements from both arrays
  return result.concat(left.slice(leftIndex)).concat(right.slice(rightIndex));
}
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3: Quick Sort Challenge:

Exercise: Implement the Quick Sort algorithm in JavaScript, emphasizing its efficiency and partitioning strategy.

Sample Solution:

function quickSort(arr) {
  if (arr.length <= 1) return arr;

  // Choose the pivot (last element in this case)
  const pivot = arr[arr.length - 1];
  const left = [];
  const right = [];

  // Partition the array into elements smaller than pivot and larger than pivot
  for (let i = 0; i < arr.length - 1; i++) {
    if (arr[i] < pivot) {
      left.push(arr[i]);
    } else {
      right.push(arr[i]);
    }
  }

  // Recursively apply quickSort to both partitions and concatenate them with pivot
  return [...quickSort(left), pivot, ...quickSort(right)];
}
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4: Selection Sort Unveiled:

Exercise: Write a JavaScript function for Selection Sort and discuss its simplicity compared to other algorithms.

Sample Solution:

function selectionSort(arr) {
  const n = arr.length;

  // Traverse through all array elements
  for (let i = 0; i < n - 1; i++) {
    // Find the minimum element in the unsorted part of the array
    let minIndex = i;

    for (let j = i + 1; j < n; j++) {
      if (arr[j] < arr[minIndex]) {
        minIndex = j;
      }
    }

    // Swap the found minimum element with the first element
    if (minIndex !== i) {
      let temp = arr[i];
      arr[i] = arr[minIndex];
      arr[minIndex] = temp;
    }
  }

  return arr;
}
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