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  • Which sorting algorithm is better: Insertion Sort, Selection Sort, or Bubble Sort and why?

    Among the three sorting algorithms, Insertion Sort is generally considered better in terms of performance. This is because Insertion Sort has an average time complexity of O(n^2), which is better than the average time complexity of O(n^2) for both Selection Sort and Bubble Sort. Additionally, Insertion Sort is more efficient when dealing with small datasets, as it has a relatively low overhead. Overall, Insertion Sort is often preferred over Selection Sort and Bubble Sort for its better average time complexity and efficiency with small datasets.

  • What are the advantages and disadvantages of Selection Sort and Insertion Sort?

    Selection Sort has the advantage of being simple to implement and having a consistent time complexity of O(n^2) regardless of the input data. However, it is not efficient for large datasets due to its quadratic time complexity. On the other hand, Insertion Sort is efficient for small datasets and nearly sorted arrays, with a best-case time complexity of O(n). However, it also has a worst-case time complexity of O(n^2) and is not suitable for large datasets.

  • What is the runtime of Insertion Sort Count Sort in the worst case?

    The runtime of Insertion Sort in the worst case is O(n^2), where n is the number of elements in the array. This is because in the worst case scenario, each element needs to be compared and shifted to its correct position in the sorted array, resulting in a quadratic time complexity. Count Sort, on the other hand, has a linear runtime of O(n+k) in the worst case, where k is the range of the input values. This is because Count Sort creates a count array to store the frequency of each element, and then iterates through this count array to reconstruct the sorted array.

  • How does Insertion sort work?

    Insertion sort works by iterating through the array from left to right, comparing each element to the elements on its left and inserting it into the correct position in the sorted portion of the array. It starts with the second element and compares it to the first element, then moves to the third element and compares it to the elements on its left until it finds its correct position. This process continues until all elements are in their correct positions, resulting in a sorted array. Insertion sort has a time complexity of O(n^2) in the worst-case scenario.

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