91Ó°ÊÓ

In a sequential search, we start at the beginning of the list (array) and compare each element with the target element until we either find a match or reach the end of the list. The time complexity of a sequential search is O(n), where n is the number of elements in the list.

As some items are searched more frequently than others, it will be beneficial to rearrange the array so that the frequently searched items are placed closer to the beginning of the array. This way, the average search time for those items will be reduced. To achieve this, we need to first collect data on how frequently items are searched.

Once we know the frequency of searches for each item, we can reorder the array to place items in descending order of search frequency. This means that the most frequently searched item will be at the beginning of the array, followed by the second most frequently searched item, and so on. This arrangement ensures that on average, the frequently searched items are found more quickly during a sequential search, thereby improving the performance of the search.

After reordering the array, the average search performance should improve. Compare the old and the new average search times to analyze the improvement. You can calculate the new average search time by multiplying the search frequency of each item with its position (index) in the reordered array and summing these products for all items. For example, let's consider an array of length n with elements A, B, C, and D with the following search frequencies: - A: 40% - B: 30% - C: 20% - D: 10% Now, if we reorder the array based on these frequencies: New array: A B C D (descending order of search frequencies) New average search times: (0.4 * 1) + (0.3 * 2) + (0.2 * 3) + (0.1 * 4) = 2.0 Compare this with the old average search time to see the improvement in performance. Remember to continuously update the order of the array as the frequency of searches changes over time to ensure optimal search performance.