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When sequentially searching n items, the best-case is O(1) and the worst-case is O(n). But when the items are sorted, binary search will improve efficiency. The best case is still O(1), but worst case drops to O(log n) where log n is the binary logarithm of n.

Binary search starts with the middle element of the set. If the set is empty, the item we're looking for does not exist but if the middle element is the item we are looking for then we are done. If not, a simple comparison will tell us in which half of the set to discard (including the middle element). We repeat the process with the remaining half. If there are no elements remaining, the item does not exist.

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Q: How you can improve search efficiency of sequential search for a sorted file?
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How you can improve search efficiency of sequential search for a sorted file. Discuss limitations in such?

When sequentially searching n items, the best-case is O(1) and the worst-case is O(n). But when the items are sorted, binary search will improve efficiency. The best case is still O(1), but worst case drops to O(log n) where log n is the binary logarithm of n. Binary search starts with the middle element of the set. If the set is empty, the item we're looking for does not exist but if the middle element is the item we are looking for then we are done. If not, a simple comparison will tell us in which half of the set to discard (including the middle element). We repeat the process with the remaining half. If there are no elements remaining, the item does not exist.


Why linear search is called sequential search?

A linear search is called a sequential search because a sequential search takes linear time and therefore has a worst-case time-complexity of O(n) for a data sequence of n elements. Although there are more efficient search algorithms than linear search, not all data containers are ideally suited to them. For example, although a binary search can be performed in quadratic time (O(log n)) when the data container is in sorted order, we can only achieve maximum efficiency when the data container also supports constant-time random-access. Arrays and vectors do support constant-time random-access, but if the container is not sorted then we must resort to the less-efficient linear search. Linked lists do not support constant-time random-access thus a linear search would be more efficient even if the list were in sorted order.


How do you search a particular element from the vector?

To search a particular element from the vector, use the find() algorithm. If the vector is sorted, you can use the binary_search() algorithm to improve efficiency. Both algorithms can be found in the <algorithm> header in the C++ standard library.


What is a random access file in QBasic?

Random access simply means the ability to read and write anywhere in the file, as opposed to sequential access where data is simply appended to the end of the file and is accessed by traversing from the start of the file in sequential order. Random access is ideally suited to data arrays where every element in the file is exactly the same length, allowing constant-time traversal from one element to any other, in both directions. If the data is also sorted, random access also allows binary search to improve search efficiency.


Which search algorithm requires that the arrays contents be sorted?

Binary Search Algorithm

Related questions

How you can improve search efficiency of sequential search for a sorted file. Discuss limitations in such.?

When sequentially searching n items, the best-case is O(1) and the worst-case is O(n). But when the items are sorted, binary search will improve efficiency. The best case is still O(1), but worst case drops to O(log n) where log n is the binary logarithm of n. Binary search starts with the middle element of the set. If the set is empty, the item we're looking for does not exist but if the middle element is the item we are looking for then we are done. If not, a simple comparison will tell us in which half of the set to discard (including the middle element). We repeat the process with the remaining half. If there are no elements remaining, the item does not exist.


How you can improve search efficiency of sequential search for a sorted file. Discuss limitations in such?

When sequentially searching n items, the best-case is O(1) and the worst-case is O(n). But when the items are sorted, binary search will improve efficiency. The best case is still O(1), but worst case drops to O(log n) where log n is the binary logarithm of n. Binary search starts with the middle element of the set. If the set is empty, the item we're looking for does not exist but if the middle element is the item we are looking for then we are done. If not, a simple comparison will tell us in which half of the set to discard (including the middle element). We repeat the process with the remaining half. If there are no elements remaining, the item does not exist.


Why linear search is called sequential search?

A linear search is called a sequential search because a sequential search takes linear time and therefore has a worst-case time-complexity of O(n) for a data sequence of n elements. Although there are more efficient search algorithms than linear search, not all data containers are ideally suited to them. For example, although a binary search can be performed in quadratic time (O(log n)) when the data container is in sorted order, we can only achieve maximum efficiency when the data container also supports constant-time random-access. Arrays and vectors do support constant-time random-access, but if the container is not sorted then we must resort to the less-efficient linear search. Linked lists do not support constant-time random-access thus a linear search would be more efficient even if the list were in sorted order.


How do you search a particular element from the vector?

To search a particular element from the vector, use the find() algorithm. If the vector is sorted, you can use the binary_search() algorithm to improve efficiency. Both algorithms can be found in the <algorithm> header in the C++ standard library.


What is a random access file in QBasic?

Random access simply means the ability to read and write anywhere in the file, as opposed to sequential access where data is simply appended to the end of the file and is accessed by traversing from the start of the file in sequential order. Random access is ideally suited to data arrays where every element in the file is exactly the same length, allowing constant-time traversal from one element to any other, in both directions. If the data is also sorted, random access also allows binary search to improve search efficiency.


Which search algorithm requires that the arrays contents be sorted?

Binary Search Algorithm


What are the disadvantages of Fibonacci search?

There are a few disadvantages of the Fibonacci search: It can be slower than other search algorithms if the data is not sorted. It can be less accurate than other search algorithms if the data is not sorted. It can be more difficult to implement than other search algorithms.


Items that are not suitable for a binary search?

The only items suitable for a binary search are those which are in a sorted order.


Advantages of binary search over sequencial search?

Linear search takes linear time with a worst case of O(n) for n items, and an average of O(n/2). Binary search takes logarithmic time, with a worst and average case of O(n log n). Binary search is therefore faster on average.


Difference between sequential organization and serial organization?

the difference is that sequential organization: this are records are stored and accessed in a particular order sorted using a key field serial organisation: records in a file are stored one after another. You need to go first file in order to reach the required file.


Is sorting a binary search tree simple?

A binary search tree is already ordered. An in order traversal will give you a sorted list of nodes.


When binary search can't be implemented?

When the elements... ... are not sorted ... have different sizes ... are only sequentially accessible