13 Lecture

1. What is the cost of search in computer science?

a. Amount of time, resources, and computational power required to search for a specific item in a data structure b. The amount of data in a data structure c. The size of the data structure d. The type of data structure used

Answer: a.

2. Which of the following measures is a common measure of search cost?

a. Time complexity b. Space complexity c. Worst-case analysis d. All of the above

Answer: d.

3. Which search algorithm is commonly used for searching a sorted array?

a. Binary search b. Linear search c. Depth-first search d. Breadth-first search

Answer: a.

4. Which data structure is commonly used for implementing hash tables?

a. Linked list b. Queue c. Stack d. Array

Answer: a.

5. What is the time complexity of binary search?

a. O(1) b. O(log n) c. O(n) d. O(n log n)

Answer: b.

6. Which of the following is a disadvantage of linear search?

a. It has a time complexity of O(1) b. It is easy to implement c. It has a time complexity of O(n) d. It is efficient for large datasets

Answer: c.

7. Which of the following is a disadvantage of binary search?

a. It can only be used with sorted arrays b. It has a time complexity of O(n) c. It is difficult to implement d. It is not efficient for large datasets

Answer: a.

8. Which data structure is commonly used for implementing binary search trees?

a. Array b. Linked list c. Queue d. Stack

Answer: b.

9. What is the time complexity of searching a hash table with a good hash function?

a. O(1) b. O(log n) c. O(n) d. O(n log n)

Answer: a.

10. Which of the following measures is not a common measure of search cost?

a. Time efficiency b. Space efficiency c. Worst-case analysis d. Best-case analysis

Answer: d.

1. What is the cost of search and why is it important in computer science? Answer: The cost of search refers to the amount of time, resources, and computational power required to search for a specific item in a data structure. It is important in computer science because efficient search algorithms can significantly reduce search costs and improve overall system performance.

2. What are the common measures of search cost? Answer: Common measures of search cost include time complexity, space complexity, and worst-case analysis.

3. What is the time complexity of binary search? Answer: The time complexity of binary search is O(log n).

4. What is the disadvantage of linear search? Answer: The disadvantage of linear search is that it has a time complexity of O(n), which makes it inefficient for large datasets.

5. What is the advantage of hash tables for search operations? Answer: Hash tables provide constant time search operations with a good hash function.

6. What is the time complexity of searching a hash table with a good hash function? Answer: The time complexity of searching a hash table with a good hash function is O(1).

7. What is the disadvantage of binary search? Answer: The disadvantage of binary search is that it can only be used with sorted arrays.

8. What is the advantage of binary search over linear search? Answer: The advantage of binary search over linear search is that it has a time complexity of O(log n), which makes it more efficient for large datasets.

9. What is worst-case analysis for search algorithms? Answer: Worst-case analysis is a measure of the maximum amount of time or space required to perform a specific operation in the worst-case scenario.

10. How can search costs be reduced in data structures? Answer: Search costs can be reduced in data structures by using efficient search algorithms, such as binary search or hash tables, and by implementing balanced trees or other optimized data structures.

In computer science, the cost of search refers to the amount of time, resources, and computational power required to search for a specific item in a data structure. Efficient search algorithms can significantly reduce search costs and improve overall system performance. Common measures of search cost include time complexity, space complexity, and worst-case analysis. Time complexity is a measure of the amount of time required to perform a specific operation, while space complexity is a measure of the amount of memory required to store a data structure. Worst-case analysis is a measure of the maximum amount of time or space required to perform a specific operation in the worst-case scenario. Binary search is a commonly used search algorithm for searching a sorted array. It has a time complexity of O(log n), which makes it more efficient than linear search for large datasets. Hash tables are also commonly used for search operations because they provide constant time search operations with a good hash function. However, both binary search and hash tables have limitations. Binary search can only be used with sorted arrays, while hash tables can suffer from collisions and have a high space complexity in some cases. Additionally, linear search has a time complexity of O(n), which makes it inefficient for large datasets. To reduce search costs in data structures, it is important to use efficient search algorithms and to implement balanced trees or other optimized data structures. This can significantly improve search performance and reduce the amount of computational power and resources required for search operations.