Design and Analysis of Algorithms Quiz

What is an algorithm?

• A finite set of instructions that accomplishes a particular task

• A random set of instructions

• A set of instructions that can never be completed

• A set of instructions that only work on specific computers

What is the purpose of algorithm analysis?

• To make algorithms more complex

• To provide theoretical estimation for the required resources of an algorithm

• To slow down the execution of algorithms

• To confuse students

What is the space complexity of an algorithm?

• The amount of memory it needs to run to completion

• The number of comparisons between integers

• The number of steps it takes to execute

• The number of memory accesses performed

What is the difference between Las Vegas and Monte Carlo algorithms?

• Monte Carlo algorithms are deterministic

• Las Vegas algorithms are faster than Monte Carlo algorithms

• Monte Carlo algorithms always produce the same output for the same input, while Las Vegas algorithms might differ

• Las Vegas algorithms always produce the same output for the same input, while Monte Carlo algorithms might differ

What is the topmost node in a tree called?

• Leaf node

• Sub-node

• Root node

• Structural node

Which data structure is used to implement indexing in databases?

• Heap

• Graph

• Tree

• Hashing

What is the time complexity of computing biconnected components in a graph?

• O(n)

• O(n log n)

• O(n^2)

• O(n + e)

What is the purpose of the Weighted Union operation in Disjoint Sets?

• To delete a vertex from the set

• To find the root of a vertex

• To add a new vertex to the set

• To merge two sets based on their weights

Which traversal technique explores all vertices adjacent from a starting vertex?

• Postorder Traversal

• Depth-First Search

• Breadth-First Search

• Inorder Traversal

What is the difference between dynamic programming and greedy algorithms?

• Dynamic programming always guarantees an optimal solution, while greedy algorithms may not

• Greedy algorithms always guarantee an optimal solution, while dynamic programming may not

• Dynamic programming is faster than greedy algorithms

• Greedy algorithms are more memory efficient than dynamic programming