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Algorithm Design Techniques Quiz

Test your knowledge of algorithm design techniques with our engaging quiz! This quiz includes 30 carefully crafted questions that cover various concepts such as backtracking, dynamic programming, and greedy algorithms.

Challenge yourself and see how well you understand:

  • NP-complete problems
  • Minimum spanning trees
  • Algorithm efficiency
  • Huffman coding
30 Questions8 MinutesCreated by CodingCaptain321
One of the two major category of problems are: (choose one)
Optimization
Graphing
Searching
Sorting
Backtracking is a general algorithm design technique for: (choose one)
Solving problems defined by recurrences with overlapping subproblems
Constructing a solution to a problem piece by piece through a sequence of choices
Solving a problem by constructing candidate solutions one component at a time based on a certain rule
Solving a problem by transforming it into another simpler instance of the same problem
Prim’s algorithm provides a solution for: (choose one)
Transitive closure
Single-source shortest paths
All pairs shortest paths
Minimum Spanning Tree
Problems that are tractable are those that: (choose one)
Cannot be solved in polynomial time
Cannot be solve by any algorithm
Can be solved in polynomial time
Can be solved for only small inputs
Which is NOT true? (choose one)
Backtracking uses a bounding function
Backtracking is used for non-optimization problems
Branch-and-bound prunes non-promising nodes
Branch-and-bound is used for optimization problems
The time efficiency of Floyd’s algorithm is: (choose one)³
Θ (n²)
Θ (n³)
Θ (n² log n)
Θ (n)
Which of the following is an example of a NP-complete problem? (choose one)
Halting problem
Shortest paths
Minimum Spanning Tree
Hamiltonian circuit
Kruskal’s algorithm provides a solution for: (choose one)
Minimum Spanning Tree
Single-source shortest paths
All pairs shortest paths
Transitive closure
Which is not a step in backtracking? (choose one)
Explore the state space tree using BFS
Explore the state space tree using DFS
Construct the state space tree
Prune non-promising nodes
Which is NOT a difference between Prim’s and Dijkstra’s algorithms? (choose one)
Different labels for each vertex
Different kinds of spanning trees
Different greedy strategies
Different shortest path problem
Which of the following is true about Memory Functions? (choose one)
Solves only subproblems necessary for the solution more than once
Solves all subproblems for the solution only once
Solves all subproblems for the solution more than once
Solves only subproblems necessary for the solution only once
Backtracking explores the state space tree using: (choose one)
Best-first traversal
Level-order traversal
Breath-first traversal
Depth-first traversal
Which one of the following is a basic component of a dynamic programming algorithm?
Tabular computation
Sub problem definition
Solution frame
Subsequence extraction
Which of the following is an example of dynamic programming? (choose one)
Minimum spanning trees
Computing binomial coefficients
Single source shortest paths
Binary balanced search trees
Which is not a limitation of algorithm power? (choose one)
Some problems cannot be solved by any algorithm
Some problems can be solved but are tractable
Some problems can be solved by algorithms but not in polynomial time
Some problems that can be solved in polynomial time usually have lower bounds on
Which is NOT a characteristic of Huffman’s algorithm? (choose one)
Yields prefix-free codes
Compression ratio falls between 20% and 80%
Important file compression method
Probabilities are assigned to all tree nodes
Which of the following is true? (choose one)
Many problems that are not naturally decision problems can be reduced to a series of decision problems
NP is the class of all decision problems whose proposed solutions can be verified in polynomial time and are solvable by a deterministic polynomial algorithm
Problems that can be solved in polynomial time are called intractable
The discovery of a polynomial-time algorithm for any known NP-complete problems would imply that P is equal to NPC
The first proof of a problem’s NP-completeness was for: (choose one)
Graph coloring
CNF_satisfiability
Knapsack
Bin packing
Floyd’s algorithm is NOT applicable to: (choose one)
Undirected graphs
Directed graphs
Graphs with negative weights
Graphs with negative weights
Greedy technique is a general algorithm design technique for: (choose one)
Solving problems defined by recurrences with overlapping subproblems
Solving a problem by constructing an optimal solution piece by piece through a sequence of choices
Solving a problem by transforming it into another simpler instance of the same problem
Solving a problem by constructing candidate solutions one component at a time based on a certain rule
Backtracking and Branch-and-Bound techniques are similar in that they both: (choose
Utilize best-first tree traversal
Utilize state space trees
Are used for optimization problems
Utilize bounding functions
Dijkstra’s algorithm provides a solution for: (choose one)
Minimum Spanning Tree
All pairs shortest paths
Single-source shortest paths
Transitive closure
Which of the following is not a characteristic of choices made by Greedy algorithms?
Transitive
Feasible
Locally optimal
Irrevocable
The time efficiency of the dynamic programming algorithm for the optimal Binary Search Tree problem is:
Θ (n²)
Θ (n³)
Θ (n² log n)
Θ (n)
Which is NOT a characteristic of NP Problems?
Cannot be solved by any polynomial-time algorithm
Are solvable and tractable
Are solvable but intractable
A solution to the problem can be verified in polynomial time
Dijkstra’s algorithm is not applicable to: (choose one)
Graphs with negative weights
Graphs with positive weights
Undirected graphs
Directed graphs
For which problem does Greedy algorithms yield optimal solutions? (choose one)
All instance of change making
Traveling Salesman Problem
Huffman codes
Knapsack problem
Which is not a step in branch-and-bound? (choose one)
Explore the state space tree using best-first traversal
Set up a bounding function
Construct the state space tree
Explore the state space tree using breath-first traversal
Warshall’s algorithm provides a solution for: (choose one)
Transitive closure
All pairs shortest paths
Single-source shortest paths
Minimum Spanning Tree
Dynamic programming is a general algorithm design technique for: (choose one)
Constructing a solution to a problem piece by piece through a sequence of choices
Solving problems defined by recurrences with overlapping subproblems
Solving a problem by constructing candidate solutions one component at a time based on a certain rule
Solving a problem by transforming it into another simpler instance of the same problem
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