Computational complexity theory
- 1. Computational complexity theory is a branch of theoretical computer science that focuses on classifying computational problems based on their inherent difficulty and the amount of resources required, such as time and space. It deals with understanding the efficiency of algorithms, analyzing the feasibility of solving problems on different types of machines, and determining the limitations of computing power. By studying computational complexity theory, researchers seek to investigate the boundaries of computation and identify the capabilities and limitations of computers in solving various types of problems.
What is computational complexity theory focused on?
A) Developing new programming languages
B) Hardware design for computers
C) Psychological aspects of human-computer interaction
D) Analyzing the resources required to solve computational problems
- 2. Which notation is commonly used to denote the complexity of algorithms?
A) Binary code
B) Big O notation
C) Greek letters
D) Roman numerals
- 3. Which complexity class contains decision problems that are efficiently verifiable?
A) NP
B) PSPACE
C) EXP
D) BPP
- 4. What is the Cook-Levin theorem related to in computational complexity theory?
A) Quantum algorithms
B) P vs NP problem
C) NP-completeness
D) Parallel computing
- 5. What complexity class is used to classify problems that can be solved by a quantum computer in polynomial time?
A) EXPSPACE
B) PSPACE
C) BQP
D) NP-complete
- 6. What does 'EXP' stand for in computational complexity theory?
A) Expert
B) Exploratory
C) Expanded
D) Exponential time
- 7. What is the main objective of computational complexity theory?
A) To generate random numbers
B) To build supercomputers
C) To create faster computers
D) To classify computational problems based on their inherent difficulty
- 8. What is the complexity class that represents the hardest problems in NP?
A) P
B) EXPTIME
C) NP-complete
D) BPP
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