All Flashcards
How is pathfinding (shortest path) applied in real-world scenarios?
GPS navigation systems, network routing, logistics optimization.
How are sorting algorithms applied in real-world scenarios?
Database management, search engine results, e-commerce product listings.
How are heuristics used in AI?
Game playing (e.g., chess), machine learning model training, spam filtering.
How is cryptography related to computer science?
It uses algorithms to secure data and communications, ensuring confidentiality and integrity.
How is dynamic programming applied in bioinformatics?
Sequence alignment for DNA and protein analysis.
How are graph algorithms used in social networks?
Friend recommendation, community detection, influence analysis.
How is machine learning used in fraud detection?
Identifying patterns of fraudulent behavior based on transaction data.
How are search algorithms used in web search engines?
Indexing and retrieving relevant web pages based on search queries.
How is data compression used in multimedia applications?
Reducing the size of images, audio, and video files for efficient storage and transmission.
How are scheduling algorithms used in operating systems?
Managing and prioritizing processes to optimize CPU utilization and system performance.
What is the significance of polynomial time?
Indicates an algorithm is generally efficient and scalable.
Why are exponential time algorithms considered inefficient?
Their runtime grows very quickly, making them impractical for large inputs.
When should heuristics be used?
When finding the optimal solution is too computationally expensive.
How does input size affect algorithm efficiency?
Larger inputs generally require more computational resources, impacting efficiency.
What is the trade-off when using heuristics?
Accuracy is sacrificed for speed and feasibility.
What is the goal of algorithm design?
To solve a problem efficiently using minimal resources.
Explain the relationship between problem type and algorithm efficiency.
Optimization problems can be more computationally intensive than decision problems.
What does it mean for an algorithm to be 'scalable'?
The algorithm maintains reasonable efficiency as the input size increases.
What is the importance of understanding algorithm efficiency?
Helps in choosing the best approach for solving a problem within resource constraints.
How do heuristics relate to unreasonable time complexity?
Heuristics provide practical solutions when a problem has unreasonable time complexity.
What is an algorithm?
A set of instructions designed to solve a specific problem.
What is a problem instance?
A specific input to a problem.
What is a decision problem?
A problem with a yes or no answer.
What is an optimization problem?
A problem that seeks the best solution from many possibilities.
What is algorithm efficiency?
A measure of how many computational resources an algorithm uses.
What is 'reasonable time' in algorithm analysis?
Algorithms that run in polynomial time or lower.
What is 'unreasonable time' in algorithm analysis?
Algorithms that run in exponential or factorial time.
What are heuristics?
Approximation techniques used when finding an exact solution is too difficult or time-consuming.
Define polynomial time.
A running time that increases as a polynomial function of the input size (e.g., n, n^2, n^3).
Define exponential time.
A running time that increases exponentially as the input size grows (e.g., 2^n, 3^n).