Fundamentals of Algorithms

Front

What is an algorithm?

Back

An algorithm is a step-by-step procedure for solving a problem.

Front

Explain the difference between time complexity and space complexity.

Back

Time complexity focuses on execution time, whereas space complexity focuses on memory usage.

Front

What is Big O notation?

Back

Big O notation is a way to describe the upper limit of an algorithm's time or space complexity.

Front

Describe the concept of divide and conquer in algorithms.

Back

Divide and conquer is an algorithm design paradigm that recursively breaks a problem into smaller subproblems, solves them independently, and combines their results.

Front

What is a greedy algorithm? Give an example.

Back

An example of a greedy algorithm is the Coin Change Problem, where the goal is to make change for a given amount using the fewest coins possible. The algorithm selects the largest denomination coin first until the amount is reached.

Front

What is the purpose of a sorting algorithm?

Back

The purpose of a sorting algorithm is to arrange data in a specified order.

Front

Explain the difference between linear search and binary search.

Back

Linear search is O(n) in time complexity, while binary search is O(log n) and requires a sorted array.

Front

What is dynamic programming? Provide a use case.

Back

A use case of dynamic programming is the Fibonacci sequence calculation, where each number is the sum of the two preceding ones. Instead of recalculating Fibonacci numbers multiple times, dynamic programming stores previously computed values.

Front

What are the characteristics of a good algorithm?

Back

Characteristics of a good algorithm include clarity, efficiency, finiteness, definiteness, generality, and measurable performance.

Front

What is the significance of algorithm analysis in computer science?

Back

Algorithm analysis is significant for evaluating efficiency and performance of algorithms.