Data Structures - Introduction

What is an algorithm?

• A computer program
• A step-by-step procedure to solve a problem
• A hardware device
• A flowchart

Answer explanation

An algorithm is a step-by-step procedure or formula for solving a problem or performing a task.

Why is algorithmic notation important?

• To reduce program size
• To write readable and understandable algorithms
• To increase memory usage
• To design hardware components

Answer explanation

Algorithmic notation helps standardize the description of algorithms, making them easier to understand, analyze, and implement.

What are the key principles of algorithm design?

• Clarity, simplicity, and efficiency
• Complexity and redundancy
• Ambiguity and vagueness
• Speed and size

Answer explanation

Key principles include correctness, efficiency (time and space complexity), clarity, simplicity, and modularity.

What is time complexity?

• The amount of memory an algorithm uses
• The amount of time an algorithm takes to run
• The size of the program
• The type of sorting used

Answer explanation

Time complexity refers to how the running time of an algorithm grows with the input size.

What is 'Big-O' notation?

• A notation to measure the running time of an algorithm
• A symbol for memory space
• A programming language
• A notation to represent binary trees

Answer explanation

Big-O notation is used to describe the upper bound of the time complexity of an algorithm, representing the worst-case scenario. Example: The time complexity of binary search is O(log n).

Which of the following is a basic building block of an algorithm?

• Arrays
• Sequence, Selection, and Iteration
• Loops
• Classes

Answer explanation

Sequence: The order in which instructions are executed. Selection: Decision-making, e.g., `if-else` statements. Iteration: Repeating a set of instructions, e.g., loops.

How is the efficiency of an algorithm measured?

• By counting the number of comments
• By analyzing time and space complexity
• By the number of lines of code
• By the CPU usage

Answer explanation

By evaluating its time complexity and space complexity.

What is worst-case complexity?

• The time when an algorithm performs best
• The maximum time taken by an algorithm in any scenario
• The most frequent time taken by an algorithm
• The ideal scenario for an algorithm

Answer explanation

Worst-case: The longest running time for any input of size n. Best-case: The shortest running time for any input of size n. Average-case: The expected running time over all inputs of size n.

What does asymptotic notation describe?

• The exact running time of an algorithm
• The behavior of an algorithm as the input size grows
• The initial state of an algorithm
• The hardware requirements of an algorithm

Answer explanation

Asymptotic notation (like Big-O, Big-Ω, Big-Θ) helps analyze the performance of algorithms by providing a high-level understanding of how their execution time grows with input size.

What is a one-dimensional array?

• A list of elements arranged in a single row
• A data structure with multiple layers
• A set of pointers
• A hierarchical structure

Answer explanation

A one-dimensional array is a list of elements stored in contiguous memory locations and indexed by a single index.