Algorithms Quiz

A flowchart uses shapes like ovals, diamonds, and rectangles to visually represent the flow of an algorithm, while pseudocode uses written statements in plain English to describe the steps. Flowcharts provide a more visual approach, while pseudocode is more detailed and closely resembles actual code.

A step-by-step approach ensures that every action in the algorithm is clearly defined and leads towards the solution. This approach reduces the risk of errors, ensures clarity, and makes the algorithm easier to implement and understand.

Algorithmic complexity refers to how the runtime or space requirements of an algorithm grow as the size of the input increases. It is typically measured using Big O notation (e.g., O(n) for linear time, O(log n) for logarithmic time).

A linear search is a simple searching algorithm where each item in a list is checked in sequence until the desired item is found or the entire list is checked. It works well for small, unsorted lists but is inefficient for large datasets.

A 'for' loop is used when the number of iterations is known in advance, and the loop runs a specific number of times. A 'while' loop, on the other hand, runs as long as a condition is true, and the number of iterations is not necessarily known at the start.

A decision structure in an algorithm allows for different actions based on a condition, such as if-else statements. It’s important because it enables the algorithm to make choices and handle different situations or inputs appropriately.

A binary search algorithm is an efficient searching algorithm that divides a sorted list in half repeatedly, comparing the target value with the middle element and eliminating half of the remaining elements with each comparison. It should be used when the list is already sorted.

Iteration refers to the repetition of a set of instructions or steps in an algorithm, often through loops like 'for' or 'while'. It allows an algorithm to process multiple data points or perform a task multiple times.

Testing an algorithm ensures that it works as expected, produces the correct output, and handles edge cases effectively. It helps identify errors or inefficiencies before implementation in a program, reducing the risk of failure in real-world use.

An algorithm provides a clear, structured approach to solving a computational problem by breaking it down into smaller, manageable steps. It helps define how to process inputs and produce outputs, making it an essential part of programming and problem-solving.