Algorithm: Definition

Algorithm: Definition

Definition of an Algorithm

Basics of an Algorithm

  • In computer science, an algorithm is a set of instructions for solving a problem or achieving a specific task.
  • It serves as the building block of any computational process, akin to a recipe in cooking.

Characteristics of an Algorithm

  • An algorithm should be clear and unambiguous. Each step in an algorithm must be clear and must lead to only one meaning.
  • An algorithm should be well-defined. The instructions should be effectively defined for every input and should give an output.
  • An algorithm must be finite. It means that the algorithm should terminate after a finite time.
  • An algorithm is effective. It must solve all the instances of the specified problem.
  • An algorithm is also general. It should be able to solve all problems of a particular type, not just a specific instance of the problem.

Structure of an Algorithm

  • An algorithm usually takes one or more inputs as a starting point, which are the initial conditions of the problem to be solved.
  • The algorithm produces an outcome or output, which is the solution to the problem.
  • Between the input and the output, the algorithm performs a finite number of well-defined operations or steps in a particular order.

Real-world Applications

  • Algorithms are used in a wide variety of fields, including mathematics, computer science, physics, and economics.
  • Common examples of algorithms include sorting algorithms (like bubble sort, quick sort), search algorithms (like binary search), and path-finding algorithms used in navigation and robotics.
  • In advanced fields, more complex algorithms are used, such as machine learning algorithms for data analysis and prediction.

Importance of Efficiency

  • The efficiency of an algorithm refers to the amount of computational resources that the algorithm requires to produce the output. These resources could be time (processor usage) and/or space (memory usage).
  • Two major ways to analyze an algorithm are time complexity and space complexity. These measure the time and memory required by an algorithm, given an input size.
  • Solving a problem with an efficient algorithm can greatly reduce the amount of time and/or space required, which is critical in many applications, especially in large-scale computations.

Algorithm Representation

  • Algorithms can be expressed in many kinds of notation, including natural languages, pseudocode, flowcharts, drakon-charts, programming languages or control tables.
  • The choice of representation depends on the purpose of the algorithm. For instance, flowcharts are often used for visualisation purposes whereas pseudocode is useful for describing the logic. On the other hand, algorithm written in a programming language can be executed on a computer.

Designing an Algorithm

  • The process of creating an algorithm is both an art and a science. It requires creativity, experience and analytical thinking.
  • The two most popular methods for algorithm design are recursive algorithms and iterative algorithms.
  • Recursive algorithms involve making the problem simpler and solving the simpler version until a base condition is met.
  • Iterative algorithms involve repeating a certain process until a desired result is achieved. They often employ looping control structures like “for” and “while”.