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Topic: Design & Analysis of Algorithms (Computer Science Course)

Introduction to Design & Analysis of Algorithms Assignment Services

Design and Analysis Algorithm

 

Introduction:

A finite set of instruction that specifies a sequence of operation is to be carried out in order to solve a specific problem or class of problems is called an Algorithm. . An algorithm is a sequence of unambiguous instructions for solving a problem, i.e., for obtaining a required output for any legitimate input in a finite amount of time. Design and Analysis of Algorithm help to design the algorithms for solving different types of problems in Computer Science. It also helps to design and analyse the logic on how the program will work before developing the actual code for a program An Algorithm is a sequence of steps to solve a problem. To design an algorithm, it is very important for designing algorithm to solve different types of problems in the branch of computer science and information technology.

 

Definition:

Design and analysis of Algorithm is a set of well-defined instructions designed to perform a specific set of tasks. It is used in Computer science to perform calculations, automatic reasoning, data processing, computations, and problem-solving. For designing an algorithm, it is important before writing the program code as the algorithm explains the logic even before the code is developed. Algorithm Design Techniques in Data Structure are all data structures and each of them allows us to perform different operations on data. No matter which programming language you use, it is important to learn algorithm design techniques in data structures in order to be able to build ascendable systems.

 

Types of Design and Analysis Algorithm:

  • Divide and Conquer algorithm: A divide and conquer algorithm is a strategy of solving a large problem by breaking the problem into smaller sub-problems. Solving the sub-problems, and. combining them to get the desired output. Divide the problem into a number of sub problems that are smaller instances of the same problem, Conquer the sub problems by solving them recursively. If they are small enough, solve the sub problems as base cases. Combine the solutions to the sub problems into the solution for the original problem.
  • Dynamic Programing: Dynamic Programming is a technique in computer programming that helps to efficiently solve a class of problems that have overlapping and optimal substructure property. Dynamic Programming is mainly an optimization over plain recursion. Wherever we see a recursive solution that has repeated calls for same inputs, we can optimize it using Dynamic Programming. The idea is to simply store the results of sub problems, so that we do not have to re-compute them when needed later.
  • Greedy heuristics: It is a “Solving Strategy". A Greedy algorithm is one that makes choices based on what looks best at the moment. In other words, choices are locally optimum but not necessarily globally optimum. It is an approach for solving a problem by selecting the best option available at the moment. The algorithm never reverses the earlier decision even if the choice is wrong. It works in a top-down approach. 

 

Design and Analysis Algorithm Question and Answers:

Question 1. What is algorithm analysis?

Answer: Algorithm analysis is an important part of computational complexity theory, which provides theoretical estimation for the required resources of an algorithm to solve a specific computational problem. Analysis is the determination of the amount of time and space resources required to execute it.

 

Question 2. What are the uses of algorithm?

Answer: Algorithms are used for calculation, data processing, and automated reasoning.” Whether you are aware of it or not, algorithms are becoming a ubiquitous part of our lives.

 

Question 3. What are the characteristics of an algorithm?

Answer: Characteristics of an Algorithm

  1. Input: An algorithm requires some input values. 
  2. Output: At the end of an algorithm, you will have one or more outcomes.
  3. Unambiguity: A perfect algorithm is defined as unambiguous, which means that its instructions should be clear and straightforward.

 

Question 4. What are the steps in the design of an algorithm?

An Algorithm Development Process

  1. Obtain a description of the problem. This step is much more difficult than it appears. 
  2. Analyse the problem.
  3. Develop a high-level algorithm.
  4. Refine the algorithm by adding more detail.
  5. Review the algorithm.

 

Question 5. What kind of problems are solved by the algorithm?

Answer: Algorithms are commonly used to solve certain types of computational problems. We can often describe such a problem by specifying a relationship between input and output. The sorting problem, for example, can be described like this: Input: a sequence a1, a2, an of n numbers.

 

 

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