## introduction

Algorithm is a sequence of steps to solve a problem. Design and analysis of algorithm is very important for designing algorithm to solve different types of problems in the branch of computer science and information technology. Students find it hard to complete the algorithm design assignment due to their busy schedule extracurricular activities and exams being around the corner. If you are one of the million students who does not have time for algorithm assignment, then you can seek algorithm assignment help from professional experts. Assignmentsguru have a team of programmers who have expertise and knowledge in designing algorithm assignments that can fetch you excellent grades.

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An algorithm is a set of steps of operations to solve a problem performing calculation, data processing, and automated reasoning tasks. An algorithm is an efficient method that can be expressed writhing a certain amount of time and space.

An algorithm is the best way to represent a solution of particular problem in very simple and efficient way. If we have an algorithm for specific problem then we can implement it in any programming language.

## Characteristics of algorithm

1. Input specified-The input is the data to transformed during computation to produce the output. An algorithm should have Zero or more well defined inputs. Input precision requires that you know what kind of data, how much and what should be.
2. Output specified- The output is the data resulting from computation. An algorithm should 1 or more well defined outputs, and should match the desired output. Output precision also requires that you know what kind of data, how much and what form the output should be.
3. Effectiveness-For an algorithm to be effective, it means that all those steps that are required to get output must be feasible with the available resources. It should not contain any unnecessary and redundant steps which could make an algorithm ineffective.
4. Finiteness-An algorithm must stop, eventually. Stopping mean you get desired output or you get response that no solution is possible. Algorithms must terminate after a finite of steps. There is no point in developing an algorithm which is infinite as it will be useless for us/
5. Independent-An algorithm should have step by step directions which should be independent of any programming code. it should be such that it could run on any programming languages.
6. Definiteness-Algorithms must specify every step and the order the steps must be taken in the process. Definiteness means specifying the sequence of operations for turning input into output. Algorithm should be clear and unambiguous. Details of each step must also be spelled out.

## Algorithm design

The important aspect of algorithm design includes creating efficient algorithm to solve a problem in efficient way using minimum time and space. To solve a problem, different approaches can be followed some of them can be efficient with respect to time consumption, whereas other approaches may be memory efficient. However, one has to keep in mind that both time consumption and memory usage cannot be optimized simultaneously.

If we require an algorithm to run in lesser time, we have to invest in more memory and if we require an algorithm to run in lesser memory we need to have more time.

## Difference between an algorithm and pseudocode

An algorithm is formal definition with specific characteristics that describes a process, which could be executed by Turing complete computer machine to perform a specific task. Algorithm can be used to describe any high-level task in computer science.

On the other hand, pseudocode is an informal and human readable description of an algorithm leaving many granular details of it. Writing a pseudocode has no restriction of styles and its only objects to describe the high-level steps of algorithm in much realistic manner in natural language.

## Algorithm analysis

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. Most algorithms are designed to work with inputs of arbitrary length. Analysis of algorithms is the determination of the amount of time space resource required to execute it.

The efficiency or running time of an algorithm is stated as a function relating the input length to the number of steps known as Time complexity, or volume memory, known as Space complexity. By considering an algorithm for specific problem we can begin to developed pattern recognition is that similar types of problems can be solved by the help of this algorithm

Analysis of algorithm is the process of analyzing the problem-solving capability of the algorithm in terms of time and size required. However, the main concern of algorithms is the required time or performance generally we perform the following types of analysis.

• Worst-case-The maximum number of steps taken on any instance of size a.
• Best-case-the minimum number of steps taken on any instance of size a
• Average case-an average number of steps taken on any instance of size a

## Algorithmic techniques

There are different ways to execute the same program. So, it’s up to programmer to use the right technique to draft the algorithm assignment that works effectively and efficiently. These techniques include:

1. Divide and conquer- This is the best technique that would break a complicated problem into small chunks. You can solve each sub- problem and then join all the problems to give a perfect solution. This type of technique is widely use to multiply many numbers.
2. Backtracking algorithm- In this type of technique, a single move is selected from a number of moves. If you are able to solve problem with the move that you have picked, the result would be printed, else backtracked to choose another move.
3. Randomized algorithm-This type of technique is used to make the right decision logically and accurately. The best example of this algorithm is quicksort.
4. Dynamic programming-This technique would break the problem into smaller problems. Though this technique find to be similar to that of divide and conquer technique, but both are chalk and cheese dynamic programming is used to divide a single problem int sub problems which are then overlapped to form the best sub-structure.
5. Greedy algorithm-This is a perfect technique that is use to solve optimization issues. This type of algorithm will solve the problems by taking the current situation into consideration. However, this will not take the future situation into considerations to find solution to a problem.

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