Table of Contents
How does an algorithm relate to a computer?
In the most general sense, an algorithm is a series of instructions telling a computer how to transform a set of facts about the world into useful information. The facts are data, and the useful information is knowledge for people, instructions for machines or input for yet another algorithm.
What is algorithm and complexity in computer science?
An algorithm is a specific procedure for solving a well-defined computational problem. The development and analysis of algorithms is fundamental to all aspects of computer science: artificial intelligence, databases, graphics, networking, operating systems, security, and so on.
Does time complexity depend on hardware?
Time and space complexity depends on lots of things like hardware, operating system, processors, etc. Let each operation takes time. The number of lines of code executed is actually depends on the value of .
What is the difference between an algorithm and a computer program?
Differences between Algorithm and Program An algorithm is more like an idea, a way to solve a problem, while a program is more linked to the execution of one or more tasks by a computer. A program can implement one or more algorithms, or it may be so simple that we don´t have to use an algorithm.
What are the two factors which affect the complexity of algorithm?
Two factors which determine the complexity of an algorithm :1 Time Complexity :The amount of computer time algorithm needs to run to completion. 2 Space Complexity :The amount of memory algorithm needs to run to completion.
What is the time complexity of an algorithm?
$\\begingroup$From Wikipedia In computer science, the time complexity is the computational complexity that describes the amount of time it takes to run an algorithmand see also from CS.SO Difference between time complexity and computational complexity$\\endgroup$ – kelalaka Aug 24 ’19 at 21:34 Add a comment |
What is linear time complexity O(n)?
If an algorithm’s running time is directly proportional to the input data size, (e.g it grows linearly when the input data size increases), we call this a linear time complexity O (n). Let’s analyze the implemented algorithm in the function shown above.
What are the methods to distinguish between two algorithms?
The method must be: Independent of the machine and its configuration, on which the algorithm is running on. Shows a direct correlation with the number of inputs. Can distinguish two algorithms clearly without ambiguity. There are two such methods used, time complexity and space complexity which are discussed below:
What is running time of an algorithm on a particular input?
The running time of an algorithm on a particular input is the number of primitive operations or “steps” executed. Also the author uses the running time to analyze algorithms. Then I referred a book called Data Structures and Algorithms made easy by Narasimha Karumanchi. In which he describes the following.