Introduction to Algorithm in Programming
The whole world is digitalized today. There is a sense of intelligence, there is a sense of communication in every traditional device that makes our lives so easy, so fast. All these technological advancements are taken forward by software which is a bunch of programs that are meant to solve a problem. And every program is built upon a logic/solution which is called as an Algorithm. The name algorithm is named after the clever man from Baghdad, Al Khwarizmi. He was the first person to introduce algorithms to the world which were mechanical, precise and unequivocal.
What is an algorithm?
A standard textbook definition would be – an algorithm is a well-defined step by step solution or a series of instructions to solve a problem. An algorithm can be the method to find the least common multiple of two numbers or the recipe to cook Veg Manchurian.
What is an algorithm in a programming perspective?
You see, computer basically does a lot of math which means it has a lot of problems to solve. That’s exactly why algorithms form the heart of computer science. A computer algorithm is a computational procedure that takes in a set of finite input and transforms it into output by applying some math & logic. An algorithm in programming will have several steps as follows –
- Problem definition – What is to be done?
- Data collection – What do we have to solve the problem? Or inputs.
- Data processing – Understanding what we have or transforming them into a usable form.
- Logical approach – Employing the collected & created data against logic to solve.
- Solution – Present the solution in the way you want in a GUI or a terminal or a diagram or a chart.
To put it in a nutshell, given finite input value for x, an algorithm transforms it into effective output value y, where y is f(x) for some well-defined function f.
One important aspect to know is that the algorithms are not strictly bound to any programming language. They are generic solutions as such.
How does the algorithm in programming make working so easy?
The subject field of algorithms has grown so deep and wide that the theories and the basics that are laid down will help us attack any computational problem. There are so many efficient algorithms that are already published like binary search, bubble sort, insertion sort, merge sort, quick sort, Euclid’s algorithms to find the GCM, Prim’s algorithms to find the shortest path in the graph, etc.
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There are so many kinds of algorithms like –
| Brute force algorithms | Which are straight forward trial and error approach of solving problems? Just like you do repeat addition to find the result of a multiplication problem. |
| Divide and Conquer algorithms | Which break the problem into small subproblems and then combine the result of each subproblem to get the final result. Just like you first segregate the coins of different denominations into different buckets and then count the number of coins in each bucket to find how many coins of individual denominations are there. |
| Greedy algorithms | Which follow a problem-solving heuristic to reach the next best state to find the final best state as the result. Just like you find the less steep area which climbing a mountain for ease. |
| Dynamic programming | An approach which is same as divide and conquers but divides the problem into subproblems such that their results are reusable for other subproblems. |
Such methodologies help us come up with a good algorithm which possesses the following defining characteristics. A good algorithm is –
- Precise – It knows the exact and correct steps to execute.
- Unique – The input for the current instructions comes only from the preceding instruction.
- Finite – The algorithm ends giving the result after the execution of a finite number of instructions.
- Generality – The algorithm holds good to set of inputs and not strictly one input.
Advantages of the algorithm and why should we use the algorithm in programming?
More than having a wide horizon of applications in the real world, it acts as a powerful lens to see through a problem. It helps us decide if a problem is solvable or not. If yes, then how, how fast and how accurate? If not, then an algorithm again helps us decide, if we can solve a part of it.
Talking about why we should use algorithms in programming, we must understand that computer programs adopt different algorithms run on computer hardware which has a processor & memory and these components have limitations. A processor is not infinitely fast and the memory we have is not free. They are bounded resources. They must be used wisely and a good algorithm that is efficient in terms of time complexities and space complexities will help you do so.
How this technology will help you in your career growth?
Just like any other technologies, algorithm design in programming is also ever evolving because the computer hardware is ever evolving. Starting from traditional x86 machines to supercomputers to Quantum computers, there has been a revolutionary change in the way of solving problems. Having a strong algorithm design knowledge is what differentiates a skilled programmer from the rest. The modern-day resources don’t really mandate the study of algorithms with so many software frameworks and libraries developed but a thorough understanding of the same will help you so much more.
Conclusion
Despite if someday we have a processor that is incredibly fast and a memory that is continuous, we still have to study algorithm, design them so as to see if the solution terminates and does so with a correct result. May it be commercial applications, scientific computing, engineering, operational research or artificial intelligence, in each field articulating problems, figuring out efficient algorithms to solve and data structures to deal with will remain inevitable forever.
Just like it is an important plan before working. It is important to define the algorithm before coding.
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This has been a guide to Algorithm in Programming. Here we have discussed how the algorithm is useful in programming perspective along with advantages and career development. You may also look at the following articles to learn more –
