There can be several aspects when you think about analysis of algorithms. You may be writing a large scale application where you have to decide between two choices. You may be trying to submit a solution to some online competition and you want a higher score, or probably you may just want to write fewer lines of code. Analysis during an Interview Let’s say you are appearing for an interview. The person who is interviewing you gives you a problem to solve. He or she is not just interested in…
Maths
Algorithms involving basic math calculations


As soon as you hear the word ‘Big O’, does your mind go “Oh my god! Oh no! This again?” The next thing following it would be time complexity and what not. Suddenly, your brain starts getting this confusing signals and you lose track of what is happening. If you have felt this at some point of time while learning programming, then I want to tell you that you are not alone. In fact, you are proceeding in the right direction. But all these notations can start to get overwhelming…

The first thing that comes to our mind on hearing the word recursion is doing a thing over and over again. But how can you expect to achieve a solution to a problem by repeating the same thing over and over again. In this post we would be understanding exactly that. Algorithmic paradigms are a way to solve a problem, and recursion is one of them. Some of the other ways are: Brute Force Divide and Conquer Greedy Dynamic Programming So, what is Recursion? Sometimes a good image helps to…

Time complexity is an important criteria when determining the quality of an algorithm. An algorithm is better if it produces the same result in a less time for the same input test cases. However, one must take care of the type of input data used. Some input data can give you false positives. Let us take an example to understand this better. You have an algorithm that is sorts a list of numbers. If the input data you provide to this algorithm is already sorted. Then this algorithm gives you…

Algorithmic Paradigms in short define how you can go about solving a problem. If you are starting to solve problems in computer science, this course is designed for you. However, this course is also recommended for you if you are revising all the basics and want a quick recap of some famous techniques. What are Algorithmic Paradigms? Whenever you try to build something, or develop something, an initial research and foundation is very essential. Think about it, a skyscraper will only be as stable as its base. In the world…

Dynamic programming always reminds of a favorite quotation: Of the several different ways to solve a problem, dynamic programming is a paradigm where we tend to solve the problem as we move ahead and keep on learning. This is one of the techniques which even seasoned programmers find hard to implement. In this post we will try to address some of these fears and aim to have a better understanding of this approach. If you are new to problem solving and somehow landed at this post, it is recommended to…

We compare things all the time to determine which one is better over the other. The best example is when you are buying stuff online, we compare prices across websites, two different mobile phones, or even two different outfits. We know that there are different techniques of solving a problem in computer science: Brute Force Divide and Conquer Greedy Dynamic Programming Naturally, when we try to solve a problem with different methods, one would want to compare them. Once they are put side to side, we can then analyze which…

Greedy algorithms is a paradigm that describes the approach on how you can go about solving a problem. You might have heard about a lot of algorithmic techniques while learning how to solve problems in computer science. The others being: Brute Force Divide and Conquer Dynamic Programming In this post we shall understand what a greedy algorithm is and how can it be used to solve problems which don’t seem very trivial at the first glance. What is a Greedy Algorithm? What is the first thing that comes to your…