Understanding Algorithms and Big O Notation
As a full stack web developer and someone freelancing as a programmer, it is essential to grasp the basics of algorithms, data structures and Big O notation. Understanding and applying algorithms helps to simplify and perform faster when dealing with operations and development processes. Big O notation helps to analyze the time and space complexity of an algorithm as well.
What are Algorithms?
An algorithm is a set of instructions used to solve a problem. Algorithms are often used to look for patterns and analyze data.
For example, a web development project may involve the usage of a sorting algorithm to sort a list of data in ascending or descending order. A path finding algorithm may be used to find the shortest route from point A to point B.
How to Implement Algorithms in Different Programming Languages?
Algorithms can be implemented in many programming languages, such as Python, C#, JavaScript, Java, and C++.
For instance, here’s a typical selection sort algorithm written in Python:
```python
def sort(list):
for i in range(len(list)):
# Find the minimum element in remaining
# unsorted array
min_idx = i
for j in range(i+1, len(list)):
if list[min_idx] > list[j]:
min_idx = j
# Swap the found minimum element with
# the first element
list[i], list[min_idx] = list[min_idx], list[i]
list = [64, 25, 12, 22, 11]
sort(list)
print(list)
```
What is Big O Notation?
Big O notation is a way to measure the complexity of an algorithm. It helps to measure how long it will take an algorithm to complete its execution, and how much memory it will require. Different algorithms can have different Big O notation values, which can greatly affect their performance.
For example, let’s take a look at the selection sort algorithm mentioned previously. The Big O notation of this algorithm is O(n2), which means that it takes longer to execute as the number of items (n) in the list increases. This algorithm is therefore not a good choice for sorting large lists.
Resources for Learning Algorithms and Big O Notation
There are several great resources for getting hands on practice with algorithms and Big O notation.
Best YouTube Channels
- The Genuine Coder
- Mackenzie Child
- Traversy Media
- My Code School
- Computerphile
Best Websites
- GeeksforGeeks
- HackerRank
- LeetCode
- Hackerrank
Conclusion
In conclusion, understanding algorithms and Big O notation is essential for any programmer looking to advance their skillset. There are many great resources, both online and offline, that can help to further your knowledge. With practice and dedication, understanding these concepts can be a breeze.
