Every serious programmer should take the subject of algorithms seriously if they want to make a decent income. Algorithms are fundamental in computer science and are useful in almost all industries.
In this article, we have prepared five algorithms that every programmer must know.
Dynamic Programming (DP)
This is an algorithmic technique that solves complex problems by dissecting it into less complex problems (sub-problems). This method involves using the different results obtained from the sub-problems to find the answer to the complex problem. This technique is related to graph algorithms.
There are two major characteristics of dynamic programming, which include:
- Optimal Substructure Property: When the optimal solution to the particular problem is gotten from using the optimal solutions of the other subproblems.
- Overlapping Subproblems: This involves finding the solution by solving the particular sub-problem numerous times.
DP algorithmic technique has two methods used to solve problems, and these include:
- Top-down with Memorization: This method is used when solving a larger problem by repeatedly getting the solution to smaller sub-problems. When the result of the smaller sub-problem is found, the answer is cached in order not to repeatedly solve the exact same sub-problem if it’s called multiple times. Here, we can quickly return to the already saved result to use it. This is what is termed Memorization.
- Bottom-up with Tabulation: This method is opposite to the top-down memorization, and it avoids recursion. In this method, we first solve all the affiliated sub-problems by typically filling the n-dimensional table. From the result of the table, we then proceed to solve the original problem.
Hashing is the process where a particular key is converted into a different value. A hush function through the use of a mathematical algorithm is used to generate a different value. Hash values are usually stored in a Hash Table, or Hashmap, which is data structures.
This technique is the most commonly used when trying to find accurate data by key or ID. It is central in the world of error detection, cryptocurrency, efficient look-up, and cache management. All the hash functions are closely related and are very similar in nature.
You know a hash function is safe when it is difficult to convert the original data back to the hash value.
When it comes to hashing, two keys can produce the same hash. The term used to describe this phenomenon is known as Collision.
Pattern Matching And Parsing
This is one of the most important problems that always arise in computer science. A lot of times, when we conduct a search in a word file or notepad for a string, the results are shown through pattern searching algorithms. There have been various researches conducted because of this particular problem; however, today, we will be discussing two of the basics every serious programmer should know:
- KMP Algorithm: KMP stands for the Knute-Morris-Pratt algorithm. This problem is handy in a lot of different areas, such as document matching, DNA matching, pattern recognition, and so on. It is used to match in cases where short patterns have to be matched in a long string.
- Regular Expression: This comes in handy when trying to manipulate a reflex-based text processing tool or source code in a text editor. A lot of languages used for programming use related constructs such as keywords, strings, and comments. However, frequently, there are slight variations, which makes it more challenging to use the correct reflex.
Understanding pattern matching and parsing, however, helps to filter data that is poorly structured. This is one of the reasons Perl is very popular.
Data frequently never come in the right order; therefore, before making use of such data and applying any algorithm that will have meaning, you will have to sort such data. Sorting has proven to be quite a complex topic, and the most studied when it comes to computer science.
There are different types of the sort, but we will be defining five in this article.
- Merge Sort: This has to do with divide and conquer. It is a very efficient comparison-based and general-purpose sort.
- Quick Sort: You partition the elements based on a pivot. Once you select the pivot, for the first half, make sure the elements are less than the pivot, and in the second half, the elements must be greater than or equal to the pivot. A pivot is a random element you select.
- Radix Sort: If you know the range of values the array you need to sort has, you can create another array b to keep a count of the number of times a value occurs in array a. Then to sort, you go through b and add to the array can element as many times as it occurs. Then c should be sorted.
- Bucket Sort: This is an algorithm that means distributing the elements contained in an array into different buckets.
- Heap Sort: The heap is a structure that helps you get the greatest or smallest element quickly and efficiently. What you do here is to put all the elements in a heap, then you keep removing the smallest element until the heap is empty.
In computer science, a search algorithm is used to find and retrieve an element from a data structure where it was stored. There are generally two categories of these search which are:
- Linear Search: In linear search, you go through all the elements in the array order looking for a particular element, and if you find it, you return the position in the array, and if you don’t find it, you can return a value like -1. Another name for this search algorithm is called a sequential search.
- Binary Search: Binary search only works when the array is sorted. It involves checking the center of the search structure to see if the center is greater than or equal to the element you are trying to find. If it is greater than, then you search in the second half, and if it is less than you search in the first half, if it is equal to you, return the position.
Mastering algorithms is very important for a programmer if they want to be competitive and sought after by profitable companies. You must become very proficient in the algorithms mentioned above and know when to apply them.
Thomas Lore is a 23-year old writer, who is currently working for Online Writers Rating. Also, Thomas is a creative and diligent freelance blogger, who is always seeking for new ways to improve himself. Thomas is very versatile and he wants to reach the tops with his writing skills.