Data Structures and Algorithms Essentials: A Programmer’s Guide
Summary
Many budding programmers might not even know what data structures and algorithms are. However, they have already used them in one or the other ways. Data structure and algorithms are essential for programming, and all beginners should know what they are.
This blog tries to bust the myth that DSA is a difficult concept. It includes the most beneficial data structures and essential algorithms. Additionally, these details will assist you in clearing interviews and enhancing your competitive programming skills.
Introduction to Data Structures and Algorithms
Data Structures and Algorithms are the backbone of efficient computer programs. It enables the organization and manipulation of data for optimal problem-solving. Let’s discuss each of them one by one.
What is Data structure?
A data structure is a system to keeps data in the computer's memory while an algorithm is executed. Even if you are new to programming, you probably have seen data structure uses. Now see the previous example of adding several numbers. You would most likely use an array to store the numbers before processing the addition. These values will be there in the computer's RAM while your algorithm is being run.
Besides arrays, there are many other data structures that each have a specific function. However, you should use them correctly to improve the performance of your algorithms.
Types of Data Structure
They are the simplest and most common data structures. You can define Arrays by the ease you can access the elements by index (position). Additionally, they are a continuous block of memory. Moreover, depending on the programming language, they comprise elements of the same type.
Stack formalizes the idea of controlled access collection. It is an abstract data type. The restriction refers to the Last In, First Out (LIFO) principle. Thus, the first piece you delete from the stack is the one that was most recently added. Furthermore, arrays and linked lists are two ways to implement stacks.
Like arrays, a linked list in data structure is a type of linear data structure. The main difference between linked lists and arrays is that linked list elements are not kept in consecutive memory regions. But, it consists of nodes, which are objects that keep a record. They record the value of the current element and a reference to the element after it.
Furthermore, a linked list whose nodes are all connected in a circle is a circular linked list. The start node and the last node in a circular linked list connect together, forming a circle.
Maps or dictionaries, are abstract data types containing a set of keys and a set of values. Each key also holds a value.Whereas, a specific kind of map is a hash table. Here, the key is hashed, and the resulting hash tells the location of the value. There is also a hash function to construct a hash code into an array of buckets or slots.
A queue is a different data type from the restricted access collection, similar to the stack. A circular queue is an extended form of a standard queue. Here, the start and last elements have an interconnection. Hence, it results in a structure resembling a circle.
A tree is an undirected graph that is most acyclic. A tree data structure is least linked (if you add one edge, the graph will no longer be acyclic). It also has the least connection (if you remove one edge). Apart from these, there are many other types of data structures like heaps, tries, graphs, Disjoint Set Union, etc.
What are Algorithms?
Algorithms make up the majority of the code you create. So, an algorithm is a concept where you start with an initial input and change it by carrying out a set of instructions. These instructions work one at a time and produce a final result. A practical example of an algorithm would be asking for several numbers from the user. Further, reading those numbers, adding them together, and then returning the sum.
Types of Algorithms
After seeing data structures, let's see the types of algorithms in our discussion for data structures and algorithms.
Divide and Conquer (DAC) is not a single algorithm in and of itself. However, it is essential to resolve issues that you can break down into smaller, more manageable sub-issues. Although these issues relate to the primary issue.
A sorting algorithm helps in rearranging the elements (from an array or list). It works using a comparison operator on the elements. Thus, a sorted array is in ascending order when we mention it during data structures and algorithms.
You can find a data structure's elements using searching algorithms, which can also return them. There are a few different search techniques, but linear and binary searches are the most common.
- Knuth-Morris-Pratt Algorithm
The Knuth-Morris-Pratt (KMP) algorithm is an effective method for resolving the pattern-matching issue.
The Greedy technique can be useful for issues where optimization is essential. Moreover, you can use it if you need to follow the path from the local to the global optimal solution. Thus, the best answer at each stage leads to the best answer overall via Greedy.
DP, or dynamic programming, is a strategy to divide and conquer. Additionally, it divides the issue into related subproblems. However, they have an interconnection and dependency on one another rather than a separate resolution.
- Longest Common Subsequence
A sequence that appears in the same relative order but is not always contiguous is a subsequence. You can use this algorithm when you need to find the length of the longest subsequence present in two sequences.
Conclusion
Data Structures and algorithms (DSA) serve as the basis of the most cutting-edge technological ideas. Thus, they are crucial to both developers with experience and those looking for jobs. By mastering DSA, you may solve previously unsolved challenges and add value to any tech organization.
Moreover, you can improve your work using your computational and algorithmic thinking. DSA helps you increase the efficiency, extensibility, and reliability of your code by knowing them.
Frequently Asked Questions
Q.Is the queue a LIFO or FIFO?
Ans. A queue is a FIFO (First-In-First-Out) data structure, where the first element added is the first to be removed.
Q.What is stack and queue?
Ans. A stack is a data structure with a collection of elements and operations. These operations can push (add) and pop (remove) elements from the top of the stack. Whereas a queue is a data structure with a collection of elements and operations to enqueue (add) elements at the back of the queue. They can also dequeue (remove) elements from the front of the queue.
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