essay about data structures

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Data Structures and Algorithms

My understanding on data structures and algorithms goes mainly to the three books that I read as a beginner and continue to consult the books whenever I need guidance.

Data Structures Using C by Aaron M. Tenenbaum
Data Structures, Algorithms, and Program Style Using C by James F. Korsh
Data Structures and Algorithms with Object-Oriented Design Patterns in C++ by Bruno R. Preiss

Technology changes quickly and new languages keep surfacing while old ones become obsolete. However, the basic knowledge I captured on data structures and algorithms through these books is what I can rely on for other languages as well since the fundamentals remain the same.

Seniors, peers and my online community of programmers have helped me during my career. Without their help and guidance, I wouldn’t have been able to resolve half the practical problems that I faced while programming. Working as a Web Developer for an IT company called “The Academics”, I have used C# as my programming language.

I learnt about different data types such as boolean, integer types (short, signed and unsigned integer, long, etc.), floating point types (float, single, double, long double, etc.) string types (string, char), etc., with each language having its own version of data types but the classification is more or less on similar lines. One of the important things I learnt is to understand how much memory each data type occupies in whatever language you are working with and when and how to use them in your programming. My first lesson on data types was when I used an integer value where a long was required. So for all future programs, I always used a higher data value than required that is using long instead of integer. One of my seniors pointed out how that hogged up the memory unnecessarily and why it is essential to understand and consider the most appropriate data type rather than using the minimum sized or maximum sized data type.

I frequently used data structures to temporarily store sets of data together to be able to access them with a single variable and perform operations on them. Arrays, linked lists, stacks, queues, hash tables are common examples in many languages while ArrayList, HashSet, Dictionary have been new in C#. Using various algorithms, one can manipulate the data contained in these data structures. Some examples are searching the data, sorting them, etc.

Arrays are the simplest and most commonly used data structure in almost all languages. In C#, an array is a list of objects of the same type and fixed length. List, on the other hand, is a dynamic array whose length can be varied as required. The object type needs to remain the same however. ArrayList goes a step further – it is a dynamic array whose length can be varied as required, and it also supports storing of different types of objects in the same ArrayList. Due to this, there is need of casting the retrieved values back to their original type before they could be used.

LinkedList also stores series of objects; however, instead of indexing the list, each object is linked to each other i.e. each object has a reference each to the next object and previous object. Dictionary data structure allows making the index keys which can be of any type of object unlike ArrayList, for example, which automatically makes sequential integer keys. Thus, keys can actually be meaningful and link it to the object for easy retrieval. Hashtables are similar to Dictionary except that the keys are generic objects rather than typed which makes it faster than Dictionary data structure. A new data structure introduced in latest C# versions is HashSet which is similar to List data structure except that it does not allow duplicate values.

Stack data structure is similar to ArrayList but works on the Last-In-First-Out (LIFO) behavior and is particularly useful when it is required to “retrace your steps”. Queue, on the other hand, is based on First-In-First-Out (FIFO). This can be used when, for example, you want to serve clients on the basis of who came first.

The typical operations include adding or removing data, retrieving data, manipulating data, displaying in a particular format, sorting data, etc.

A common algorithm for sorting arrays is bubblesort method based on swapping. One variable is compared with the other and their places are switched with the help of a temporary variable. C# also provides a Sort function for Arrays to sort the list directly. The most efficient method, however, is to use the interface IComparable and the function CompareTo to compare the objects and sort accordingly.

The source files in C language are usually given the extension “.c” and “.h”, one for the source file and the other for the header files. For C++, the files use the “.cpp” extension and “.h” for the declaration or header files. While file organization has no significance to the C# compiler i.e. an entire project could be merged into one.cs file and it would still compile (except for preprocessor statements). However, it makes sense to have one type in one file making the filename matching the name of the class and the file’s directory matching the name of the class’s namespace.

In C#, the abstract class Stream forms the parent class for performing file operations and processing and it is comes under the System.IO namespace. With the help of this abstract class, one can store data to a stream or retrieve data from a stream. Stream class acts as the parent class for inherited classes which consists of the actual implementation to carry out the necessary operations. Typical stream operations usually require a combination of classes, for example, some classes are used to create a stream object, some others to write data back to the stream, and another set to read the data from the stream.

One such stream is file streaming that consists of performing one of the routine operations on a file, such as creating, opening, editing, appending, etc. A basic class to help with the file creation and opening is FileStream. A FileStream object is used to get a stream ready for reading, writing, and other processing. Another class, BinaryWriter class is used to write values of primitive data types such as int and float in C#. TextWriter is another abstract class for writing data to the streams. StreamWriter, derived from TextWriter is used to write a character to a stream. Similarly, TextReader is an abstract class and StreamReader is derived from that class and is used to perform reading operations from a stream.

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DSA Tutorial

Linked lists, stacks & queues, hash tables, shortest path, minimum spanning tree, maximum flow, time complexity, dsa reference, dsa examples, introduction to data structures and algorithms.

Data Structures is about how data can be stored in different structures.

Algorithms is about how to solve different problems, often by searching through and manipulating data structures.

Theory about Data Structures and Algorithms (DSA) helps us to use large amounts of data to solve problems efficiently.

What are Data Structures?

A data structure is a way to store data.

We structure data in different ways depending on what data we have, and what we want to do with it.

First, let's consider an example without computers in mind, just to get the idea.

If we want to store data about people we are related to, we use a family tree as the data structure. We choose a family tree as the data structure because we have information about people we are related to and how they are related, and we want an overview so that we can easily find a specific family member, several generations back.

With such a family tree data structure visually in front of you, it is easy to see, for example, who my mother's mother is—it is 'Emma,' right? But without the links from child to parents that this data structure provides, it would be difficult to determine how the individuals are related.

Data structures give us the possibility to manage large amounts of data efficiently for uses such as large databases and internet indexing services.

Data structures are essential ingredients in creating fast and powerful algorithms. They help in managing and organizing data, reduce complexity, and increase efficiency.

In Computer Science there are two different kinds of data structures.

Primitive Data Structures are basic data structures provided by programming languages to represent single values, such as integers, floating-point numbers, characters, and booleans.

Abstract Data Structures are higher-level data structures that are built using primitive data types and provide more complex and specialized operations. Some common examples of abstract data structures include arrays, linked lists, stacks, queues, trees, and graphs.

What are Algorithms?

An algorithm is a set of step-by-step instructions to solve a given problem or achieve a specific goal.

A cooking recipe written on a piece of paper is an example of an algorithm, where the goal is to make a certain dinner. The steps needed to make a specific dinner are described exactly.

When we talk about algorithms in Computer Science, the step-by-step instructions are written in a programming language, and instead of food ingredients, an algorithm uses data structures.

Algorithms are fundamental to computer programming as they provide step-by-step instructions for executing tasks. An efficient algorithm can help us to find the solution we are looking for, and to transform a slow program into a faster one.

By studying algorithms, developers can write better programs.

Algorithm examples:

Finding the fastest route in a GPS navigation system
Navigating an airplane or a car (cruise control)
Finding what users search for (search engine)
Sorting, for example sorting movies by rating

The algorithms we will look at in this tutorial are designed to solve specific problems, and are often made to work on specific data structures. For example, the 'Bubble Sort' algorithm is designed to sort values, and is made to work on arrays.

Data Structures together with Algorithms

Data structures and algorithms (DSA) go hand in hand. A data structure is not worth much if you cannot search through it or manipulate it efficiently using algorithms, and the algorithms in this tutorial are not worth much without a data structure to work on.

DSA is about finding efficient ways to store and retrieve data, to perform operations on data, and to solve specific problems.

By understanding DSA, you can:

Decide which data structure or algorithm is best for a given situation.
Make programs that run faster or use less memory.
Understand how to approach complex problems and solve them in a systematic way.

Where is Data Structures and Algorithms Needed?

Data Structures and Algorithms (DSA) are used in virtually every software system, from operating systems to web applications:

For managing large amounts of data, such as in a social network or a search engine.
For scheduling tasks, to decide which task a computer should do first.
For planning routes, like in a GPS system to find the shortest path from A to B.
For optimizing processes, such as arranging tasks so they can be completed as quickly as possible.
For solving complex problems: From finding the best way to pack a truck to making a computer 'learn' from data.

DSA is fundamental in nearly every part of the software world:

Operating Systems
Database Systems
Web Applications
Machine Learning
Video Games
Cryptographic Systems
Data Analysis
Search Engines

Theory and Terminology

As we go along in this tutorial, new theoretical concepts and terminology (new words) will be needed so that we can better understand the data structures and algorithms we will be working on.

These new words and concepts will be introduced and explained properly when they are needed, but here is a list of some key terms, just to get an overview of what is coming:

Where to Start?

In this tutorial, you will first learn about a data structure with matching algorithms, before moving on to the next data structure.

Further into the tutorial the concepts become more complex, and it is therefore a good idea to learn DSA by doing the tutorial step-by-step from the start.

And as mentioned on the previous page, you should be comfortable in at least one of the most common programming languages, like for example JavaScript , C or Python , before doing this tutorial.

On the next page we will look at two different algorithms that prints out the first 100 Fibonacci numbers using only primitive data structures (two integer variables). One algorithm uses a loop, and one algorithm uses something called recursion.

Click the 'Next' button to continue.