Software Development Fundamentals: What do I need to know?
Software development is the process of creating software applications. It is a complex and challenging process, but it is also incredibly rewarding. If you are interested in learning how to develop software, there are a few fundamental concepts that you need to know.
In this article, we will discuss the following software development fundamentals: data structures, algorithms, databases, APIs, web services, object-oriented design and software testing. Let’s get started.
Data Structures
What are data structures?
Data structures are a fundamental part of any programming language, they are useful for storing and manipulating data as well as solving problems, take for example implementing the undo/redo functionality, which allows users to reverse their actions if they make a mistake, in software applications, the stack data structure is used or the task scheduler on your operating system that makes use of the queue data structure, how about the tree data structure that is used to store your computer's directory. All these won’t be possible without the help of data structures. Let’s take a look at some of these data structures and how they can be implemented.
Stacks
A stack is a data structure that follows the last-in, first-out (LIFO) principle. This means that the last item that was added to the stack is the first item that will be removed. Stacks are often used to implement recursive functions and to solve problems that require backtracking. Here is a code snippet for implementing a stack in Python:
class Stack:
def __init__(self):
self.items = []
def push(self, item):
self.items.append(item)
def pop(self):
return self.items.pop()
def is_empty(self):
return len(self.items) == 0
Queues
Just like queues in real life, the queue data structure is based on the first-in, first-out (FIFO) principle, i.e. the first item that is added to the queue will be the first item that will be removed. Most times, queues are used to implement solutions to problems that require a first-come, first-served approach such as web servers or messages in a messaging system. Here is a code snippet for implementing a queue in Python:
class Queue:
def __init__(self):
self.items = []
def enqueue(self, item):
self.items.append(item)
def dequeue(self):
return self.items.pop(0)
def is_empty(self):
return len(self.items) == 0
Linked lists
Linked lists are a flexible data structure that consists of a sequence of nodes. Each node contains a data element and a pointer to the next node in the list. Linked lists can be singly linked (each node only points to the next node), doubly linked (each node points to the next node and the previous node) or circular (the last node points back to the first node). Here is a code snippet for implementing a linked list in Python:
class Node:
def __init__(self, data):
self.data = data
self.next = None
class LinkedList:
def __init__(self):
self.head = None
def add(self, data):
new_node = Node(data)
if self.head is None:
self.head = new_node
else:
current_node = self.head
while current_node.next is not None:
current_node = current_node.next
current_node.next = new_node
def print(self):
current_node = self.head
while current_node is not None:
print(current_node.data)
current_node = current_node.next
Hash Table
A hash table is a data structure that maps keys to values. The keys are usually strings or integers, and the values can be any type of data. Hash tables are a very efficient way to store and retrieve data because they allow you to access the data by its key.
Trees
A tree is a hierarchical data structure that consists of a root node and a set of child nodes. Each child node can have its child nodes, and so on. The nodes represent data, and the edges represent the relationships between the data. Trees can be used to represent a variety of data, such as family trees, file systems, and mathematical expressions. Here is a code snippet for implementing a tree in Python:
class Tree:
def __init__(self, data):
self.data = data
self.children = []
def new_child(self, child):
self.children.append(child)
def print(self):
print(self.data)
for child in self.children:
child.print()
Graphs
A graph is a data structure that is made up of vertices and edges. The vertices represent data, and the edges represent the relationships between the data. Graphs can be used to represent a variety of data, such as social networks, transportation networks, and electrical circuits. Here's a code snippet to implement a graph in Python:
class Graph:
def __init__(self):
self.adjacency_list = {}
def new_node(self, node):
if node not in self.adjacency_list:
self.adjacency_list[node] = []
def new_edge(self, node1, node2):
if node1 not in self.adjacency_list:
self.new_node(node1)
if node2 not in self.adjacency_list:
self.new_node(node2)
self.adjacency_list[node1].append(node2)
self.adjacency_list[node2].append(node1)
def dump_graph(self):
for node, neighbors in self.adjacency_list.items():
print(node, neighbors)
if __name__ == "__main__":
graph = Graph()
graph.new_node("A")
graph.new_node("B")
graph.new_node("C")
graph.new_edge("A", "B")
graph.new_edge("A", "C")
graph.new_edge("B", "C")
graph.dump_graph()
These are just a few of the several data structures used in programs and even in everyday life. Each data structure has its strengths and weaknesses, so it is important to choose the right data structure for the problem being solved. You wouldn’t want to use stacks or queues to store the directory structure of your computer, that would be a terrible idea. You may be wondering, how do I choose the right data structure for my program or project, don’t worry, we’ll get to that.
Algorithms
What is an algorithm? An algorithm is a stepwise list of instructions that tells a computer how to solve a problem or perform a task. To address problems, algorithms and data structures are used together. The data structure offers a means of storing the data required to carry out the method, and the algorithm specifies the actions that must be completed. For example, the binary search algorithm is used to traverse the binary tree data structure.
Here are some of the most common types of algorithms:
Searching algorithms: Search algorithms are used to find a specific item in a data structure. Some common search algorithms include binary search, linear search, and hash table search.
Sorting algorithms: Sort algorithms are used to order a data structure. Some common sort algorithms include quicksort, merge sort, and heap sort.
Time Complexity
Time complexity is one of the methods used by programmers to determine and compare the efficiency of different algorithms, it is used to measure how long it takes an algorithm to run, based on the size of its input. It is usually expressed mathematically using the “big O notation”. It's not as complex as it sounds, here are some of the most common Big O notations:
O(1) also known as Constant time - The algorithm's execution time is independent of the size of the input.
O(log n) also known as Logarithmic time - The algorithm's execution time increases logarithmically as input size increases.
O(n) also known as Linear time - The algorithm's execution time increases linearly with the size of the input.
O(n^2) also known as Quadratic time - The algorithm's execution time increases in a quadratic relationship with input size
Space Complexity
Space complexity is also used to determine the efficiency of algorithms, but in this case, it measures how much memory an algorithm uses, based on the size of its input. It is also typically expressed using big O notation.
Both time complexity and space complexity should be taken into account while developing, evaluating, and selecting algorithms. The goal is to select an algorithm that has the lowest time and space complexity for the problem being solved. Sometimes (in fact most times) this is not possible so comprises have to be made to have the best solution to the problem.
Databases
A database is a collection of data that is organized so that it can be easily accessed, managed, and updated. Simply put a database is where all your data is stored, including customer information, financial records, business records, transactions, you name it. Databases are the best tool to store large amounts of data, they are also helpful when it comes to managing data, e.g. performing CRUD (create, read, update and delete) operations. Most times, sensitive data needs to be collected and stored effectively, databases help to preserve and protect your data from unauthorized access, by using a variety of security tools and measures.
Types of databases
Databases are largely classified into two main types namely: relational databases and non-relational databases. Relational databases store data in tables, they are the most common type of database. Each table is made up of fields (columns) and records (rows). Data that is related to one another can be stored and retrieved very effectively using relational databases. What happens when you need to store data that isn’t structured/related? Non-relational databases are here for you, they are designed to effectively store and retrieve large amounts of unstructured data.
Database management systems
To be able to perform any task on a database, you need a database management system (DBMS). A DBMS software allows you to create, manage, and access databases. Several DBMSs are available today, some of the favourites include MySQL (relational) PostgreSQL (relational), MongoDB (non-relational), and Redis (non-relational).
ACID
ACID stands for Atomicity, Consistency, Isolation, and Durability, it is a set of properties that ensures integrity, reliability and consistency in database operations.
Atomicity ensures that database transactions are treated as an atomic unit of work. It ensures that either every operation within a transaction succeeds, or none of them do and if any portion of it fails, the transaction is rolled back to its initial state.
Consistency guarantees that all the data in the database is correct and that the relationships between the data are maintained as they should be before and after a transaction occurs.
Isolation makes sure that database transactions are separated from each other, in order words, the changes made by one transaction are not visible to other transactions until the first transaction has been completed, this prevents interference between transactions.
Durability guarantees that once a transaction has been committed, the changes made by the transaction are permanent (even if there is a failure) the changes made by the transaction will not be lost.
The ACID properties are important for ensuring the reliability and consistency of database transactions. They help to ensure that data is not corrupted and that transactions are completed successfully even in the event of failures.
Transactions
A transaction is a unit of work that is performed in a database management system (DBMS). Transactions are used to ensure that data is consistent and reliable. Transactions are an important part of DBMS. They help to ensure that data is consistent and reliable. Transactions are used in a variety of applications, including banking, e-commerce, and inventory management.
APIs and Web Services
APIs
An Application Programming Interface (API) is a set of functions and procedures that allow two pieces of software to interact with each other. It is a way for one application to request a service from another application, and for the second application to respond to that request. It acts as the middleman between two applications. APIs are used widely in web apps and mobile apps to provide payment services (e.g. Stripe API), location services (Google Maps API) etc.
Web Services
A web service is an API that can only be used online. Web services use a variety of industry-standard protocols and technologies, such as HTTP, XML, and SOAP, to interact with other applications. There are two main types of web services:
SOAP web services: Simple Object Access Protocol is a protocol that uses XML to encode requests and responses. SOAP web services are more complex to develop and use than other types of web services, but they offer a wider range of features.
RESTful web services: Representational State Transfer (REST) is an architectural style for web services that use HTTP methods (GET, POST, DELETE, PUT) to represent different operations. RESTful web services are simpler to develop and use than SOAP web services, but they offer a more limited set of features.
Object-Oriented Design
Object-Oriented Design (OOD) is a software design technique that uses objects to model real-world entities and their interactions. OOD is based on the following principles: encapsulation, abstraction, polymorphism and inheritance.
OOD principles are not always easy to follow, but they can help to create object-oriented designs that are more effective and efficient. By following these principles, developers can create software that is easier to understand, maintain, and reuse.
Software Testing
Software testing is the process of inspecting and verifying that a software application or product performs as intended. It is a crucial step in the software development lifecycle. It helps to guarantee that the program is error-free and meets user requirements.
Software testing comes in a wide variety of forms, each with unique goals and tactics. The following are a few of the most typical test types:
Several types of testing can be performed on a system, here are a few of the frequently performed ones:
Unit testing: This kind of testing concentrates on specific pieces of code, like functions or classes. Unit testing is used to make sure that every piece of code functions as it should.
Integration testing: This kind of testing is concerned with how various pieces of code communicate with one another. Integrity testing's objective is to validate the proper interaction of the software's various components.
System testing: This kind of testing is concerned with the overall functionality of the software system. Its objective is to confirm that the program satisfies its specifications and is usable by its intended audience.
Acceptance testing: The client or end-user does this kind of testing to ensure that the program satisfies their needs.
As previously discussed, software testing is a crucial step in the software development lifecycle that ensures the product is error-free and meets user requirements. Testers can help to find and fix issues early in the development process by carrying out several tests, which can ultimately save time and money, lead to better quality end products and improve customer satisfaction.
Conclusion
In this article, we have discussed the fundamental concepts of software development, including data structures, algorithms, databases, APIs, web services, object-oriented design, and software testing. These concepts are the building blocks of software, and by understanding them, you will be well on your way to becoming a successful software developer.
Of course, there is much more to software development than just these fundamentals. There are many other concepts and skills that you will need to learn to be a successful software developer. However, the fundamentals that we have discussed in this essay provide a solid foundation for your software development journey.