How can understanding OOP improve your problem-solving skills?

Understanding Object-Oriented Programming (OOP) enhances problem-solving by promoting modular thinking, code reuse, and abstraction. For example, imagine you're developing a banking application. Using OOP, you can create classes for accounts, transactions, and customers. This modular approach simplifies problem-solving by breaking down complex tasks into manageable components, making the code more organized and maintainable.

Most recently, I have been working with a niche scripting language that does not allow for OOP. However, my understanding of OOP still helps to organise procedural processes in a way that makes sense. The concept of 'objects' is a useful tool for writing code even when you are working outside of the OOP paradigm. It becomes a planning framework for how to best abstract and encapsulate data and functions as independent units capable of being reused in different contexts.

It took me some time to grasp the idea of classes and to distinguish between classes and objects, but with continuous practice it began to make more sense. Learning OOP is like learning TypeScript, it may seem like a waste of time at first, but as you use it frequently, you'll see how much easier and faster development can be, how well-organized projects can be to prevent needless bugs, how repetitive work can be reduced, and how much shorter it can take to release new features. You will end up not wanting to have it any other way. Even more intriguing is the fact that OOP is not language-specific; rather, it is a valuable skill applicable to all languages; implementations may vary, but the idea is always the same.

OOP encourages Me to think in terms of objects, which are self-contained pieces with their own properties and behaviors. This approach allows me to break down complex problems into smaller, manageable parts (modules) that can be developed, tested, and maintained independently. This modular thinking aids in simplifying complex systems and focusing on individual components one at a time. Personally I have seen Object-Oriented Programming (OOP) concepts are particularly valued in sectors like banking and security and more Some of the reasons are Security and Data Protection , Complexity Management, Maintainability, Reusability, Reliability, Scalability.

A very simple example would be - I have a property CreatedAt in all of my classes. We should not allow anyone to modify it from outside the class to prevent setting any wrong value to it. So this property's s setter method should be private which solves the problem. In C# we do "public DateTime CreatedAt; { get; private set; }

Encapsulation restricts direct access to data, preventing unintended modifications and ensuring data integrity. This enables clearer code organization and maintenance, as changes to one part of the codebase don't necessitate modifications elsewhere. Encapsulation also simplifies debugging and enhances code reusability, fostering more efficient problem-solving.

Encapsulation is a fundamental concept of OOP that involves bundling the data (attributes) and code acting on the data (methods) into a single unit or class. It also restricts direct access to some of an object's components, which can prevent the accidental modification of data. This makes the code more modular and easier to manage, as well as enhances the security of the application.

One benefit of Encapsulation is peeking object's data private, preventing accidental changes and improving security. But I think the greatest benefit of Encapsulation is making code more readable by hiding complex series of tasks. Organize code, make it readable and you will find that you don't need to read every method thoroughly, which greatly helps in finding bugs.

By defining clear interfaces and hiding implementation details, abstraction simplifies problem analysis and solution design. This leads to more concise and maintainable code, as developers can work at higher levels of understanding without getting bogged down in implementation specifics. Abstraction facilitates code reuse and promotes scalability, enabling more efficient problem-solving across various contexts.

Abstraction allows you to hide complex reality while exposing only the necessary parts. It helps in reducing programming complexity and effort. By using abstract classes and interfaces, you can define templates that enable you to focus on higher-level problems, ignoring the details at the moment.

Human brain inevitably thinks in abstract concepts, therefore code we write is also dependent on them. We do not think in the series of small steps when we build a house, but instead, we consider the overall design, functionality, and structure, translating these high-level ideas into detailed plans and actions. The same is when we write code; we start with a broad concept of what the program should do and then break it down into smaller, manageable components to implement.

Be careful to not overuse it! Inheritence can be a very powerful strategy to tackle complexity. However, it also introduces a lot of coupling into your system, especially if done wrong. When learning about OOP, we often work with simplified examples like "Dog inherits from Animal". These examples are good to illustrate the Inheritence principle, but are definitely not something you want to use in the real world. I tend to avoid inheritence for business or domain concepts, as they often have different reasons to change. Coupling different concepts together via inheritence because they seem to "fit" into this principle makes the system often more difficult to understand and maintain. Inheritance works well for technical complexity though!

By creating parent-child relationships, developers can inherit behavior and attributes, reducing redundancy and promoting efficient problem-solving. Inheritance enables the creation of specialized classes that extend functionality while maintaining common features, fostering modular and scalable solutions. Additionally, inheritance supports polymorphism, allowing objects to be treated interchangeably, further streamlining problem-solving through flexible design.

Inheritance helps with organization and clarity. It makes your code more logical by structuring it into a hierarchy. This mirrors how things work in the real world, which makes it easier for other developers (or even future you) to understand what's going on. But it's not all rainbows and sunshine. Inheritance can lead to some tricky situations. For one, it creates a tight coupling between classes, meaning changes to the base class can ripple out and affect all the subclasses, potentially causing unexpected problems. Also, if you're not careful, you can end up with really complex inheritance trees that are hard to untangle and debug.

Inheritance lets one class adopt the properties and methods of another. Strategies for using inheritance include creating a common base class for similar objects, thus promoting reusability and reducing redundancy. This is particularly useful when dealing with a hierarchy of objects that share common characteristics, allowing you to generalize your problem-solving approach.

One common thing I do with inheritance in all my projects is creating an auditable entity. class Audit { public DateTime CreatedAt; public DateTime? LastModifiedAt; public DateTime? DeletedAt; } you can inherit all your business entities from this Audit entity. How does it help? ° Set CreatedAt when the entity is created. ° Update LastModifiedAt when anything changed within the entity. ° Set DeletedAt when the entity is soft deleted ** If the entity is restored from recycle bin, set Deletedt = null again! There you go!

Polymorphism allows an object to have multiple forms or accept different parameters as needed i.e a person, can be a student, doctor, sister, friend et al. In each of these roles, Ithey require a different parameter to enable them function as needed. This can be implemented with either method overloading or parent-child inheritance. How does this help us in development? It promotes flexibility in class use-cases, makes the implementation flow easier to understand and modify, eliminates unnecessary repetitions and the fewer the repetitions, the lighter the code, the faster it executes, and the less processing and storage memory it uses. If this concept is implemented appropriately and in the right context, the advantages trickles down.

Polymorphism allows objects of different types to be treated uniformly through a common interface, enabling more generic and adaptable solutions. By abstracting away specific implementations, polymorphism simplifies problem-solving by focusing on behaviors rather than concrete types. This fosters modular and reusable code, as components can interact seamlessly without knowledge of each other's exact types. Polymorphism also facilitates code maintenance and scalability, as new behaviors can be added without modifying existing code, promoting efficient problem-solving across diverse scenarios.

Polymorphism allows methods to do different things based on the object it is acting upon. This means that a single interface can represent different underlying forms (data types). By using polymorphism, you can design and implement systems that are easily extendable and modifiable—flexibility that is essential in problem-solving.

Polymorphism helps me a lot when I want to expose an api with common parameters and methods. So I can develop a generic interface with several custom implementations, each one will be used at runtime depending on custom configuration. All the application built at the top of the interface will remain the same independent of the implementation used and I can add all the implementations I want without worrying about to change the application behavior

By familiarizing oneself with patterns like Singleton, Factory, and Observer, developers can leverage established approaches to tackle recurring problems efficiently. Design patterns promote code readability, maintainability, and scalability by offering well-defined structures and relationships between objects. They encourage modular design, code reuse, and flexibility, ultimately leading to more robust and adaptable solutions, thus improving problem-solving skills in various development scenarios.

OOP has several different design patterns, the most popular ones being factory, decorator, singleton, and adapter patterns, among others. Every one of these patterns has a function or application and prioritizes the use of a certain OOP technique. While using and defining a certain design pattern is the best and easiest to maintain when working on a project, this isn't always the case. It may be necessary to use multiple DPs for a large project. In any case, make sure you only apply a pattern if and when it improves your code, making it readable and maintainable by other developers, so as not to undermine the goal of using OOP.

Familiarising with different design patterns is crucial when developing using a OOP language, but even more important is knowing when to apply them, it’s easy to fall in the trap of always finding a way to use a specific design pattern. Understanding when to apply them is far more challenging and it makes the difference between a more experienced developer and a beginner. Design patterns should not be the goal if they don’t actually help you in the context in which they are used. So learn them, as they are definitely useful, and give yourself time to understand when to apply them.

Design patterns are standard solutions to common problems in software design. Learning about OOP design patterns such as Singleton, Observer, Decorator, Factory, and Strategy can enhance your problem-solving skills by providing proven techniques that you can employ in your code. These patterns provide templates on how to solve common problems, improve code readability, and make maintenance easier.

When applying OOP concepts, consider the principles of SOLID (Single Responsibility, Open/Closed, Liskov Substitution, Interface Segregation, and Dependency Inversion) which are crucial for creating effective software architecture. Understanding these principles can help in creating more durable and flexible software. Also, remember that while OOP is powerful, it's not the only paradigm available. Combining OOP with other programming paradigms (like functional programming) depending on the problem context can lead to more innovative solutions.

In Software development, the first step to solve a problem is "designing the domain entities", "understanding the relationships between the domain entities" and "how the entities cover the business requirements". Once the Domain entities are designed, we can move onto building the business part of the application, the endpoints, bla bla blah. So when you think of problem solving as solving a real world business problem, your first footstep is OOP design of the system. (OOD)

It can enhance problem-solving by promoting modular thinking. Breaking down complex systems into smaller, manageable objects fosters clearer problem comprehension. Encapsulation ensures data integrity, reducing errors. Inheritance facilitates code reuse, minimizing redundancy and promoting efficiency. Polymorphism allows for flexible and scalable solutions, adapting to changing requirements seamlessly. This approach encourages abstraction, enabling focus on high-level design rather than implementation details. Ultimately, OOP encourages a structured, organized approach to problem-solving, leading to more robust, maintainable, and scalable solutions.

OOP will certainly help in atomizing the problem into smaller parts, and addressing it incrementally, in small blocks, rather than all at once. This will also teach you how to understand and explain things in parts, which will increase the clarity of your speech.