How can you elegantly implement data structures and algorithms with object oriented programming?

Object oriented programming (OOP) is a paradigm that organizes data and behavior into reusable and modular units called objects. OOP can help you design and implement data structures and algorithms in a clear, concise, and elegant way. In this article, you will learn some basic principles and techniques of OOP that can enhance your coding skills and problem-solving abilities.

1 Abstraction and Encapsulation

Abstraction is the process of hiding the unnecessary details and exposing only the essential features of an object. Encapsulation is the mechanism of bundling the data and the methods that operate on it within the same object. Together, they allow you to create a simple and consistent interface for your data structures and algorithms, while hiding the complexity and implementation details from the users. For example, you can create a Stack class that abstracts the concept of a last-in, first-out (LIFO) data structure, and encapsulates the underlying array or linked list, as well as the methods to push, pop, and peek elements.

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Paulo Zemek

Software Engineer - I talk to computers and they understand me even without AI, we just speak the same language
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These articles keep repeating this, but abstraction is not about hiding unnecessary details. That would be part of encapsulation. Abstraction is about creating a base class or interface that can tell what objects can do, without actually providing an implementation, and letting the actual implementation be written somewhere else. As an example, so it makes sense, an ILogger interface can have a method to log messages. Yet, does it log to the Console, does it write to a Window in the app, to a File, to a Database or to where? Each one of these alternatives would be a different implementation of ILogger... so, the abstract class/interface, is not even aware of the implementation details.

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2 Inheritance and Polymorphism

Inheritance is the process of creating new classes from existing ones, by reusing and extending their attributes and behaviors. Polymorphism is the ability of an object to take different forms depending on the context. Together, they allow you to create a hierarchy of classes that share common features and functionality, but also have their own specificities and variations. For example, you can create a Sort class that defines a generic algorithm for sorting an array, and then create subclasses that implement different sorting strategies, such as BubbleSort, MergeSort, and QuickSort. Then, you can use polymorphism to invoke the appropriate sort method based on the type of the object.

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3 Composition and Aggregation

Composition and aggregation are two ways of creating complex objects from simpler ones, by establishing a has-a relationship between them. Composition implies a strong and exclusive ownership of the component objects by the composite object, while aggregation implies a weak and shared ownership. Both allow you to create data structures and algorithms that are more flexible, maintainable, and reusable, by combining existing objects rather than creating new ones from scratch. For example, you can create a Graph class that aggregates a set of Node objects and a set of Edge objects, and then use composition to create a WeightedGraph class that inherits from Graph and adds a weight attribute to each edge.

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Paulo Zemek

Software Engineer - I talk to computers and they understand me even without AI, we just speak the same language
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In the example we have a Graph class that deals with many Edge objects. But, by inheriting Graph class (and creating WeightedGraph) we have no way of adding a "weight" attribute to the Edge objects. They are different classes and, although it is possible to create a WeightedGraph that contains WeightedEdges, the examples here fail in many ways. Either a Graph is a generic/template type that can be instantiated to use child-types/sub-classes of the Edges, or the WeightedGraph would need to use some kind of map/dictionary to keep track of the edges, in which case we are just showing a bad example of composition and aggregation. So, first we can have Edges and WeightedEdges... then Graph (maybe templated) and, if needed, WeightedGraph.

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4 Design Patterns

Design patterns are proven and reusable solutions to common software design problems, providing a common vocabulary and best practice for designing and implementing data structures and algorithms with OOP. There are various types and categories of design patterns, but some of the most useful ones for OOP include Creational patterns (e.g. Factory, Singleton, and Builder), Structural patterns (e.g. Adapter, Decorator, and Composite), and Behavioral patterns (e.g. Strategy, Observer, and Iterator). By using these principles and techniques of OOP, you can create data structures and algorithms that are easy to understand, modify, and reuse, as well as adaptable to different scenarios and requirements. OOP can also benefit your code quality, readability, performance, debugging skills, and testing capabilities.

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