What is a Design Pattern?

The most common purpose of design patterns is to make classes reusable and extensible. Design patterns do this by documenting common solutions to common problems.
Since design problems come up again and again in different contexts, it is profitable to learn to recognize common ones. Once you recognize a common problem, you can recall and reuse its solution.
A design pattern is the combination of the problem and its solution.
Programmers are familiar with the concept of an abstract data type. Object-oriented languages and their associated separation of interface from implementation also make possible abstract algorithms; that is, algorithms that do things without precise specifications of how or even what they are doing.

An abstract data type (ADT) defines a data structure in terms of the operations that can be performed on it rather than in terms of a specific implementation. It separates what the data structure does from how it does it.
For instance, linked lists and growable arrays are simply two different implementations of the same linear list ADT since the operations that can be performed on each are the same. In computer science, an abstract data type (ADT) is a mathematical model for a certain class of data structures that have similar behavior. An abstract data type is defined indirectly, only by the operations that may be performed on it and by mathematical constraints on the effects of those operations. However, the concrete implementation

1. linked list or
2. growable array

affects the performance characteristics of the ultimate code.

Abstract data types are an object-like means of raising the bar on the size of programs that can be written in a purely procedural language. Past a million lines of code, even Object Oriented Design begins to break down. New techniques are needed that allow truly huge programs to be both built and maintained. This is not to say, of course, that these techniques cannot also be used for more complicated programs such as games, word processors, and spreadsheets. In fact, they have been used for these things for many years, sometimes with great success, sometimes with spectacular failure. If you investigate the successes, you will often notice that developers adopted object-oriented principles like data encapsulation even though the language they were coding in did not explicitly support it.
But it's my contention that procedural programming is not the best approach to take for these problems, that OOP more closely matches the way these programs are designed and used, and thus enhances programmer productivity.

Design patterns take abstraction one step further. A design pattern abstracts something you want to do from the actual

1. data structures,
2. algorithms,
3. code,
4. classes, and
5. objects

that fulfill a function.
It decouples the abstract from the specific.
A design pattern is not a particular class, object, data structure, or algorithm, though all of these elements are used to implement patterns. A design pattern is the abstract structure of a common solution to a common problem. It can be implemented in different languages in different ways, and yet still retain its essential flavor.

The field of computer science has constantly evolved, striving to address complex problems with efficient and elegant solutions. Central to this endeavor is the "divide and conquer" strategy, a fundamental approach that has withstood the test of time and informed various methodologies, including design patterns. This analysis delves into the essence of this strategy and its intricate relationship with design patterns.

1. The Essence of "Divide and Conquer": The "divide and conquer" paradigm is predicated on the principle of breaking a problem down into smaller, more manageable sub-problems until they are simple enough to be solved directly. These solutions are then combined to solve the original problem. This approach rests on two fundamental operations:
   • Divide: Decompose the main problem into a set of smaller instances of the same problem.
   • Conquer: Solve each of these smaller instances, either directly (if they are sufficiently simple) or recursively using the same approach.
   
   The efficacy of "divide and conquer" lies in its ability to reduce the computational complexity of problems, making seemingly intractable challenges more approachable.
2. Relation to Design Patterns: Design patterns are recurring solutions to common problems encountered in software design. They encapsulate best practices, allowing developers to leverage tried and tested strategies without reinventing the wheel. The philosophy of "divide and conquer" reverberates through various design patterns in the following ways:
   • Decomposition and Modularity: At the heart of many design patterns is the principle of decomposing a system into modular components, each handling a specific responsibility. This modular decomposition resonates with the "divide" phase of the "divide and conquer" paradigm. For instance, the Composite pattern, which treats individual objects and compositions uniformly, mirrors this strategy by breaking down complex structures into simpler elements.
   • Recursive Problem Solving: Some design patterns inherently lean on recursive solutions, mirroring the "conquer" phase of "divide and conquer." The Chain of Responsibility pattern, where a request traverses through a chain of potential handlers until it's addressed, epitomizes this approach.
   • Optimization through Subdivision: Patterns like the Flyweight leverage the "divide and conquer" strategy by subdividing tasks or data. The Flyweight pattern aims to minimize memory usage by sharing as much data as possible with related objects, an approach that recalls the efficiency goals of "divide and conquer."
   • Parallelism and Concurrency: The "divide and conquer" paradigm often lends itself to parallel solutions since subdivided problems can be tackled concurrently. Patterns like the Strategy, which encapsulates an algorithm inside a class, facilitate parallel or distributed implementations, echoing the "divide and conquer" ethos.

The "divide and conquer" paradigm, with its analytical rigor of subdivision and recursive problem-solving, has left an indelible imprint on the realm of design patterns. It underscores the philosophy of tackling complexity through systematic decomposition and modular design. Recognizing the deep-seated influence of this paradigm in design patterns enables developers to approach software design challenges with a profound analytical lens, fostering solutions that are both efficient and elegant.