What's the difference between an abstract data type and a concrete data type?

An abstract data type (ADT) defines a data type conceptually, while a concrete data type provides a specific implementation of a data type.

An abstract data type, often abbreviated as ADT, is a high-level description of a collection of data and the operations that can be performed on that data. It is called 'abstract' because it does not specify how the data should be stored and the algorithms for performing the operations. It only describes what operations are to be performed but not how these operations will be implemented. It serves as a blueprint for a data type, and different implementations of the same ADT can vary in efficiency. Examples of ADTs include List, Stack, Queue, and Tree.

On the other hand, a concrete data type, also known as a data structure, is a specific implementation of an ADT. It provides the exact storage method and algorithms for the operations, hence it is 'concrete'. It is the actual representation of the data in a computer program or a physical device, and it includes both the collection of data and the set of operations that can be performed on it. Examples of concrete data types include arrays, linked lists, binary trees, and hash tables.

The distinction between abstract and concrete data types is crucial in the field of computer science. ADTs allow programmers to think about data and operations at a high level without worrying about low-level implementation details. This abstraction makes it easier to design and reason about software systems. Concrete data types, on the other hand, allow programmers to implement these high-level designs in actual computer code. Understanding the difference between these two concepts can help you write more efficient and maintainable code.