Algebraic Data Types (ADTs) are a fundamental concept in Haskell that allow you to define and work with structured data types. ADTs are composed of two main components: sum types (also called tagged unions or disjoint unions) and product types.

1. Sum Types :
   * Sum types allow you to represent a value that can be one of several possible alternatives. Each alternative is associated with a constructor, and the constructors are typically tagged with unique names. Sum types are created using the `data` keyword in Haskell.
   * An example of a sum type is the `Bool` type in Haskell, which can have two alternatives: `True` and `False`. It is defined as:

     data Bool = True | False​

   * Sum types can also have additional data associated with each constructor. For instance, consider the `Maybe` type, which represents an optional value:

     data Maybe a = Nothing | Just a​

     Here, `Maybe` has two alternatives: `Nothing` represents the absence of a value, and `Just a` represents a value of type `a`.


2. Product Types :
   * Product types allow you to combine multiple values into a single value. Product types are created using the record syntax in Haskell, where you define a constructor that takes multiple fields with associated names.
   * An example of a product type is a 2D point, which can be represented as a pair of coordinates:

     data Point = Point { x :: Double, y :: Double }​

     Here, `Point` is a product type with two fields: `x` and `y`. Each field represents a coordinate value. ADTs are used in Haskell for a variety of purposes, including :

* Modeling and Abstraction : ADTs allow you to define custom data types that closely match the problem domain, making it easier to model and reason about complex structures.

* Type Safety : ADTs help enforce type safety by specifying the possible values that a type can have. The type system can catch errors at compile-time if you attempt to use values that are incompatible with the defined ADT.

* Pattern Matching : ADTs are often used in pattern matching to destructure and process values. Pattern matching allows you to handle different cases based on the constructors and their associated data, enabling elegant and concise code.

* Data Transformation : ADTs facilitate transforming and manipulating data in a structured manner. Functions can be defined to operate on ADTs, allowing you to transform and combine values of ADT types.

* Domain-Specific Languages (DSLs) : ADTs are a powerful tool for building DSLs in Haskell. By defining custom ADTs, you can create languages tailored to specific problem domains and provide expressive and type-safe interfaces for working with domain-specific concepts.