Datentyps

Datentyps is the term used in German-speaking contexts for data types—the classifications of values that a program can store, manipulate, and reason about. Data types define what operations are valid, how much memory a value requires, and how the value should be interpreted. They are a fundamental concept in programming languages and data storage, influencing correctness, performance, and interoperability.

Data types are typically divided into primitive and composite categories. Primitive types include integers, floating-point numbers, booleans, and characters. Composite types cover structures such as arrays, records, lists, and tuples, which combine multiple values. Many languages also provide user-defined types like enums, structs or classes, and more flexible constructs such as variant or union types. Some languages introduce optional or nullable types to represent the absence of a value.

Type systems describe how a language enforces and uses data types. They can be static or dynamic: static typing checks types at compile time, while dynamic typing defers checks to run time. They can be strong or weak: strong typing reduces implicit conversions, improving safety, whereas weak typing allows more implicit coercions, which can lead to surprises. Other aspects include type inference, generics or parametric polymorphism, and explicit versus implicit type declarations. Memory layout, type aliases, and casting rules also affect how data types are implemented and used.

In practice, data types guide program design, influence performance and space usage, and enable safer interfaces between components. They are also crucial in databases, where column types determine data validity, storage efficiency, and query behavior. Understanding datentyps helps developers write clearer, more reliable, and more portable code.