Which feature of a programming language helps prevent data type mismatch errors?

Strong data typing is a feature of a programming language that enforces strict adherence to defined data types, thereby preventing data type mismatch errors. In strongly typed languages, every variable and expression type is known at compile time, and type constraints are enforced at runtime. This means that if a variable is defined as an integer, it cannot be assigned a string value without an explicit conversion. The compiler or interpreter will raise an error if there is any attempt to perform operations that are not type-compatible, thus safeguarding against potential runtime errors that arise from type mismatches.

Strong data typing enhances code reliability and maintainability, making it easier for developers to identify and correct type-related errors early in the development process. This contrasts with weakly typed languages, where types are more flexible and conversions between different data types can occur implicitly, leading to ambiguous behavior and errors that might not surface until the program is executed.

Dynamic typing allows types to be determined at runtime, potentially leading to data type mismatches if not carefully handled, while type inference refers to the ability of a language to deduce the type of a variable automatically. Though these last two concepts contribute to type management, they do not inherently prevent data type mismatches in the same definitive manner that strong data typing does.