Considerations for Creating HDF Data Types

1. HDF Metadata-Based Constructors

   • Include constructors that accept HDF-specific metadata (e.g., size, type, null-termination) to construct objects from data read directly from an HDF file.

2. Default HDF-Compliant Constructors

   • Provide constructors that default missing parameters to HDF-specified default values, simplifying the creation process when full metadata is not required.

3. Application Value-Based Constructors

   • Implement constructors that take application-level values (e.g., String, int, BigDecimal) and convert them to HDF-compliant internal representations while setting the appropriate metadata.

4. Getters for HDF Byte Arrays

   • Ensure methods exist to retrieve the HDF-compliant byte[] representation of the value, with support for specifying additional metadata like desired endianess.

5. Application-Friendly Value Getters

   • Provide methods to access the value in a format suitable for application use (e.g., String, BigInteger, float, double).

6. Validation of Inputs

   • Perform internal validation to ensure inputs comply with HDF constraints (e.g., bit length, type compatibility, metadata correctness).
   • Throw meaningful exceptions for invalid or incompatible inputs.

7. Immutability

   • Ensure the immutability of data type objects by making fields final and using defensive copying for mutable inputs like byte[].

8. String Representation

   • Override toString() to provide a clear, human-readable representation of the value, metadata, and internal state.

9. HDF Specification Compliance

   • Implement internal handling and features that adhere to HDF specifications, ensuring compatibility with storage and retrieval requirements for all HDF data types.

10. Testing and Compatibility

    • Develop comprehensive unit tests for all constructors and methods to validate functionality against HDF specifications and typical application scenarios.