Nicolai Parlog
Data-Oriented Programming - Version 1.1
#1about 2 minutes
Introducing the four principles of data-oriented programming
Data-oriented programming (DOP) is a paradigm that models programs as a series of transformations on data, guided by four key principles.
#2about 5 minutes
Modeling a GitHub crawler page type example
An example of a GitHub crawler is used to explore how to model a complex page data type with various states and required operations.
#3about 2 minutes
Using Java records for immutable and transparent data
Java records are the ideal choice for modeling immutable data, and compact constructors can be used to ensure deep immutability for collection fields.
#4about 3 minutes
Modeling data alternatives using sealed interfaces and records
Sealed interfaces create a closed type hierarchy, allowing you to precisely model "either/or" relationships between different record types representing distinct data states.
#5about 3 minutes
How to make illegal data states unrepresentable
By combining a precise type hierarchy with validation in record constructors, you can prevent the creation of invalid object states within your domain model.
#6about 6 minutes
Separating operations from data using pattern matching
Operations are moved out of data records and implemented externally using switch expressions with pattern matching to deconstruct and act on the data.
#7about 4 minutes
Ensuring maintainability with compiler exhaustiveness checks
Switching over sealed types is safe because the compiler enforces exhaustiveness, issuing a compile error if a new subtype is added but not handled.
#8about 3 minutes
Comparing data-oriented programming to the visitor pattern
Data-oriented programming provides a more ergonomic alternative to the classic visitor pattern and is useful for modeling complex return types.
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