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I am strongly considering buying a copy of your book and giving data-oriented programming a go in my day job. My only hesitation is data immutability. I work in a data-intensive scientific field where we frequently use custom, mutable data structures holding massive amounts of data. Creating persistent versions of these data structures would be an extremely complex undertaking. Do you have any thoughts about using data-oriented programming in situations when data mutability is difficult to avoid?



Could you elaborate about the complexity involved in using immutable data structures in your use case? Is that a performance concern?


That’s right. Our data structures are designed for working with large amounts of compressed text (dynamic FM-Index is one example). They are pretty hard to implement so making a persistent version of such a data structure would require a big time commitment. I imagine that my use case is not that unique and there are many situations where mutable data structures are hard to avoid.


In most languages, there are libraries that provide efficient implementation of persistent data structures.

What languages do you use?


I use C++ and Rust. Unfortunately, there are no persistent versions of the data structures I need available in any language (using dynamic FM-index as an example again). It is just interesting to think about “hybrid” systems where most of the code follows principles of data-oriented programming and some of the code deals with any unavoidable mutability.


I totally agree




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