New group: Pragmatic functional programming research

I've started a new Google Group to discuss issues surrounding the practical use of former research around functional programming including issues such as designing purely functional data structures to leverage mainstream virtual machines (JVM and CLR) and garbage collectors, wrapping mainstream libraries (e.g. Windows Presentation Foundation) to improve productivity from modern functional languages and so on.
Please join us here.

Comments

Post a Comment

Popular posts from this blog

Benchmarking in the web age

The TechEmpower website contains some fascinating benchmarks of servers. The results on this benchmark of multiple requests to servers provide some insight into the performance characteristics of .NET on a modern problem. Specifically, the C# on ASP.NET Core solutions range from 2.5-80× slower than fastest solution which is written in Rust. In fact, C# is beaten by the following programming languages in order: Rust Java Kotlin Go C Perl Clojure PHP C++ Furthermore, .NET Core is Microsoft's new improved and faster version of .NET aimed specifically at these kinds of tasks. So why is it beaten by all those languages? I suspect that a large part of this is the change in workload from the kind of number crunching .NET was designed for to a modern string-heavy workload and I suspect .NET's GC isn't as optimised for this as the JVM is. As we have found, .NET has really poor support for JSON compared to other languages and frameworks, with support fragmented across many non-stand...
Read more

Does reference counting really use less memory than tracing garbage collection? Mathematica vs Swift vs OCaml vs F# on .NET and Mono

Image
Our previous post caused some controversy by questioning the validity of some commonly-held beliefs. Specifically, the beliefs that reference counting (RC) always requires less memory than tracing garbage collection (GC) and that tracing GCs require 3-4x more memory in order to perform adequately. We presented a benchmark written in Swift and OCaml and noted that the RC'd Swift implementation ran over 5x slower and required over 3x more memory than the tracing GC'd OCaml implementation. This observation disproves these beliefs in their strong form and even brings into question whether there is even any validity in the weak forms of those beliefs. After all, we have never seen any empirical evidence to support these beliefs in any form. We received a lot of criticism for that post. The vast majority of the criticism was not constructive but two valid points did arise. Firstly, although our result was anomalous it would be more compelling to see the benchmark repeated across a w...
Read more

Does reference counting really use less memory than tracing garbage collection? Swift vs OCaml

Image
The way software developers cling to folklore and avoid proper experimental testing of hypotheses really bothers me. I think perhaps the worst branch of computer science still riddled with myths and legends is memory management. Despite over half a century of research on garbage collection showing that reference counting is inferior to tracing garbage collections algorithms (even when almost all GC research restricts consideration to Java when much better algorithms have been known for years) there are still many people who claim otherwise. C++ developers obviously still believe that reference counted smart pointers are superior to tracing garbage collection but now other people are doing it too. People who should know better. This situation recently reared its ugly head again when Apple released a promising new programming language called Swift that shuns tracing garbage collection in favor of reference counting. Now, there are logical reasons for Apple to have chosen reference count...
Read more