Programming Leftovers
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Frank framework Low-code Open-source Messaging Framework
Frank Framework is a free open-source low-code messaging framework that allows developer to connect systems, integrate services and create a data applications. It is an open-source platform to quickly build enterprise applications. To have an enterprise application, or as we say a Frank, you have to deploy the Frank!Framework in combination with XML configuration files.
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Advent of Code 2022
The first puzzles will unlock on December 1st at midnight EST (UTC-5). See you then!
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‘Let It Crash’ under attack
With that said, I just don’t understand the obsession with testing in Erlang? Did we lose sight of the essence of Erlang? Or are some of us Erlangutans bored, need to fill in the day with busy-work, and thus spend too much time writing tests in Erlang?
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[Old] [EN] Writing a Dynamic Array in C
Although C is a very, very popular language, it is also known to be quite tiny: memory is handled manually, and much of what is available in its standard library is a given in all other languages. But C being a low level language also means it lacks a lot of other stuff other popular languages have; for instance, dynamic arrays are present in the library of most popular languages, be it JavaScript, C++, Rust and so on, but C’s simplicity forbids them from being there. If you want it in C, you have to implement it –which is exactly what I did!
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Functional programming explains why containerization is needed for reproducibility
I’ve had some discussions online and in the real world about this blog post and I’d like to restate why containerization is needed for reproducibility, and do so from the lens of functional programming.
When setting up a pipeline, wether you’re a functional programming enthusiast or not, you’re aiming at setting it up in a way that this pipeline is the composition of (potentially) many referentially transparent and pure functions.
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I am disappointed by dynamic typing
Here’s weird thing about me: I’m pro-dynamic types. This is weird because I’m also pro-formal methods, in fact teach formal methods as a career, which seems completely antithetical. So on one hand I teach people how to do static analysis, on the other I use languages which make static analysis impossible.
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AI experts are increasingly afraid of what they’re creating
Of course, handing over huge sectors of our society to black-box algorithms that we barely understand creates a lot of problems, which has already begun to help spark a regulatory response around the current challenges of AI discrimination and bias. But given the speed of development in the field, it’s long past time to move beyond a reactive mode, one where we only address AI’s downsides once they’re clear and present. We can’t only think about today’s systems, but where the entire enterprise is headed.
The systems we’re designing are increasingly powerful and increasingly general, with many tech companies explicitly naming their target as artificial general intelligence (AGI) — systems that can do everything a human can do. But creating something smarter than us, which may have the ability to deceive and mislead us — and then just hoping it doesn’t want to hurt us — is a terrible plan. We need to design systems whose internals we understand and whose goals we are able to shape to be safe ones. However, we currently don’t understand the systems we’re building well enough to know if we’ve designed them safely before it’s too late.