Earlier quoted context omitted.
TS really stands out as amazing. It’s realized a lot of the promise of strong typing.
How so? It looks a lot like a less-rich Java, whose type system has existed for literally decades. In fact, the generics syntax and type erasure was directly influenced by Java.
What's worked in Computer Science: 1999 vs. 2015 (2015)
41–50 of 155 posts
Re: What's worked in Computer Science: 1999 vs. 2015 (2015)
#42> Fancy type systems We are taking steps to this direction. By adding optional typing to dynamic languages Python and JavaScript/TypeScript. And then type checker tools and local programming style guides are making using these maybe less optional, and more mandatory.
IMO the day python types become mandatory there will be a fork. It would be such a total betrayal of it's reason for existing that we would have to invent another untyped or duck-typed language again.
I find myself using less type hints in Python because the story for REPL driven development is so much better than JavaScript, and that takes most of the pain away.
Re: What's worked in Computer Science: 1999 vs. 2015 (2015)
#43I'd say that " pure Functional programming" has become a no. But "Functional programming approach" has been subsumed into existing programming languages, e.g. records in Java. You get most of the benefit of FP while keeping all of the other good stuf from an imperative language.
If you try to write mostly pure code in Java I’m afraid you’re in for a bad time, despite the (big!) improvements of records and lambdas.
Minimum viable FP starts at OCaml, F#, Scala and Closure, yet none of these are mainstream.
Re: What's worked in Computer Science: 1999 vs. 2015 (2015)
#44Fancy type systems have come a long way since then. (TypeScript, for example.)
TS really stands out as amazing. It’s realized a lot of the promise of strong typing.
Re: What's worked in Computer Science: 1999 vs. 2015 (2015)
#45Earlier quoted context omitted.
TS really stands out as amazing. It’s realized a lot of the promise of strong typing.
How so? It looks a lot like a less-rich Java, whose type system has existed for literally decades. In fact, the generics syntax and type erasure was directly influenced by Java.
Re: What's worked in Computer Science: 1999 vs. 2015 (2015)
#46Earlier quoted context omitted.
TS really stands out as amazing. It’s realized a lot of the promise of strong typing.
How so? It looks a lot like a less-rich Java, whose type system has existed for literally decades. In fact, the generics syntax and type erasure was directly influenced by Java.
Re: What's worked in Computer Science: 1999 vs. 2015 (2015)
#47Fascinating about how ARM has made tremendous strides in the “high end” market since 2015. I would argue that I would categorize RISC as a “yes” with its absolute dominance on mobile and now moving into data center not to mention all the embedded use cases.
My view, even when I was studying RISC V in grad school around 6 years ago, was that RISC is clearly superior technically and this would only become more obvious with Moore's Law dying. I think subsequent events are only confirming this view. The strongest evidence for it is that nobody would even think about making a new CISC architecture that isn't x86.
Re: What's worked in Computer Science: 1999 vs. 2015 (2015)
#48Earlier quoted context omitted.
> Apple's M chips have made RISC is a clear yes now. ARM is not a pure RISC architecture (even though its instruction set is somewhat inspired by those ideas behind RISC that stood the test of time).
What counts as "pure RISC"?
Elsewhere in the comment section is describe the question isn’t RISC/CISC, it’s x86/Nonx86. And far more interesting since those lines are still fairly well established.
Re: What's worked in Computer Science: 1999 vs. 2015 (2015)
#49I would like to suggest that the classical taxonomy of RISC/CISC dichotomy is basically non-existent nowadays -- namely because both sides have influenced each other. It is well known that CISC has taken a lot of inspirations from RISC designs (such as having a lot more registers in x64), and RISC designs also taken some inspirations from CISC (such as having SIMD/vectorization units). In other words, the line betwee…
A 20,000 gate minimal RISC-V RV32E controller CPU isn't going to use μops. In 2024, RISC-V has turned that 2015 No into an unqualified Yes even if the microarchitecture of more complex OOO RISC-V systems resemble the microarchitectures of similarly complex x86 and ARM CPUs.
Re: What's worked in Computer Science: 1999 vs. 2015 (2015)
#50Neural networks: 1999 - No 2015 - Not really 2024 - Yes?