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Good points. I actually did my Ph. D. in software engineering after getting my computer science master degree a bit over 20 years ago. Software engineering as a

Good points. I actually did my Ph. D. in software engineering after getting my computer science master degree a bit over 20 years ago. Software engineering as a discipline is a bit of an oddball science as it is a bit stuck between typical hard / math driven scientific fields like mathematics and physics and other scientific fields like sociological, economics, etc. The core issue is that software engineering involves people and processes. Mathematical proofs don't really work all that well for that kind of stuff and you need to reach for scientific methodology from other fields to study it properly. A lot of computer scientists actually struggle with this and don't fully get it. As a result, software engineering education isn't all that great in a typical computer science curriculum. One reason is that most computer scientists actually lack the experience of having worked in large software companies and don't actually know a lot about how that works. It's something I realized while doing my Ph. D. in this area and I fixed it by leaving academia. I learned a lot since then. One thing I learned is that a lot of good software engineers exist that never studied computer science. I know people with physics, geology, micro biology, philosophy degrees that ended up working as software engineers and that are very good at what they do. Most scientific work involves some level of programming these days. So, it's quite common to meet people with some python or even machine learning experience that never studied computer science. Things like formal methods, linear algebra, etc. are useful to know of course for some things. But you don't need to have a any of that to learn python, javascript, or any of the other popular languages. In the same way, knowing a lot about type systems is nice if you build compilers or design your own languages. But you don't need to know much about that to use a language.

frankreyes 3y ago
> and don't actually know a lot about how that works. It's something I realized while doing my Ph. D. in this area and I fixed it by leaving academia. I learned a lot since then. Well said.
tialaramex 3y ago
> But you don't need to know much about that to use a language. On the other hand, without the formal underpinning there is an enormous risk you assume your intuitions are correct about stuff where it turns out there's just unyielding mathematics (or occasionally physics) that disagrees. The formal instruction would either outright tell you about that or at least give you the right lenses to see for yourself. For example it's not at all rare to see programmers who think about floating point as just the Real Numbers, because they superficially resemble real numbers you've seen - but it's not, it's the modulo integers again but wearing a trench coat. Formally it's obvious we're not getting the Real Numbers, Almost All of which aren't even computable. But without that formal underpinning people have nasty surprises. People's intuitions about concurrency and parallelism are all wrong too. Amdahl's law matches reality but doesn't match how people intuitively expect this to work out. The insight that makes Rust and several modern languages work (that you can't incur a data race if you don't have multiple references and mutation) is not at all intuitive.
- jillesvangurp 3y ago
  It's a theoretical risk; you mitigate it by just having smart people that have a good analytical mindset that can learn. As it turns out, the most important thing you learn in university is the ability to acquire new skills; not any particular skills. That ability is not unique to computer science. Another thing is that languages and tools that require a lot of formal background are a hard sell in industry because it means having to hire more scarce and expensive people. It's a reason that functional programming was a hard sell for a long time until languages got good enough that normal people could figure it out. Scala was an early example that did not quite get that right maybe. Too difficult for people without a CS degree and a good understanding of type systems. Indeed the whole language became a bit of a playground for type system nerds. It got a bad reputation for being hard and a bit over engineered. Javascript and python, both of which now have some level of functional programming support, are much easier to pick up by other people. Which is why those languages are so popular. Any high school kid can work with this. I currently have a couple of summer interns in my team. These two languages are what they know.
KineticLensman 3y ago
> One reason is that most computer scientists actually lack the experience of having worked in large software companies and don't actually know a lot about how that works. It's something I realized while doing my Ph. D. in this area and I fixed it by leaving academia. I learned a lot since then This was me exactly. I started a Ph. D. simultaneously with two other students and our supervisor had us working on separate aspects of a common overall problem, each of which required a lot of software development, in C, because we were chasing performance. The supervisor had an academic background and all of us had only just graduated. Needless to say this was a total disaster and we never even managed to complete our separate parts let alone integrate a usable system. I bailed out and got an M.Phil for my efforts, but on the basis of the experience managed to get the job that I wanted, so it wasn't a complete write-off. As soon as I encountered some actual software engineers in a well structured research department, I realised how bad our approach in Uni had been. My job involved a similar problem area, and using better tools (Common Lisp on a Lisp machine) I managed to build in about six months what I had failed to do in three+ years in academia. My thoughts on the feudal nature of the Ph.D system at my Uni are a whole separate post!
- deleted 3y ago
  [deleted]
- shae 3y ago
  I would enjoy a summary of that separate post!

frankreyes 3y ago

> and don't actually know a lot about how that works. It's something I realized while doing my Ph. D. in this area and I fixed it by leaving academia. I learned a lot since then. Well said.

tialaramex 3y ago

> But you don't need to know much about that to use a language. On the other hand, without the formal underpinning there is an enormous risk you assume your intuitions are correct about stuff where it turns out there's just unyielding mathematics (or occasionally physics) that disagrees. The formal instruction would either outright tell you about that or at least give you the right lenses to see for yourself. For example it's not at all rare to see programmers who think about floating point as just the Real Numbers, because they superficially resemble real numbers you've seen - but it's not, it's the modulo integers again but wearing a trench coat. Formally it's obvious we're not getting the Real Numbers, Almost All of which aren't even computable. But without that formal underpinning people have nasty surprises. People's intuitions about concurrency and parallelism are all wrong too. Amdahl's law matches reality but doesn't match how people intuitively expect this to work out. The insight that makes Rust and several modern languages work (that you can't incur a data race if you don't have multiple references and mutation) is not at all intuitive.

jillesvangurp 3y ago
It's a theoretical risk; you mitigate it by just having smart people that have a good analytical mindset that can learn. As it turns out, the most important thing you learn in university is the ability to acquire new skills; not any particular skills. That ability is not unique to computer science. Another thing is that languages and tools that require a lot of formal background are a hard sell in industry because it means having to hire more scarce and expensive people. It's a reason that functional programming was a hard sell for a long time until languages got good enough that normal people could figure it out. Scala was an early example that did not quite get that right maybe. Too difficult for people without a CS degree and a good understanding of type systems. Indeed the whole language became a bit of a playground for type system nerds. It got a bad reputation for being hard and a bit over engineered. Javascript and python, both of which now have some level of functional programming support, are much easier to pick up by other people. Which is why those languages are so popular. Any high school kid can work with this. I currently have a couple of summer interns in my team. These two languages are what they know.

KineticLensman 3y ago

> One reason is that most computer scientists actually lack the experience of having worked in large software companies and don't actually know a lot about how that works. It's something I realized while doing my Ph. D. in this area and I fixed it by leaving academia. I learned a lot since then This was me exactly. I started a Ph. D. simultaneously with two other students and our supervisor had us working on separate aspects of a common overall problem, each of which required a lot of software development, in C, because we were chasing performance. The supervisor had an academic background and all of us had only just graduated. Needless to say this was a total disaster and we never even managed to complete our separate parts let alone integrate a usable system. I bailed out and got an M.Phil for my efforts, but on the basis of the experience managed to get the job that I wanted, so it wasn't a complete write-off. As soon as I encountered some actual software engineers in a well structured research department, I realised how bad our approach in Uni had been. My job involved a similar problem area, and using better tools (Common Lisp on a Lisp machine) I managed to build in about six months what I had failed to do in three+ years in academia. My thoughts on the feudal nature of the Ph.D system at my Uni are a whole separate post!

deleted 3y ago
[deleted]
shae 3y ago
I would enjoy a summary of that separate post!