On 25/09/2022 3:56 pm, Peter Sylvester wrote:
On 25/09/2022 05:02, David Crayford wrote:
There's some interesting videos here. All entertaining in their own
way. It's like any dogma, if you want to believe then you will. If
you have spent your entire career using structured programming you
probably think "hell yeah"!
Is such a person the primary target audience of this presentation? I
don't think so (the audience is younger). In some other presentation
(I don't know the conf/presenter): "If you agree with me, you haven't
understood".
Maybe, but young people just want a decent job and that usually means
using either an OO or FP language in todays job market. We've got a lot
of HLASM in our code base and it's not easy to find young people who
want to commit to learning a language they consider to be a dead end.
Young people move around a lot and want to pick up skills that are
transferable. The job market for HLASM programmers may get lively as
more people start to retire. Same for COBOL and PL/I. Half of our team
have moved to 3 day weeks with a view to retiring.
One funny "critique/comment" is the fortran COMEFROM :-) Easy to
implement btw. The spaghetti monster"s programming language, (R)amen.
IMHO, your last sentence may provide a hint. If one spends all his
career using the same "paradigm" (or whatever one may call a
"religion") ... And then may even reinvent a square shaped wheel
(where pi equals 4) ... Or a cubic sphere (in my neighborhood), which
is actually fun :-)
https://www.youtube.com/watch?v=cNSTJ2Y80OQ
Lot's of things to be critized about the following, too. But whow,
putting *all* this into a short presentation. (I missed some, e.g.
SNOBOL, CDL).
https://www.youtube.com/watch?v=0fpDlAEQio4
LOL. Agreed, good fun :)
As already said, I was lucky to work as a student (and later as IBM
systems programmer) in a mainframe environment of a CS and math
research institute (GMD) with >1000 people. Chance to see "beyond and
avove" and "play with" a multitude of different perspectives and
experiments, some good, some no so, software (totally unstructured
programs), hardware (lisp/reduction machine, Suprenum, Eumel),
theories (Petri Nets, Interval arithmetic). And, of course, preachers,
dogmas.
Our ported tools team develop the SciPy libraries for IBM machine
learning products on z/OS using highly optimized C/C++ code to implement
Python libraries. The MIT "Introduction to programming" course is now
taught in Python. SciPy supports both OOP and FP paradigms.
https://docs.scipy.org/doc/scipy/
Best
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