Brush up your COBOL: Why is a 60 year old language suddenly in demand?
stackoverflow.blog
stackoverflow.blog
The use case was processing of record-based inputs in an administrative context, based on a technology millions of times less powerful than current hardware, yet still able to sustain a massive administration (old-school banking, anyone?)
No, you will not write a compiler or a kernel module in COBOL, just like you won't write it in SQL, APL or Matlab. But for the purpose it was built for, you'll be a lot more comfortable than in most alternatives.
That certainly wasn't on display here. The equivalent Java program (to use everyone's favorite punching bag) would be a tenth the length.
The value of SQL is easily demonstrated in a blog entry of less than 500 words. Now that I've had this introduction, I can't imagine ever thinking "oh this would be a great place to use COBOL!"
Fantastic and educational article, however.
Not if you started dealing with real-life record format specifications, including fixed-precision numbers for currency, dates etc.
In shortest words: variable declaration is also used as I/O format specification. Pretty much all of IO is just reading into a buffer, and the values are automatically mapped for your use. Sure you can use the same method in pretty much every general-purpose language (mapping C structs etc), but here it comes just natural.
If you want to make the case that COBOL is still a good DSL for its niche (report generation?), it seems like there should be some straightforward examples. This is super easy to do with the aforementioned SQL or Matlab.
Our field evolves quickly. Cast aspersions on the issues of our field today all you want - fragmentation and trend-chasing are big problems, but the argument, “well it was built to last, and look, it’s still running,” doesn’t excuse the horrible waste that comes from trying to maintain this ancient stack instead of taking a level-headed approach and investing appropriately in modern, stable technologies.
I won't be surprised as IBM has bought redhat, now you can execute python programs in mainframe. Why not do all that machine learning ans be close to data instead of migrating to Hadoop.
In Europe the grandfather has worked all his life to build a house, which will last for generations. The father has worked all his life to buy a car, which will last for generations. And the son is working with the aim to buy a yacht.
But in Japan each generation is working all life to re-build a house, which lasts only one generation.