Given that AI-generated code is not 100% perfect, we need to take into account the time and cost of reviewing when we discuss the productivity boost AI developers receive from code.
I convinced a software company to use a version control system (RCS on shared disk) back in 1993. To make it work we had to setup a network — Ethernet over (thin) coaxial cable at the time. This was so new to us that we didn't know we needed to use terminators on the two cable ends.
30 years ago (1995) open source offerings: mostly CVS for large projects and RCS for smaller ones. On the proprietary side, the aged SCCS was available and used, while Perforce and Microsoft Visual Source Safe were being launched.
I published an updated extension of this post's linked article in Empirical Software Engineering. You can read it without a paywall at https://rdcu.be/b7FzE. You may also be interested to see the actual GitHub repository at https://github.com/dspinellis/unix-history-repo.
I'm curious: what do you mean by "dgsh will use iteration under the hood too"? Dgsh does several things under the hood, but I wouldn't characterize any of them as iteration.
Yes you’re right. My apologies. I was glancing at the examples while cooking, specifically the git example (https://www2.dmst.aueb.gr/dds/sw/dgsh/#commit-stats) thinking that it was iterating over the lines output from git, but clearly that’s not even how bash would work. That will teach me for commenting without giving something my full attention first doh!
Looking properly at this, I can see no iteration is needed. Which actually makes the Murex implementation even easier because Murex already has tee pipes just like dgsh. It’s just not (yet) particularly well documented.