Using Ctrl-r and fzf roughly doubled my efficiency in the shell overnight. Interestingly, it had an even greater long term effect: I became a more ambitious user of shell commands because I knew I could outsource my memory to fzf. For example, since it’s now very easy to recall past commands, I no longer set global environment variables, which had previously caused me grief when I forgot about them. Now I set environment variables on a per-command basis, knowing that I can recall them with Ctrl-r and fzf.

source: HN

With the benefit of hindsight, I think UML had quite possibly reached not only its actual, but also its potential, peak in 2000: as a medium for software sketching, people only ever needed the basics from it. However, the standardisation community developed an ambitious vision for UML that far exceeded sketching. Whether or not that vision could ever be realised can be seen as a matter of genuine debate: what seems unarguable to me is that such a vision was deeply unsuited to any standardisation process.

One of the things that’s become increasingly obvious to me over the past few years is that the general consensus breaks down for one vital emerging trend: language composition. Composition is one of those long, complicated, but often vague terms that crops up a lot in theoretical work. Fortunately, for our purposes it means something simple: grammar composition, which is where we add one grammar to another and have the combined grammar parse text in the new language (exactly the sort of thing we want to do with Domain Specific Languages (DSLs)). To use a classic example, imagine that we wish to extend a Java-like language with SQL

In the process of using the Kalibera and Jones methodology, we noticed quite a lot of variation in the warmup time of different VMs and cases where VMs didn’t seem to warmup at all. This was surprising because pretty much every paper we’d read until that point had assumed – and, in many cases, explicitly stated – that warmup was a quick, consistent, thing. On that basis, it seemed interesting to see how the warmup time of different VMs compared. In May 2015, I asked Edd if he’d knock together a quick experiment in this vein, estimating that it would take a couple of weeks. After a couple of weeks we duly had data to look at but, to put it mildly, it wasn’t what we had expected: it showed all sorts of odd effects. My first reaction was that if we showed this data to anyone else without checking it thoroughly, we’d be in danger of becoming a laughing stock. It was tempting to bury my head in the sand again, but this time it seemed like it would be worth digging deeper to see where we’d gone wrong.

Be careful what you measure. You may not like the result...

Part 2: https://tratt.net/laurie/blog/entries/why_arent_more_users_more_happy_with_our_vms_part_2.html

source: Dfly

So, while I’m not claiming to have any novel insights, here is my attempt to enumerate some often-forgotten (at least by me) issues which limit the effectiveness of optimising compilers.