Good critique of the current practice of using algorithm questions during tech interviews from Dan Luu
At this point, we’ve gone through a few decades of programming interview fads, each one of which looks ridiculous in retrospect. Either we’ve finally found the real secret to interviewing effectively and have reasoned our way past whatever roadblocks were causing everybody in the past to use obviously bogus fad interview techniques, or we’re in the middle of another fad, one which will seem equally ridiculous to people looking back a decade or two from now. Without knowing anything about the effectiveness of interviews, at a meta level, since the way people get interview techniques is the same (crib the high-level technique from the most prestigious company around), I think it would be pretty surprising if this wasn’t a fad. I would be less surprised to discover that current techniques were not a fad if people were doing or referring to empirical research or had independently discovered what works.
The Guardian Digital team’s write-up on their “test in prod” setup — post-release monitoring through running integration test suites. We do the same in Swrve, calling our suites the “canary tests”, and it works really well for us.
oh dear, I use this model….
About 3 weeks ago our neighbour installed power line adapters. The PLAs in question were branded TP-Link [….] How did I know that my neighbour had installed these? Well, the 50MHz band was immediately submerged under a wall of radio noise. Much tinkering with the Noise Blanker settings on the Icom IC-7300 allowed me to separate out two distinct types of noise – 1st a sound like a chicken clucking which was there 24 hours per day and – 2nd a wideband swoosh of white noise of varying strength which happened at certain times.
This is fascinating, and potentially quite useful — although the great loft I stayed in in Antwerp is marked in a decidedly yellowish region :) (via Nelson)
The aim of this project is to map tourists’ perceptions of different urban areas through data retrieved from vacation rental platform Airbnb. After their stay, Airbnb guests score their feeling about the neighbourhood using a star-based rating system. The aggregated rating of each Airbnb listing is publicly accessible, and given the widespread expansion of this platform, a large amount of data is available for the most visited cities. When overlaid on a map of the city, the data reveals interesting geographic patterns and exposes subjective perceptions on safety, upkeep or convenience. — Beñat Arregi
in case I need to fill my house with IOT tat