[HN Gopher] Auditory console logging: identifying bugs by listen...
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       Auditory console logging: identifying bugs by listening to code
       execution
        
       Author : electric_muse
       Score  : 46 points
       Date   : 2022-05-19 14:44 UTC (8 hours ago)
        
 (HTM) web link (blog.visor.us)
 (TXT) w3m dump (blog.visor.us)
        
       | nybble41 wrote:
       | The article says each operation gets a unique note, but I wonder
       | how the notes were selected? It would be interesting to apply
       | some musical theory to the process so that, for example,
       | operations which normally run together form pleasing cords, while
       | warning or errors appear more discordant. One could also
       | experiment with using different voices/instruments in addition to
       | plain notes.
        
         | electric_muse wrote:
         | Good question. We used the pentatonic scale, so that there
         | wouldn't ever be any dissonance when multiple notes were played
         | simultaneously
         | 
         | https://en.wikipedia.org/wiki/Pentatonic_scale
        
       | justinlloyd wrote:
       | It has been around for a while as far as I know, I was introduced
       | to the concept back in the '80s. It was called "cat belling."
       | Memory leaks and memory pressure, frame rate drops (it was
       | especially useful for that), texture loads & swaps, game AI
       | processing. We used it for determing if the game was executing
       | correctly by how often it passed certain check points in the
       | code. Also tracking the number of sprites in play vs the number
       | on-screen. You could listen for the rhythm of the various
       | sections of the code, in what was to most people, a cacophony of
       | noise.
       | 
       | After thought: I should probably try and work some of that
       | concept in to my next music track release.
        
       | bmogen wrote:
       | Similar idea in neuroscience - listen to neural spikes during
       | task/training/experiment to help troubleshoot experiment setup
       | and get a secondary source of info before visualizing data[0].
       | 
       | 0. Sonifying and Visualizing Neural Data
       | https://ccrma.stanford.edu/~mindyc/256a/final/
        
         | electric_muse wrote:
         | Wow. This seems particularly helpful since it allows you to
         | process more information when your sense of sight is otherwise
         | busy.
        
       | seclorum_wien wrote:
       | Back in the day, I'd tee a supposedly quiet log file to /dev/snd0
       | on my workstation so I could take a nap under the desk and be
       | sure to be woken up when the particles hit the fabric, so to
       | speak..
        
         | electric_muse wrote:
         | Not familiar with /dev/snd0 -- what would cause the sound to
         | play?
        
           | throwanem wrote:
           | It'd be an audio device on probably some old Sun or SGI
           | workstation. It would expect to receive bytes in RIFF (WAV),
           | AU, or some other format the backing hardware is equipped to
           | decode. Teeing a log file into it would produce some form of
           | horrible noise every time a line was written to the log. So
           | if you set up that tee while the logfile is quiet, turn the
           | speakers up, and stretch out under the desk, it'll give you a
           | very effective wake alarm when the log starts seeing new
           | entries.
        
       | malfist wrote:
       | This isn't too far from using a logic probe to test hardware
       | circuit. It has a tone for LOW and a tone for HIGH, and you can
       | listen to what state pins are in, even if they're switching
       | faster than your eyes can see the LED flicker, you can hear the
       | pitch changes.
        
       | mark_undoio wrote:
       | At the National Museum of Computing in the UK
       | (https://www.tnmoc.org/) I saw an old minicomputer where, if I
       | recall correctly, the low order bit(s?) of the program counter
       | had been hooked up to a speaker for some very simple auditory
       | debugging.
       | 
       | My memory is that e.g. infinite loops would be easy to identify
       | as a persistent tone, etc as repeated small changes to the
       | program counter happened.
        
       | convolvatron wrote:
       | came here for 'lights on the cm2' and was disappointed. you could
       | in fact indentify the application and stage of computation by the
       | patterns. it was sometimes useful in debugging, not that you got
       | any real information, but if it didn't look right you might was
       | well stop and look further instead of waiting 20 minutes for it
       | to finish.
        
       | paulryanrogers wrote:
       | There was a rumor about a place that configured OS alert sounds
       | as orchestra instruments. So that as folks were working it would
       | sound like an orchestra tuning up. Instead of lots of random
       | alert tones.
        
       | zanethomas wrote:
       | My dad used a transistor radio in a similar fashion.
        
       | polishedbadass wrote:
       | This is such a fascinating concept!
        
       | ramesh31 wrote:
       | This touches on something I've thought about for years, which is
       | what I refer to as "synesthetic computing" for lack of a better
       | term. It's the idea that as humans, we are innately endowed with
       | these _incredible_ abilities that no computer can possibly match,
       | like our ability to understand social situations and hierarchies,
       | and our ability to process and understand complex emotions. We
       | could potentially unlock whole new models of computation by
       | leveraging them. Imagine a data visualization environment where
       | instead of just looking at rows of spreadsheet data, each data
       | point had a  "personality", and was allowed to form "social
       | groups" autonomously with other data points. Those social groups
       | could then be analyzed in the same way we do with actual human
       | social interactions. Their reasons for grouping could be looked
       | at emotionally and understood through intuition. And those
       | intuitions could even be fed into machine learning models as a
       | heuristic for hyperparameter optimization.
        
         | zasdffaa wrote:
         | Hard to know what to make of such a suggestion, perhaps you
         | could flesh it out somewhat.
        
           | [deleted]
        
         | teddyh wrote:
         | Look into "Calm Technology":
         | 
         | https://calmtech.com/papers/designing-calm-technology.html
         | 
         | https://calmtech.com/
        
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       (page generated 2022-05-19 23:02 UTC)