stats VS goodreads-toolbox

> do not believe in the possibility of a "General Theory of Productivity." I'm highly skeptical of attempts to quantify the precise relationship between error discovery stage and cost in a way that is generalizable, although I think it might be possible given a large group of engineers using a highly homogenous process, tools, and accounting. Google is pretty close to this (common dev infrastructure across tens of thousands of engineers), and even across Google this kind of generalization would be extremely difficult.

I don't think you are incorrect, but I think a lot of the aspirants behind ESE just want to have a better sense of what works and what doesn't; I'd even welcome negative results! The current state of things is to read 100 opinionated people and their blog posts. And given enough time, you'll encounter someone who swears that after drinking their morning coffee and jumping on one foot for 1 min, they enter a VRChat standup with their team and hit max flow. There's just so little knowledge right now about what works and what doesn't that I'd welcome more clarity, especially negative results.

> As a result, academic research into productivity can be difficult to generalize

I think defects are what we should measure for, not productivity because of the subjectivity of measuring productivity. But even measuring defects is complicated. The best way I see to measure defects is to ask a Team Under Test to document bugs that they encounter along with resolution times, but this is not only expensive, but something I doubt most corporations will be willing to share outside of their walls. Perhaps open source projects can try to store this data, like curl's stats [1].

[1]: https://github.com/curl/stats

I know nothing about Linux, Docker, or Perl, and am only minimally confident at the command line, but I really wanted to play around with this Goodreads toolbox. Unfortunately it has minimal documentation and is no longer supported by the author, but nothing ventured, nothing gained, right? I actually got Docker installed, successfully ran the toolbox in a container, connected to Goodreads and ran one of the Perl scripts which successfully generated two HTML output files. However, here I am at the finish line and I have no idea how to actually find or open these files.

Don't know about the mobile app, but the desktop website does not offer this feature. There's just https://www.goodreads.com/book/friend_reading ("Books My Friends Are Reading" at the moment). If you have Linux/Linux-friend/Docker or perhaps Windows Subsystem for Linux (WSL), you could try a separate tool made for finding Goodreads books popular among your friends: https://github.com/andre-st/goodreads-toolbox/blob/master/help/friendrated.md

At that time I had developed prototypes for these features for Linux users. For those interested in the (archived) forum posts, dates and links can be found at the top of each program's help pages at https://github.com/andre-st/goodreads-toolbox