Christmas books for 2020

Derek Jones from The Shape of Code

A very late post on the interesting books I read this year (only one of which was actually published in 2020). As always the list is short because I did not read many books and/or there is lots of nonsense out there, but this year I have the new excuses of not being able to spend much time on trains and having my own book to finally complete.

I have already reviewed The Weirdest People in the World: How the West Became Psychologically Peculiar and Particularly Prosperous, and it is the must-read of 2020 (after my book, of course :-).

The True Believer by Eric Hoffer. This small, short book provides lots of interesting insights into the motivational factors involved in joining/following/leaving mass movements. Possible connections to software engineering might appear somewhat tenuous, but bits and pieces keep bouncing around my head. There are clearer connections to movements going mainstream this year.

The following two books came from asking what-if questions about the future of software engineering. The books I read suggesting utopian futures did not ring true.

“Money and Motivation: Analysis of Incentives in Industry” by William Whyte provides lots of first-hand experience of worker motivation on the shop floor, along with worker response to management incentives (from the pre-automation 1940s and 1950s). Developer productivity is a common theme in discussions I have around evidence-based software engineering, and this book illustrates the tangled mess that occurs when management and worker aims are not aligned. It is easy to imagine the factory-floor events described playing out in web design companies, with some web-page metric used by management as a proxy for developer productivity.

Labor and Monopoly Capital: The Degradation of Work in the Twentieth Century by Harry Braverman, to quote from Wikipedia, is an “… examination the nature of ‘skill’ and the finding that there was a decline in the use of skilled labor as a result of managerial strategies of workplace control.” It may also have discussed management assault of blue-collar labor under capitalism, but I skipped the obviously political stuff. Management do want to deskill software development, if only because it makes it easier to find staff, with the added benefit that the larger pool of less skilled staff increases management control, e.g., low skilled developers knowing they can be easily replaced.

Regressive Tendencies – a.k.

a.k. from thus spake a.k.

Several months ago we saw how we could use basis functions to interpolate between points upon arbitrary curves or surfaces to approximate the values between them. Related to that is linear regression which fits a straight line, or a flat plane, though points that have values that are assumed to be the results of a linear function with independent random errors, having means of zero and equal standard deviations, in order to reveal the underlying relationship between them. Specifically, we want to find the linear function that minimises the differences between its results and the values at those points.

Announcing Smolpxl Scores – a high score table for your game

Andy Balaam from Andy Balaam's Blog

It’s a very early beta for now, but I’m ready to announce Smolpxl Scores, which provides high-score tables for Free and Open Source games.

Each game can have multiple high-score tables – for example, you might want one for each level.

At the moment it’s deployed in my own web hosting and therefore written using the technologies that are most convenient for me to deploy there, which is PHP+MySQL. If it becomes more widely used and the performance suffers I guess I’ll ask for donations to host it somewhere else, and use more fashionable technologies.

To add a score you make a POST request like this:

curl https://scores.artificialworlds.net/api/v1/myappname/mytablename/ -d \
    '{"appId":"myappid","name":"Megan Tria", "score": 13.5, "notes": ""}'

and to look at some existing scores you can request them by pages:

curl 'https://scores.artificialworlds.net/api/v1/myappname/mytablename/?startRank=11&num=20'

or by name:

curl 'https://scores.artificialworlds.net/api/v1/myappname/mytablename/?startName=David%20Lloyd%20Geo&offset=-5&num=10'

The results are ordered by players’ scores, and are provided as JSON.

Each table stores only one score per player.

Of course, the API will evolve over time, but I hope that what I have now will be good enough to support some real-life games, and provide enough feedback to make it better.

As soon as people are actually using it, I will ensure the current API version (v1) remains stable, and release any incompatible updates as later versions.

If you’d like to use Smolpxl Scores to add a high-score table to your game, please create an issue at gitlab.com/smolpxl/smolpxl-scores/-/issues.

This service is only available to Free and Open Source games. Also, if someone abuses it (accidentally or on purpose) I will talk to them, and may eventually have to remove their access if we can’t fix the problem.