- How Might We Code in VR? — caught my eye because I’m looking for ideas on how to think about interaction design in the holoculus world.
- Git Workflows for Pros — non-developers don’t understand how important this is to productivity.
- All Programming is Bookkeeping — approach programming as a bookkeeping problem: checks and balances.
- Why I Am Not a Maker (Deb Chachra) — The problem is the idea that the alternative to making is usually not doing nothing — it’s almost always doing things for and with other people, from the barista to the Facebook community moderator to the social worker to the surgeon. Describing oneself as a maker — regardless of what one actually or mostly does — is a way of accruing to oneself the gendered, capitalist benefits of being a person who makes products.
Common behavior to watch out for when transitioning to a PaaS
Today I am going to cover 5 ways developers may be on a Platform as a Service (PaaS) but have not really embraced the new platform effectively. If you have done any of these things below while building your application hosted on a PaaS, like OpenShift, Heroku, or Google App Engine, don’t feel bad:
- PaaS is a relatively new concept in the development world and I think some of these patterns are only recently coming to light
- I have seen veteran developers making these mistakes as they move to the new paradigm
One piece of terminology I will use throughout the article is container. When I am using this word I am referring to the piece of the PaaS that hosts the application and does the work. An application can be composed of multiple containers and the PaaS will probably have a method to add your favorite server-side tech to the container. On OpenShift this is called a gear while on Heroku it is called a dyno.
So without further ado, let’s dig in on some of the code smells in the cloud.
Making forking the norm
Forking another spec: generally less than ideal. Spooning w another spec: weird. Knifing another spec: generally indicative of larger issues
— вкαя∂εℓℓ (@briankardell) April 28, 2014
— Kip Hampton (@kiphampton) April 28, 2014
Free and Open Source software licenses make forking legal. Git makes forking easy. GitHub makes it easy to fork sociably. Can we just make this normal?
Meanwhile, in a reminder that specifications can fork too, Ian Hickson put his objections to the W3C forking a WHATWG spec on www-archive to make sure his complaints of plagiarism would be part of the permanent record. WHATWG specs are licensed CC0, so once again, it’s legal.
It seems to be a common pattern to want to grant rights, but only want other people to use those rights if they acknowledge our control. (I sometimes have similar tendencies, granted.) We hope that people will contribute to our works while recognizing our power and our ownership over those works. Even the fact that we have to choose licenses at the start of a project gives us a sense of ownership and control, often hiding the (excellent) lack of control that comes once those licenses are applied.
Disposable robot assassins and spreadsheets
Computers aren’t ready to write much of our code for us, but they can still help us clean and improve our code.
Bowkett explored many options and iterations of his automation ideas,
- The roots: Martin Fowler’s classic Refactoring. [at 00:50]
- “Probably the first time ever you see a developer or hacker enthusiastic about using a spreadsheet… I am that fluke.” [at 01:48]
- Matching method names with the ack and wc Unix command line utilities, and finding some useless methods. [at 5:58]
- “More complex information… surfacing an implicit object model.” [at 7:45]
- Filter scripts and text streams [at 14:45]
- “Towlie, because it liked to make things DRY”, using similarity detection in Ruby. [at 16:37]
- Building on JSLint [at 20:10]
- “Have script that… tells you this file is the one that people have edited most frequently. [at 30:29]
- Grepping through git history [at 32:53]
- “Automatic refactoring will let you get to better code much faster.” [at 36:25]
It’s an amazing mix of capabilities that let you build your own robot (code) assassins.
Assertions, regression tests, and version control
Programming any non-trivial piece of software feels like rock climbing up the side of a mountain. The larger and more complex the software, the higher the peak.
You can’t make it to the top in one fell swoop, so you need to take careful steps, anchor your harnesses for safety, and set up camp to rest. Each time you start coding on your project, your sole goal is to make some progress up that mountain. You might struggle a bit to get set up at first, but once you get going, progress will be fast as you get the basic cases working. That’s the fun part; you’re in flow and slinging out dozens of lines of code at a time, climbing up that mountain step by steady step. You feel energized.
However, as you keep climbing, it will get harder and harder to write each subsequent line. When you run your program on larger data sets or with real user inputs, errors arise from rare edge cases that you didn’t plan for, and soon enough, that conceptually elegant design in your head gives way to a tangled mess of patches and bug fixes. Your software starts getting brittle and collapsing under its own weight.
Can version control manage content?
Web designers? Git? Github? Aren’t those for programmers? At Artifact, Christopher Schmitt showed designers how much their peers are already doing with Github, and what more they can do. Github (and the underlying Git toolset) changes the way that all kinds of people work together.
Sharing with Git
As amazing as Linux may be, I keep thinking that Git may prove to be Linus Torvalds’ most important contribution to computing. Most people think of it, if they think of it at all, as a tool for managing source code. It can do far more, though, providing a drastically different (and I think better) set of tools for managing distributed projects, especially those that use text.
Git tackles an unwieldy problem, managing the loosely structured documents that humans produce. Text files are incredibly flexible, letting us store everything from random notes to code of all kinds to tightly structured data. As awesome as text files are—readable, searchable, relatively easy to process—they tend to become a mess when there’s a big pile of them.
Google's Data Centers, Top Engineers, Hiring, and Git Explained
- Google Has Spent 21 Billion on Data Centers — The company invested a record $1.6 billion in its data centers in the second quarter of 2013. Puts my impulse-purchased second external hard-drive into context, doesn’t it honey?
- 10x Engineer (Shanley) — in which the idea that it’s scientifically shown that some engineers are innately 10x others is given a rough and vigorous debunking.
- How to Hire — great advice, including “Poaching is the titty twister of Silicon Valley relationships”.
- Think Like a Git — a guide to git, for the perplexed.
Git Secrets, Ab Initio Keyboard, Continuous Deployment, and 3D Atomic Models
- More Git and GitHub Secrets (Zach Holman) — wizards tricks. (via Rowan Crawford)
- Building a Keyboard from Scratch (Jesse Vincent) — for the connoisseur.
- Practicing Deployment (Laura Thomson) — you should build the capability for continuous deployment, even if you never intend to continuously deploy.
- 3D Printed Atoms (Thingiverse) — customize and 3d-print a Bohr model of any atom.