Notes

Years ago I wrote about my enthusiasm for automation of toil. The advent of coding agents is the first time I’ve faced automation of a task I enjoy. I enjoy developing software, and I enjoy coding.

For fun projects, the ‘return’ on the investment is ‘fun’—and sometimes the fun is in the coding, sometimes it’s in solving the problem, and sometimes it’s in solving the problem by coding.

I found programming fairly young. I was lucky to have a computer and a technologist father who encouraged my interest. I enjoyed coding: making something “go”. I also enjoyed solving problems. Initially these were problems like “how do I make it do what I want” or pursuing an interest in a language or tool.

It was Monday, November 18, 2013 around 10:00 a.m. and I was standing in a humid Florida parking lot in the midst of a large crowd of people. We were all waiting to get on one of the many buses that had gathered there.

We all had good reason to be waiting in that parking lot. The buses were going to the NASA Causeway where we would get to see a rocket launch a spacecraft on its way to Mars.

Suppose you’re building a service that depends on several other services to work. You write a bunch of code and carefully include error handling code and have a plan for what happens if each service your new service calls fails. Naturally, you want to test your code. These services are invoked over a network. Perhaps they’re web services but they may be some other network protocol. Suppose further your code is nicely factored so there’s a “client” class that presents the network service as a library API to the rest of the service.

Code is communicating. Communicating with the computer to make it do something useful. Communicating with the future people that will read and maintain the code.

The former doesn’t care how clever you are. The latter may know where you live. The latter may be you.

You’ve got a choice to make. You’ve carefully written down the various attributes you care about and how well each choice lines up with those attributes. You’re having a hard time making a decision because with the information you have now they all look very similar. One of the following is true:

• You’re missing attributes with which to evaluate the choices, attributes which would differentiate the choices for you
• You’re incorrect about how well the choices match your evaluation criteria
• There really is no difference between the choices given information you can have now (ruling out somehow getting future knowledge)

Don’t discount the possibility that the situation is the last one. Due diligence is important but don’t block forever waiting for some flash of information that will never come. Don’t discount the opportunity cost of not making the decision and moving on to the next thing to do – sometimes that outweighs any potential cost caused by picking the worst possible choice among those you have selected. Never spend more energy on a decision than the cost of being wrong.

In my learning programming post I wrote about some approaches for learning to program and linked to a bunch of resources. Some of my insightful friends pointed out that most programming teaching doesn’t cover debugging and that lack leads to a lot of frustration. This is particularly hard on those working alone or with other people that don’t know how to debug.

Debugging is the art of figuring out why a system doesn’t work. The skills of debugging apply not just to errant programs but to any system that needs diagnosis.

I’m interested in how people learn to program. Over the past few years, friends or relatives have asked me about resources for learning to program for themselves or for people they know. I’ve collected and refined that advice here. It’s hard to know what approach will work for someone to learn to program. It’s hard work so it’s important that each step be interesting and rewarding enough to keep going particularly when there’s no external force such as formal courses.

RFC 761 section 1.2.2.

2.10. Robustness Principle TCP implementations should follow a general principle of robustness: be conservative in what you do, be liberal in what you accept from others.

RFC 1122 elaborates with section 1.2.2.:

1.2.2 Robustness Principle

At every layer of the protocols, there is a general rule whose application can lead to enormous benefits in robustness and interoperability: “Be liberal in what you accept, and conservative in what you send”

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I’m pretty passionate about automating tasks. I don’t think people should spend time doing things that computers can do, especially when automating those things is easy. I have, in the past, slid down expansive, deep ratholes writing a program to automate some grunt work or another. Sometimes the time to write the program takes longer than doing it by hand, but I believe the time was still well spent because of learning during the automation or because of how unlikely it is that the grunt work will really only have to be done once.

I’m a software developer. There are tools I like and have successfully built applications using but I also enjoy learning new tools and languages.

My goal is to use the best tool for the job. Most of the time the “best tool” is not a choice based entirely on the merits of one platform over another. If I want to hack my WordPress install, I have to use PHP. If I want to use Lucene for something, I have to use Java.