Programming Leftovers

posted by Roy Schestowitz on Apr 21, 2025

• Linux Handbook ☛ 7 Utilities I Use to Boost Development Workflow Productivity

  Here are a few tools that I have discovered and use to improve my development process.

• Daniel Lemire ☛ Streamlined iteration: exploring keys and values in C++20

  In software, we often use key-value data structures, where each key is unique and maps to a specific value. Common examples include dictionaries in Python, hash maps in Java, and objects in JavaScript. If you combine arrays with key-value data structures, you can represent most data.

• Elliot C Smith ☛ Experiments are Bricks

  Given enough time, almost any A/B test style growth experiment you run will probably look meaningless. Even if you measure statistical significance, over a long time horizon that significance tends to fade. You shouldn’t expect every little change in copy and colors to continue to deliver uplift forever.

• Michał Sapka ☛ Commodore 64 Assembly, part 3: mnemonics, opcodes, pseudos, control commands, and tables

  Keywords which we write in assembly, like ldx or sdx are called mnemonics. They are what we, developers, can memorize write down. Assembler converts them into hexadecimal values, which the machine interprets as operation. This is what assembler does: it converts assembly language (with mnemonics) into machine code (with opcodes).

• [Old] Well-Typed LLP ☛ falsify: Hypothesis-inspired shrinking for Haskell

  In this first section we will discuss some of the background behind falsify; the next section will be a more tutorial-style introduction on how to use it. This section is not meant to an exhaustive discussion of the theory behind falsify, or how the theory differs from that of Hypothesis; both of those topics will be covered in a paper, currently under review. However, a basic understanding of these principles will help to use the library more effectively, and so that will be our goal in this first section.

• Simon Safar ☛ Error Handling and If Statements

  Error handling is one of those things which is pretty important if you do not want your code to die of fixable causes all the time. On the other hand, it's not especially exciting to read. It also tends to overcomplicate code by a decent amount. For example, look at this example: [...]

• Jeremy Bowers ☛ Functional Programming Lessons Conclusion

  And it wasn’t until I’d written several of these posts that I noticed the recurring theme of scale, that functional programming principles are best brought in to imperative languages at the medium scale rather than the micro scale. I find this insight to have been almost worth the writing on its own.

  I arranged these points roughly in order from least offensive to most offensive, so it’s possible that you arrive here thinking I do not like functional programming. But consider how much I have drawn from it. This is a good thing. I like it.

• Rlang ☛ Banking & Insurance Dataset for Data Analysis in RStudio

  When you are working on a project involving data analysis or statistical modeling, it's crucial to understand the dataset you're using. In this guide, we'll explore a synthetic dataset created for customers in the banking and insurance sectors.

• Go

  • Jeremy Bowers ☛ Layered Design in Go

    This post will describe how I design my programs in Go. I needed this for work, and while I searched for a link, nothing quite fits my coding practices out there. The word “Layered” can pull up some fairly close descriptions, but I want to lay out what I do.