Paul’s Substack

Paul’s Substack delves into programming innovations, techniques, and paradigms focusing on efficiency, simplicity, and the adaptation of programming to modern challenges. It covers specific programming approaches, tool development, language transpilation, and conceptual frameworks for understanding and improving developer experience and software architecture.

Programming Techniques Software Architecture Developer Experience Language Transpilation Message Passing Functional Programming Coding Paradigms Memory Management Developer Tools

The hottest Substack posts of Paul’s Substack

And their main takeaways
2 HN points 14 Jun 24
  1. Simplify type checks to optimize CPU performance. For example, using indices for type testing can be more efficient than complex branching.
  2. Functional Programming allocates data on a stack in LIFO order, simplifying garbage collection. This approach can lead to more efficient memory management.
  3. Atom interning, creating atoms only once, can be optimized using hash-table strategies for memory efficiency.
0 implied HN points 04 Jul 24
  1. Transpiling code between different languages can be challenging, especially when going from a low-level language like Scheme to a higher-level language like Python.
  2. Creating a higher-than-high-level language (HHLL) can help capture manual reverse-engineering processes and facilitate transpilation to different programming languages.
  3. Approaching complex coding tasks by manually writing scripts, creating grammars, and testing transpilers can help in achieving programming goals efficiently.
0 implied HN points 02 Jul 24
  1. Subroutines are not functions designed to support functional paradigms, but rather to save code space at the cost of extra CPU cycles. They are non-reentrant and not thread safe.
  2. Physics teaches the technique of 'divide and conquer' using simplifying assumptions to focus on areas of interest, pushing aside unnecessary details.
  3. Different problems, involving time like video sequencing, robotics, gaming, etc., may benefit from using programming languages with paradigms other than the function-based one, like Prolog for relational paradigm.
0 implied HN points 28 Jun 24
  1. Structured message passing involves handling multiple inputs in a specific order.
  2. FIFO queues maintain the order of message arrival, unlike LIFO strategies used in recursion.
  3. FIFO queues and dispatchers enable true asynchrony, which is different from function-based synchronous thinking.
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0 implied HN points 24 Jun 24
  1. Ceptre consists of a factbase and rules organized in groups called 'Stages'.
  2. Rules in Ceptre involve inhaling to match patterns against the factbase and exhaling to execute actions.
  3. The main loop algorithm of Ceptre involves deciding the current stage, pattern matching, executing actions, and potentially finishing the program.
0 implied HN points 15 Jun 24
  1. Using old solutions for new problems may not be efficient if the context has drastically changed over time.
  2. The advancements in technology and accessibility of CPUs and memory have transformed the landscape of programming, making old techniques from the 1950s less relevant today.
  3. To address modern programming challenges, consider utilizing message passing, embracing multiple programming languages, and creating IDEs that cater to the current technological environment.
0 implied HN points 14 Jun 24
  1. Paul Tarvydas has a Substack focused on programming simplicity.
  2. The Substack post is shared with a link and can be shared via various platforms like Facebook, email, and more.
  3. The post indicates that something new is coming soon.
0 implied HN points 28 Jun 24
  1. Function-based, synchronous thinking can't handle true asynchronous operation, needing a new 'clutch' for desynchronization.
  2. Networking protocols between truly asynchronous nodes show promise with state machines and Statecharts.
  3. Program development should incorporate multiple paradigms while focusing on creating little networks that use queues for non-synchronous communication.
0 implied HN points 08 Jul 24
  1. Specific notations can be devised to solve programming problems effectively, and they don't always have to be text-based.
  2. Total decoupling and isolation, referred to as '0D', can help combat flatness in design by enabling layering.
  3. Tools like OhmJS and Ohm-editor can streamline the creation of new, specific notations in a short amount of time.
0 implied HN points 05 Jul 24
  1. Transpiling from a lower level language to a higher level language is harder than the reverse.
  2. Python poses challenges due to its higher level nature and restricted control structures compared to Scheme.
  3. Writing a transpiler is simpler than the reverse-engineering task involved in transpiling.
0 implied HN points 04 Jul 24
  1. Reading is a form of linear thinking in 2D with text arranged on paper.
  2. Computers offer a 4-dimensional medium for creation, with dimensions x, y, z, t.
  3. People don't necessarily need to know programming, just utilize the new 4D medium for various purposes like gaming, robotics, and ubiquitous computing power.
0 implied HN points 27 Jun 24
  1. Routing involves sending messages between components like parent and child containers.
  2. Basic routing includes sending messages down from parent to child, across between children, and up from child to parent.
  3. Consider factors like multiple output messages, multiple inputs and outputs, and different routing scenarios when designing a routing system.
0 implied HN points 24 Jun 24
  1. The Complexity Elision Pyramid proposes building multiple Solution Centric Notations (SCNs) for each project, streamlining programming language creation and problem-solving.
  2. By eliding low-level implementation details, programmers can focus more on intricate problem-specific aspects rather than technical specifics.
  3. Layers of the pyramid represent distinct aspects of the problem space, with each layer building upon the one below in a manner akin to low-level assembly instructions.
0 implied HN points 15 Jun 24
  1. Development often involves failure, iteration, and debugging until a program becomes stable enough to ship.
  2. To cope with an iterative workflow, consider writing software that generates code, allowing you to easily make changes and regenerate code as needed.
  3. Creating little DSLs specific to each project, using tools like PEG parsing, can help simplify coding, debugging, and adapting to new insights about the problem space.