How a Python function relates to a two thousand year old debate in philosophy

We describe the vision of being able to reason about the design space of data structures. 
We break this down into two questions: 1) Can we know all data structures that is possible to design?  2) Can we compute the performance of arbitrary designs on a given hardware and workload without having to implement the design or even access the target hardware?
If those challenges are possible, then an array of exciting opportunities would become feasible such as interactive what-if design to improve the productivity of data systems researchers and engineers, and informed decision making in industrial settings with regards to critical ardware/workload/data structure design issues. Then, even fully automated discovery of new data structure designs becomes possible. Furthermore, the structure of the design space itself provides numerous insights and opportunities such as the existence of design continuums that can lead to data systems with deep adaptivity, and a new understanding of the possible performance trade-offs. Given the universal presence of data structures at the very core of any data-driven field across all sciences and industries, reasoning about their design can have significant benefits, making it more feasible (easier, faster and cheaper) to adopt tailored state-of-the-art storage solutions. And this effect is going to become increasingly more critical as data keeps growing, hardware keeps changing and more applications/fields realize the transformative power and potential of data analytics.  
This paper presents this vision and surveys first steps that demonstrate its feasibility. 

Why on earth would someone would pick C to start a new project in 2020? Surely there is a newer language with more shiny features that’s better right? Well I can’t speak for other people but I’ll tell you my reasons.

First of all let me preface this by saying that of course this is a biased opinion and the language I pick for something depends on the context it’s going to be used in. For example; I doubt I’ll ever be reaching for C when writing a web service simply because the ecosystem around that domain isn’t great and I’m not itching to write my http framework at this time.

But for games, more specifically cross-platform games C is a clear winner for me because it provides me with exactly the things I’m looking for which is reliability, simplicity and performance.

Vstr is a string library, it's designed so you can work optimally with readv()/writev() for input/output. This means that, for instance, you can readv() data to the end of the string and writev() data from the beginning of the string without having to allocate or move memory. It also means that the library is completely happy with data that has multiple zero bytes in it.

This design constraint means that unlike most string libraries Vstr doesn't have an internal representation of the string where everything can be accessed from a single (char *) pointer in C, the internal representation is of multiple "blocks" or nodes each carrying some of the data for the string. This model of representing the data also means that as a string gets bigger the Vstr memory usage only goes up linearly and has no inherent copying (due to other string libraries increasing space for the string via. realloc() the memory usage can be triple the required size and require a complete copy of the string).

Like many developers, I have been interested in Rust for quite some time. Not only because it appears in so many headlines on Hacker News, or because of the novel approach the language takes to safety and performance, but also because people seem to talk about it with a particular sense of love and admiration. On top of that, Rust is of particular interest to me because it shares some of the same goals and features of my favorite go-to language: Swift. Since I've recently taken the time to do try out Rust in some small personal projects, I wanted to take a little time to document my impressions of the language, especially in how it compares to Swift.

The tradition of a "Hello, World" program goes back at least to 1978. But for modern coders, what's an appropriate "Hello, World"?

This is an easy to understand example based tutorial aimed at those who know nothing of awk.

Python codes implementing algorithms described in Bishop's book "Pattern Recognition and Machine Learning"

Comparison among the number of command line options for various commands for v7 Unix (1979), slackware 3.1 (1996), ubuntu 12 (2015), and ubuntu 17 (2017).

The number of command line options has dramatically increased over time; they tend to have more options and there are no cases where programs have fewer options.

The C language is still prominent in the industrial embedded world, where “IoT” often refers to platforms much more limited than a Raspberry Pi. Often having to deal with such environments, we wrote the following informal explainer about C for internal company needs, and thought it could be of interest for more readers. This is basic material, mixing C and operating systems knowledge, aimed at readers with no or limited understanding of how you go from C source code to an executable. We could expand on many points, but for now we just share this meandering overview.

In order to increase fluency in a programming language, one has to read a lot of it. But how can you read a lot of it if you don't know what it means?
In this article, instead of focusing on one or two concepts, I'll try to go through as many Rust snippets as I can, and explain what the keywords and symbols they contain mean.

Ready? Go!

The C10k problem is still a puzzle for a programmer to find a way to solve it. Generally, developers deal with extensive I/O operations via thread, epoll, or kqueue to avoid their software waiting for an expensive task. However, developing a readable and bug-free concurrent code is challenging due to data sharing and job dependency. Even though some powerful tools, such as Valgrind, help developers to detect deadlock or other asynchronous issues, solving these problems may be time-consuming when the scale of software grows large. Therefore, many programming languages such as Python, Javascript, or C++ dedicated to developing better libraries, frameworks, or syntaxes to assist programmers in managing concurrent jobs properly. Instead of focusing on how to use modern parallel APIs, this article mainly concentrates on the design philosophy behind asynchronous programming patterns.

Ballerina is an open source programming language and platform for cloud-era application programmers to easily write software that just works.

Some hints: Naming Convention; Keyword First Syntax; Type Last Syntax; No Dangling Else; Everything Is An Expression, Including Blocks; etc.

Panolens.js is based on Three.JS (a 3D framework) with specific interest area in panorama, virtual reality, and potentially augmented reality.

There are lots of laws which people discuss when talking about development. This repository is a reference and overview of some of the most common ones.

Some examples: Hofstadter's Law, Kernighan's Law, Metcalfe's Law, Moore's Law, Murphy's Law, Occam's Razor, etc.