data-oriented programming

Mike Acton of Insomniac Games argues that a program's purpose is transforming data, and shows how common C++ approaches work against that in performance-critical game development. He covers cache behavior, data layout and the limits of compilers.

Brian Will makes the case for procedural programming over object-oriented programming, arguing that OOP's promised encapsulation and decoupling are largely illusory. He analyzes real code examples and the problems of tying data to behavior in classes.

Andrew Kelley, creator of Zig, presents practical data-oriented design techniques for shrinking memory footprint and making programs cache friendly. He ends with a case study of how these ideas sped up the Zig compiler.

A CppCon 2018 talk arguing that OOP has failed to deliver on reuse and performance, and presenting data-oriented design for C++ with practical worked examples from real systems.

Brian Will critiques object-oriented programming and rewrites a roughly 3800-line OO program in a procedural style, cutting code and complexity. It is part of a series of OOP critiques.

A live-coded demo by Jonathan Blow showing how to get object-system-style expressiveness in a data-oriented way, covering structure-of-arrays layouts and composition. It shows features of his Jai language that make programs fast.

Raph Levien presents his new Rust GUI framework, built on data-oriented design and ideas from entity component systems, for the Xi editor. He weighs the approach against alternatives and discusses pros and cons.

A long recorded seminar in which Alan Kay discusses object-oriented programming, probably from the mid-1980s. He covers the original idea of objects, messaging and the work done at Xerox.

Brian Will follows up his earlier anti-OOP video by walking through four short code examples, including Java code in the style of Uncle Bob, to show how object-oriented design complicates simple programs. It argues that OOP hides and scatters state and adds needless indirection.

An animated ranking of the most popular programming languages from 1965 to 2019, built from popularity indexes, GitHub access data and historical surveys.

James Powell's nearly two-hour PyData talk builds up Python's data model, decorators, generators and context managers, coding live in Vim. It aims to take intermediate programmers toward real Python expertise.

Rich Hickey, creator of Clojure and designer of Datomic, gives a JaxConf 2012 talk that takes apart traditional database architecture. He presents a different way to think about databases and explains the reasoning behind Datomic's fact-based design.

Juan Pedro Bolivar Puente explains immutable and persistent data structures in C++ and how they support value semantics. He presents the Immer library, rrb-trees, and a prototype text editor that opens a huge file instantly.

Simon Peyton Jones explains nested data parallelism and Data Parallel Haskell, an approach to exploiting multicore and distributed hardware while keeping a simple single-control-flow programming model.

Robert C. Martin (Uncle Bob) traces the history of software from 1948 to today, looking at the problems programmers faced, how they were solved, and what mistakes the profession made. He then projects where the field is going, including professionalism and regulation.

Rich Hickey's talk at Clojure's tenth anniversary on the kind of programs Clojure is designed for. He argues for situated programs that deal with changing requirements, and for dynamic typing and data over static types.

Mark Bastian contrasts top-down object-oriented design with bottom-up, data-oriented design in Clojure. He models a board game as plain data plus small composable functions and compares it with a roughly 22-class OOP version.

Casey Muratori's two-hour talk tracing the history of object-oriented programming back to the 1960s and examining how its ideas, and later entity component systems, came about. It is followed by a Q&A.

Kevlin Henney argues that procedural programming never went away despite later paradigms such as OO and functional. He traces the history of structured programming and shows where procedural thinking still lives in modern code and why it matters for readability.

Luca Sas's ACCU 2021 talk on Modern C, a style of C and C-like C++ aligned with data-oriented design. It covers centralized memory management, zero-is-initialization, error handling and API design.

A short clip of Casey Muratori from Handmade Hero explaining why he rejects the object-oriented mindset and how to move away from it. It is part rant, part programming philosophy.

Kevlin Henney revisits structured programming, from Go To Statement Considered Harmful to block-structured code and object orientation. He argues it still matters for how we write code today.

The first lecture of Andy Pavlo's CMU 15-445 Intro to Database Systems (Fall 2019), covering course introduction and the relational model.

Michael Arntzenius's Strange Loop talk on Datafun, a functional query language that brings database-style querying into a general-purpose language. It discusses bridging database theory and programming languages.

Richard Feldman's elm-conf talk on designing models so that bugs from impossible application states cannot occur, using Elm's compiler and types. It demonstrates techniques for making invalid states unrepresentable.

Rafal Dittwald's Clojure/north talk shows how to move from writing Java-style code in Clojure to thinking in data-driven, functional terms. He walks through a JavaScript example, refactoring imperative code step by step into a functional core.

A five-minute excerpt of Rich Hickey's Clojure Made Simple talk, with new slides, ranting about HttpServletRequest and specificity. He argues for using generic maps instead of many specific classes and getters.

Jafar Husain's ACM keynote presents Netflix's JSON Graph and Falcor, which let web developers treat all cloud data as one virtual JSON model. It combines reactive programming with REST principles.

Tef's EMF 2012 talk on lessons from a career in programming, a candid and humorous look at why programming is so often terrible. Slides and a draft script are available online.

A 1991 NeXT promotional video that stages a head-to-head programming contest between a NeXT computer and a Sun workstation. It shows NeXT's interface builder and object-oriented tooling producing an application far faster than traditional UNIX development.

Sean Parent of Adobe argues that object-oriented frameworks ultimately fail to deliver scalable, high quality software and proposes combining generic and declarative programming instead. It draws on Stepanov's Elements of Programming.

A five-minute lightning demo of VisiData, a terminal tool for exploring and manipulating data. It uses two months of NYC 311 complaint data to drill down, plot points on a virtual map and save selected rows.

John Oliver's Last Week Tonight segment explains how data brokers collect and sell personal information, including a stunt in which his team bought data to identify members of Congress.

Database pioneer Michael Stonebraker argues that 'big data' is really at least four different problems: big volumes with small analytics, big analytics, velocity, and variety. He comments on where each market is heading.

Felienne Hermans argues that Excel is the world's most popular programming language and shows how spreadsheets work as a pure functional language. She implements a few mathematical problems in spreadsheet formulas to illustrate why they are so powerful and approachable.

Lee Byron of Facebook explains how persistent immutable data structures work and how to use them in React apps with Immutable.js. He covers memoization benefits and avoiding coupling through shared mutable state.

Benn Jordan investigates infrasound and low-frequency noise from data centers, including xAI's Colossus and a crypto mine, and reports his own experiments on the effects. The video covers the health and community impacts on nearby residents.

Peter Norvig's 2007 Google talk on theorizing from data, covering what huge datasets can do for language understanding, translation, information extraction and inference. It argues that more data often beats cleverer models.

A Business Insider investigation into the US boom in AI data centers, mapping where they are, who owns them, and how much power and water they consume. It looks at the costs borne by communities, with a focus on Virginia.

Peter Norvig's UBC distinguished lecture on how massive amounts of simple data, such as for language modeling, can yield understanding that hand-built models could not.