Programming by any other name - Bob 2020

# Programming by any other name

Mariano Guerra [@warianoguerra](https://twitter.com/warianoguerra)

[instadeq.com](https://instadeq.com) [@instadeq](https://twitter.com/instadeq)

[Slides @ marianoguerra.github.io](https://marianoguerra.github.io)

???

Will go over many things fast, I want to cover all the possibilities, you can
later focus on the ones you like

y will read from slides because I'm a newbie on almost all of them and I don't
want to say things that are wrong so much :)

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# Java, Scala, Clojure(script), Erlang, Rust, Elixir

# and Tons of Javascript

https://futureofcoding.org/

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# Why

Can be as productive as anyone today with tools from the 70s (vim, bash, make, grep, unix)

With the right tools from the 70s/80s someone can be much more productive (Smalltalk, Lisp)

A Computer scientist to Create a CRUD app (with bugs)

VC funding to create a To Do app (with bugs)

Supercomputers on the table, no way to make them do something together

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Not a "the grass was greener in the 70s" guy,
just a "the grass is greener somewhere today, let's go there"

The failures are "around" the languages, all the scafolding that falls outside
what we call a programming language, maybe we should start considering
programming environments

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# Hypernormalization

Everyone in the Soviet Union knew the system was failing

???

Let's break this local maxima and search for another higher ones

But no one could imagine an alternative to the status quo

Politicians and citizens were resigned to maintaining the pretense of a functioning society

Over time, this delusion became a self-fulfilling prophecy

The fakeness was accepted by everyone as real

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# It is difficult to make predictions

## especially about the future

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# The future is already here

## it’s just not evenly distributed

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You can see it in the past, if you went to the right places you could see
smalltalk and lisp in the 70s

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![HN Orange](img/hn-orange.png)

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![HN Gray](img/hn-gray.png)

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# Glamorous Toolkit

The **moldable** development environment.

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If you leave the environment you loose

A live notebook.

A flexible search interface.

https://gtoolkit.com/

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SmallTalk, Object Oriented, Programming Environment

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# Glamorous Toolkit

A fancy code editor.

A software analysis platform.

A data visualization engine.

All in one.

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The Inspector lets you define **custom presentations for any object**.

The **Playground** powers up the inspector and makes the code part of the live inspection flow.

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**Define examples** throughout the code and use them **for documentation or testing**.

A developer can **switch from static code to a live environment** and
program in the presence of objects.

It **enables example-driven development**.

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Every object can say how it can be searched.

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Debugger lets you **build custom debuggers** that can be used when debugging

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Live slide shows are another way to **construct interactive narratives that
complements documents**.

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**Visualization is a first-class citizen in the environment**.

It contains a few programmable engines including Mondrian, for **drawing graphs**,
and Connector, for identifying connections between various objects.

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Built on top of the Bloc vector-based graphical framework.

It relies on **exactly one rendering tree at all times** without the need of an intermediate canvas.

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Create and consume code **documentation and tutorials directly in the environment**.

It transforms the environment into a data science tool.

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Release workflow built-in

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# Darklang

ML/Elm like

https://darklang.com/

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Good for "serverless" stuff, quick prototyping, small apps that need a backend
glue between systems, integrations, webhooks, bots, email automation

Structured editor

Web Based

Private Beta

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Implemented in OCaml?

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Canvas Cell Types

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Structured Editor

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Pervasive Autocomplete

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Command Palette

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Run HTTP Requests

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New handler autoconfigures with trace contents

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Requests without handlers go to the 404 section

Inspect and create new handler for those requests

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Builtin data store

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Incomplete evaluation

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# Unison

Open Source

Distributed programming language

Always live, never broken code bases

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# Unison

Supports algebraic effects ('abilities'), replace monads 🌯

Programs are not text

Content-Addressed Code

Names are metadata

Codebase is append only

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Implemented in Haskell

Influences: Haskell, Erlang, [Frank](https://arxiv.org/abs/1611.09259)

Statically Typed

Decomplect Names

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A unison program can describe an entire elastic distributed system that deploys itself at runtime

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> This particular API is also "serverless" in the sense that nodes are not part of the programming model; instead it's **up to the handler to decide how the forked computations get scheduled onto actual machines**.

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# Unison Properties

No Builds

Rename Trivialy

Cache unit test results

No dependency conflicts

Automatic Serialization

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# Unison UX

* Scracth file and a REPL

* Use your favorite text editor

* Search for definitions by name, by type

* REPL watches for changes on the scratch files

* Once definitions are committed they can be removed from the scratch files

* Definitions can be loaded into the scratch file to continue working

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# Netlogo

What do ants, bees, traffic jams, slime mold, forest fires, segregation, fireflies, birds and kevin bacon have in common?

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# Fireflies

https://ncase.me/fireflies/

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NTP style clock synchronization algorithm

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Pheromones to signal the path to food

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Consensus algorithm to agree on the location of the next hive

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Flock formation

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Phase transition on forest fire extension when tree density goes over a threshold

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Emergent segregation pattern in neighborhoods when two types of agents want to
live near a small percentage of agents like them.

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This model explores the formation of networks that result in the “small world”
phenomenon – the idea that a person is only a couple of connections away any
other person in the world.

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# Explorabe Explanations

https://explorabl.es/

http://worrydream.com/ExplorableExplanations/

https://www.complexityexplorer.org/

https://distill.pub/

https://ncase.me/

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# Hazel

["Hazel: A Live Functional Programming Environment with Typed Holes"  by Cyrus Omar](https://www.youtube.com/watch?v=UkDSL0U9ndQ&feature=emb_title)

[hazel.org](https://hazel.org)

[Play with Hazel](https://hazel.org/build/master/index.html)

An experimental programming **environment**

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# Hazel

Every incomplete program that you can construct

Using Hazel's language of type-aware edit actions

Is both statically and dynamically well-defined

It has a (possibly incomplete) type

Can run it to produce a (possibly incomplete) result

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# Hazel

Structural, type-aware edit actions (Automatic hole insertion)

A structural/projectional editor

Tries to feel like editing text

Execution doesn't stop on holes

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# Hazel: Types of holes

Empty holes for partial expressions

Non empty holes for errors (like dynamic type errors)

Free variable holes for binding errors

Conflict holes (roadmap)

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**A structural/projectional editor**

- syntax highlighting
- autoformatting
- context-free tree transformations
- Type and context inspection
- Semantic navigation
- Context-sensitive tree transformations (refactorings)
- Environment inspector

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# Dynamic Land

https://dynamicland.org/

[The Humane Representation of Thought](https://vimeo.com/115154289)

Dynamicland is a **communal computer**

Designed for **agency, not apps**

Where people can **think like whole humans**

The computer of the future is not a **product**, but a **place**

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# Dynamic Land

Programming conflates 2 things

Engineering 👉 communicate intent to Computers

Authoring 👉 communicate intent to Humans

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# Lasp

> Lasp is about writing correct distributed programs.

> Write a program once and know that it will behave the same whether it is executed on one computer or distributed across many.

https://lasp-lang.readme.io/

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# Automerge

> A JSON-like data structure (a CRDT) that can be modified concurrently by different users, and merged again automatically.

https://github.com/automerge/automerge

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# Programming by Example/Demonstration

[Your Wish is My Command: Programming by Example ](http://web.media.mit.edu/~lieber/PBE/Your-Wish/)

[Watch What I Do: Programming by Demonstration](http://acypher.com/wwid/)

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# Chemical Computing

Encompassed the **definition of molecules, reaction
rules, and the topology and dynamics of the reaction space**.

This kind of chemical information processing is known to be **robust,
self-organizing, adaptive, decentralized, asynchronous, fault-tolerant, and
evolvable**.

Computation **emerges** out of an orchestrated interplay of **many decentralized
relatively simple components** (molecules).

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# Amorphous Computing

Agents run asynchronously, are interconnected in unknown and possibly time-varying ways, communicate only locally, and are identically programmed.

If we suppose that each cell is a computing element whose program is encoded in
DNA, then an embryo would be a massively distributed system that runs a single
program on all its elements and produces a globally coherent result.

The study of amorphous computing seeks to identify and apply the engineering
principles behind the coordination of such a multitudinous distributed system.

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An amorphous computing system is a large collection of irregularly placed, lo-
cally interacting, identically-programmed, asynchronous computing elements [1].
We assume that these elements (agents) communicate within a fixed radius, which
is large relative to the size of an element, but small relative to the diame-
ter of the system. We also assume that most agents do not initially have any
in- formation to distinguish themselves from other agents; this includes
information such as position, identity and connectivity. The challenge of
amorphous comput- ing is to develop computing paradigms that enable us to write
programs that when executed on each agent produce some pre-specified emergent
behaviour.

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# Autonomic Computing

**Inspired by the human autonomic nervous system**. Its goal is to realize computer and software systems that can manage themselves in accordance with high-level guidance from humans.

A **homeostatic system** is an open system that maintains its structure and
functions by means of a **multiplicity of dynamic equilibriums** that are
rigorously controlled by **interdependent regulation mechanisms**.

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# Autonomic Computing

Such a system reacts to every change in the environment, or to every random
disturbance, through a series of modifications that are equal in size and
opposite in direction to those that created the disturbance.

The goal of these modifications is to maintain internal balances.

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An autonomic computing system requires:

(a) sensor channels to sense the changes in the internal and external environment, and

(b) motor channels to react to and counter the effects of the changes in the environment by changing the system and maintaining equilibrium.

The changes sensed by the sensor channels have to be analyzed to determine if
any of the essential variables has gone out of their viability limits.

If so, it has to trigger some kind of planning to determine what changes to
inject into the current behavior of the system such that it returns to the
equilibrium state within the new environment.

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# Robust-first Computing

> Deterministic machines will crash, seize-up, or otherwise misbehave when virtually anything goes wrong inside them; living organisms, by contrast, can suffer grievous injury and yet survive, handle the immediate situation, and get away long enough to heal up and live on.

[Site](http://robust.cs.unm.edu/doku.php), [Resources](http://robust.cs.unm.edu/doku.php?id=introduction:where_can_i_get_more_information)

[T2 Tile Project](https://www.youtube.com/channel/UC1M91QuLZfCzHjBMEKvIc-A)

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A system is robust if it tends to do something sensible even when it's design assumtions are under stress or violated

A lot of computer science is about using computer hardware efficiently

Efficiency and robustness are at odds over redundancy
* robustness requires
* efficiency eliminates

We should put robustness first and view maximizing efficiency not as an inherent virtue, but more as a regrettable sometimes necessity

The world has changed, hardware is much cheaper, more powerful than we need for a given task

And there are bugs everywhere

But we are still carrying the Correctness and Efficienty Only attitude

We should change the attitude and put robustness first and see what that would mean

- Movable Feast Machine (MFM)
    - Indefinite scalability
    - Inherent robustness
    - 2D grid of individual sites
        - Each site can hold dozens of bits or hundreds
        - Each site has processing power
        - Many things going on at once
        - Each site can be empty of have an atom
            - DReg: dynamic regulator
            - There's no global origin
            - From the POV of the given atom it is the center, everything is relative to the self (indexing), short ranged
            - Event window: the limit of number of sites that can be accessed by a given atom (4 in any direction, 41 total)
            - Can read and write to the event window arbitrarily when executing
            - MFM can be executing many events simultaneously as long of no event windows overlap

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# A way to predict the future...

## is to find it in the present and be part of it

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# Danke

Mariano Guerra [@warianoguerra](https://twitter.com/warianoguerra)

[instadeq.com](https://instadeq.com) [@instadeq](https://twitter.com/instadeq)