Simulink, yakindu, and the lifecycle modeling language (LML) folks all come to mind.

And of course SysML

Though I think LML is a better approach

Thanks Chris! I guess I still see those tools in the CAD/SIM/FAB camp, at least Simulink and yakindu, though I prob need to make another category for “business processes” (which I still don't think the UML family has done a great job solving). For me 'convivial computing’ intends something I might use to build/edit my own tools (notes, todos, etc) in a live environment.

Huh i hadn't taken a close look at LML though, that does look worth knowing

Also Netlogo which is getting discussed at https://futureofcoding.slack.com/archives/C5U3SEW6A/p1635772261029400?thread_ts=1635772261.029400&cid=C5U3SEW6A

Dalton, are you suggesting using simulation metaphors for things like programming email filters? 🤔

Would HyperCard and HyperTalk fit the bill?

this will probably sound overly philosophical but i’m not trying to be.. just what seems to happen when i try to coherently define terms.

first off, science & engineering is almost always based on the assumption that we share a common ‘reality,’ which we come to understand through our band-limited, unreliable faculties of sensing and cognition. i will adopt that assumption throughout. studies and experience show our mental models to be wildly inconsistent, both internally (‘verification’), measured against reality (‘validation’) and compared to other people’s (‘coordination’), but they form the basis of pretty much every decision we make.

my best working def of a model is ‘something that represents a partial world state’

• ‘something’ = has to exist in some form to be useful, whether encoded in a tangible object, a pencil & paper sketch, computer memory, neural circuitry, etc.

• ‘represents’ = ultimately in the eye of the beholder; requires some pre-shared bootstrapping model/implementation to be useful (e.g. among humans we have near-universal experiential primitives like ‘dark/light’, ‘hot/cold,’ etc)

• ‘world’ = all of reality

• ‘partial world’ = some subset of reality

• ‘state’ = some configuration of that subset of reality (with implicit or explicit precision/likelihood)

representation is kind of subtle even beyond coordination (alan kay’s ‘communicating with aliens’)... perhaps the most basic representation is a simple ‘reference’, which still encodes the assumption that there’s a ‘something’ that’s persistent and recognizable on the other end (‘object permanence’). i don’t see a flaw in saying ‘pointers’ are the most basic form of stateful cognition (and subject to the same foibles as c pointers... is the referent still there? can it still do the same things? does it still have the same properties? has it been replaced by an evil twin?)

models can serve a bunch of different roles. e.g. a model can communicate an observation of what i claim the current world state to be, an instruction representing the world state i want a system to produce, or an imagined scenario to reason about.

‘simulation’ is a bit slippery; to me the useful primitive to start with is ‘an ordered sequence of models,’ in which case simulation is something like ‘an ordered sequence of models representing the time evolution of a particular model according to some update rule’

one could think of science as ‘a process for finding models that best represent the world and finding rules for updating them that predict future world states’, design as ‘a process for defining models of how we want the world to be,’ and engineering as ‘a process for implementing rules (science) in order to achieve desired world states (design) based on current world states (science).’ ‘programming’ tends to muddle all 3 together, whether explicitly or (usually) implicitly.

all that said, yeah, Kartik Agaram programming email filters is squarely in the realm of what i’m talking about. you start with a model of reality that also includes your computing environment - your machine, its OS, your browser, the mail server, etc etc, which you can always drill down from whatever abstraction your dealing with if needed. you define a model for what unfiltered email is like (‘science’), a model of what you want your filtered email to be like (‘design’), and come up with (science) & implement (engineering) rules you think will achieve that. simulation is a powerful tool to aid in the ‘coming up with and implementing rules’ part (’what happens if i project this rule on this inbox model over time?’). to close the loop you also want some nice tools to see if it’s working how you want it to. netlogo enables some of this in a very ‘science-y’ not ‘user-y’ context. hypercard gives you some nice tools for very ad hoc experimentation.

wavelength check?

written before I saw the above

Absolutely! For me personally, "the essence of ‘coding’ is modeling & simulation" is exactly where I've come from in everything I've done in this space.

I wouldn't just cross out "e.g. data and functions" as a result though - you can't exactly throw those out! Even when in the most modelly and simulatey world, you'll need to present data to the user to hold current states. And behaviours of those states is basically going to boil down to something like functions, even if presented more abstractly in pretty graphics. I mean, even Excel - the financial modeller/simulator - has those!

For me, programming is creating new realities or simulating existing ones. I often refer back to the early Macs which introduced to the world a wordprocessor program that made the page actually look like the printed page you'd end up with, instead of glowing text floating on a black background that bore no relation to it. This is modelling or simulation of printed paper.

In social media or chat you're modelling or simulating the relationships between people: their social graph. You're simulating them talking (or perhaps passing little paper notes to each other!)

Of course, 3D virtual worlds and Augmented Reality are the extreme of this position, as is the programming of IoT devices.

i’m tracking. to try out my terminology (i know you wrote this before reading), i’m def not throwing out data and functions but kind of putting them in their place. ‘data’ is the encoding of models in some reconstructable form. ‘functions’ are rules for transforming models (very useful in simulation or representation). representation is a separate issue.. can be whatever makes the most sense in context: text, diagrams, interactive widgets, spatial audio. a missing concept here is ‘linking models together.’

all good examples of modeling and simulation, though i wouldn’t say 3D VR is necessarily the extreme.. e.g. you can have rich representation capabilities but very poor modeling & simulation capabilities. this is partly why a lot of MMOs despite flashy graphics struggled to achieve the immersive quality of text-based MUDs.

IMO it’s getting easier & easier to hop around these these layers while programming and it can be hard to keep track of where the lines are drawn, to the detriment of comprehension.

On the new post, I agree with everything up to the email filter bit, which I'm still digesting but it's not resonating as yet!

this will probably sound overly philosophical but i’m not trying to be.. just what seems to happen when i try to coherently define terms.

first off, science & engineering is almost always based on the assumption that we share a common ‘reality,’ which we come to understand through our band-limited, unreliable faculties of sensing and cognition. i will adopt that assumption throughout. studies and experience show our mental models to be wildly inconsistent, both internally (‘verification’), measured against reality (‘validation’) and compared to other people’s (‘coordination’), but they form the basis of pretty much every decision we make.

my best working def of a model is ‘something that represents a partial world state’

• ‘something’ = has to exist in some form to be useful, whether encoded in a tangible object, a pencil & paper sketch, computer memory, neural circuitry, etc.

• ‘represents’ = ultimately in the eye of the beholder; requires some pre-shared bootstrapping model/implementation to be useful (e.g. among humans we have near-universal experiential primitives like ‘dark/light’, ‘hot/cold,’ etc)

• ‘world’ = all of reality

• ‘partial world’ = some subset of reality

• ‘state’ = some configuration of that subset of reality (with implicit or explicit precision/likelihood)

representation is kind of subtle even beyond coordination (alan kay’s ‘communicating with aliens’)... perhaps the most basic representation is a simple ‘reference’, which still encodes the assumption that there’s a ‘something’ that’s persistent and recognizable on the other end (‘object permanence’). i don’t see a flaw in saying ‘pointers’ are the most basic form of stateful cognition (and subject to the same foibles as c pointers... is the referent still there? can it still do the same things? does it still have the same properties? has it been replaced by an evil twin?)

models can serve a bunch of different roles. e.g. a model can communicate an observation of what i claim the current world state to be, an instruction representing the world state i want a system to produce, or an imagined scenario to reason about.

‘simulation’ is a bit slippery; to me the useful primitive to start with is ‘an ordered sequence of models,’ in which case simulation is something like ‘an ordered sequence of models representing the time evolution of a particular model according to some update rule’

one could think of science as ‘a process for finding models that best represent the world and finding rules for updating them that predict future world states’, design as ‘a process for defining models of how we want the world to be,’ and engineering as ‘a process for implementing rules (science) in order to achieve desired world states (design) based on current world states (science).’ ‘programming’ tends to muddle all 3 together, whether explicitly or (usually) implicitly.

all that said, yeah, Kartik Agaram programming email filters is squarely in the realm of what i’m talking about. you start with a model of reality that also includes your computing environment - your machine, its OS, your browser, the mail server, etc etc, which you can always drill down from whatever abstraction your dealing with if needed. you define a model for what unfiltered email is like (‘science’), a model of what you want your filtered email to be like (‘design’), and come up with (science) & implement (engineering) rules you think will achieve that. simulation is a powerful tool to aid in the ‘coming up with and implementing rules’ part (’what happens if i project this rule on this inbox model over time?’). to close the loop you also want some nice tools to see if it’s working how you want it to. netlogo enables some of this in a very ‘science-y’ not ‘user-y’ context. hypercard gives you some nice tools for very ad hoc experimentation.

wavelength check?

index.html — not to be facetious, and I see you write about it in the article. Of all filesystem woes, data stored in a directory proper is not one that comes to mind.

One thing that does come to mind is treating a directory as thought it were a file. I mean macOS packages. https://en.wikipedia.org/wiki/Package_(macOS)

I didn't know about macOS packages, thanks for the hint!

HTML itself is another thing that has this "data at every level" structure, in the form of attributes. It's everywhere.

FWIW I think the more interesting problem with filesystem trees is that they're rigidly tree shaped, when tags or 2d tables might sometimes be more useful. :)

Andrew F yes, file systems being limited to tree structures is an issue. Often, something more general (e.g. a graph) would make more sense. That's something for another blog post some day 😉

If only FSs were honest to goodness trees. Hard links make for big headaches.