334 lines
19 KiB
Org Mode
334 lines
19 KiB
Org Mode
---
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title: "Modularity & Abstraction"
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author: Chris Hodapp
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date: "2020-07-16"
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tags:
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- technobabble
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- rambling
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---
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# Why don't I turn this into a paper for arXiv too? It can still be
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# posted to the blog (just also make it exportable to LaTeX perhaps)
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/(This is a sort of rambling post that I started in 2017 April.)/
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*Modularity* and *abstraction* feature prominently wherever computers
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are involved. This is meant very broadly: it applies to designing
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software, using software, integrating software, and to a lot of
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hardware as well. It applies elsewhere, and almost certainly
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originated elsewhere first, however, it appears especially crucial
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around software.
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Definitions, though, are a bit vague (including anything in this
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post). My goal in this post isn't to try to (re)define them, but to
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explain their essence and expand on a few theses:
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- Modularity arises naturally in a wide array of places.
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- Modularity and abstraction are intrinsically connected.
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- Both are for the benefit of people. This usually doesn't need
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stated, but to echo Paul Graham and probably others: to the
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computer, it is all the same.
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- More specifically, both are there to manage *complexity* by
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assigning meaningful information and boundaries which allow people
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to match a problem to what they can actually think about.
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# - Whether a given modularization makes sense depends strongly on
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# meaning and relevance of *information* inside and outside of
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# modules, and broad context matters to those.
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* What Are They?
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People generally agree that "modularity" is good. The idea that
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something complex can be designed and understood in terms of smaller,
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simpler pieces comes naturally to anyone that has built something out
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of smaller pieces or taken something apart. (This isn't to say that
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reductionism is the best way to understand everything, but that's
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another matter.) It runs very deep in the Unix philosophy, which ESR
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gives a good overview of in [[http://www.catb.org/~esr/writings/taoup/html/ch01s06.html][The Art of Unix Programming]] - or, listen
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to it from [[https://youtu.be/tc4ROCJYbm0?t%3D248][Kernighan himself]] at Bell Labs in 1982.
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Tim Berners-Lee gives some practical limitations in [[https://www.w3.org/DesignIssues/Principles.html][Principles of
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Design]] and in [[https://www.w3.org/DesignIssues/Modularity.html][Modularity]]: "Modular design hinges on the simplicity and
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abstract nature of the interface definition between the modules. A
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design in which the insides of each module need to know all about each
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other is not a modular design but an arbitrary partitioning of the
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bits... It is not only necessary to make sure your own system is
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designed to be made of modular parts. It is also necessary to realize
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that your own system, no matter how big and wonderful it seems now,
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should always be designed to be a part of another larger system." Les
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Hatton in [[http://www.leshatton.org/TAIC2008-29-08-2008.html][The role of empiricism in improving the reliability of
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future software]] even did an interesting derivation tying the defect
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density in software to how it is broken into pieces. The 1972 paper
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[[https://www.cs.virginia.edu/~eos/cs651/papers/parnas72.pdf][On the Criteria to be Used in Decomposing System into Modules]] cites a
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1970 textbook on why modularity is important in systems programming,
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but also notes that nothing is said on how to divide a systems into
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modules.
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"Abstraction" doesn't have quite the same consensus. In software, it's
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generally understood that decoupled or loosely-coupled is better than
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tightly-coupled, but at the same time, "abstraction" can have the
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connotation of something that gets in the way, adds overhead, and
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confuses things. Dijkstra, in one of few instances of not being
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snarky, allegedly said, "Being abstract is something profoundly
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different from being vague. The purpose of abstraction is not to be
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vague, but to create a new semantic level in which one can be
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absolutely precise." Joel Spolsky, in one of few instances of me
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actually caring what he said, also has a blog post from 2002 on the
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[[https://www.joelonsoftware.com/2002/11/11/the-law-of-leaky-abstractions/][Law of Leaky Abstractions]] ("All non-trivial abstractions, to some
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degree, are leaky.") The [[https://en.wikipedia.org/wiki/Principle_of_least_privilege][principle of least privilege]] is likewise a
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thing. So, abstraction too has its practical and theoretical
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limitations.
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* How They Relate
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I bring these up together because: *abstractions* are the boundaries
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between *modules*, and the communication channels (APIs, languages,
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interfaces, protocols) through which they talk. It need not
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necessarily be a standardized interface or a well-documented boundary,
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though that helps.
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Available abstractions vary. They vary by, for instance:
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- ...what language you choose. Consider, for instance, that a language
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like Haskell contains various abstractions done largely within the
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type system that cannot be expressed in many other languages.
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Languages like Python, Ruby, or JavaScript might have various
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abstractions meaningful only in the context of dynamic typing. Some
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languages more readily permit the creation of new abstractions, and
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this might lead to a broader range of abstractions implemented in
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libraries.
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- ...the operating system and its standard library. What is a
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process? What is a thread? What is a dynamic library? What is a
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filesystem? What is a file? What is a block device? What is a
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socket? What is a virtual machine? What is a bus? What is a
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commandline?
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- ...all other kinds of libraries a language might use, and entire
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frameworks that cross language boundaries. Consider something like
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Apache Spark, which deals in abstractions that may be accessed from
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various languages.
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- ...the time period. How many of the abstractions named above were
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around or viable in 1970, 1980, 1990, 2000? In the opposite
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direction, when did you last use that lovely standardized protocol,
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[[https://en.wikipedia.org/wiki/Common_Gateway_Interface][CGI]], to let your web application and your web server communicate,
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use [[https://en.wikipedia.org/wiki/PHIGS][PHIGS]] to render graphics, or access a large multiuser system
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via hard-wired terminals?
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As such: Possible ways to modularize things vary. It may make no
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sense that certain ways of modularization even can or should exist
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until it's been done other ways dozens or hundreds or maybe thousands
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of times.
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Other terms are related too. "Loosely-coupled" (or loose coupling)
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and "tightly-coupled" refer to the sort of abstractions sitting
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between modules, or whether or not there even are separate modules.
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"Decoupling" involves changing the relationship between modules
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(sometimes, creating them in the first place), typically splitting
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things into two more sensible pieces that a more sensible abstraction
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separates. "Factoring out" is really a form of decoupling in which
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smaller parts of something are turned into a module which the original
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thing then interfaces with (one canonical example is taking some bits
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of code, often that are very similar or identical in many places, and
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moving them into a single function). To say one has "abstracted over"
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some details implies that a module is handling those details, that the
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details shouldn't matter, and what does matter is the abstraction one
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is using.
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One of Rich Hickey's favorite topics is *composition*, and with good
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reason (and you should check out [[http://www.infoq.com/presentations/Simple-Made-Easy/][Simple Made Easy]] regardless). This
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relates as well: to *compose* things together effectively into bigger
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parts requires that they support some common abstraction.
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In the same area, [[https://clojurefun.wordpress.com/2012/08/17/composition-over-convention/][Composition over convention]] is a good read on how
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/frameworks/ run counter to modularity: they aren't built to behave
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like modules of a larger system.
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The contrasting terms *interface* and *implementation* are commonly
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seen in software, with "implementation" loosely referring to what is
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inside a module, and "interface" referring to its "outside" boundaries
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and thus to the abstractions it supports. You'll commonly hear advice
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about separating interface from implementation, and some semi-related
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things:
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- [[https://en.wikipedia.org/wiki/SOLID][SOLID]]
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- [[https://en.wikipedia.org/wiki/Cross-cutting_concern][Cross-cutting concerns]] and [[https://en.wikipedia.org/wiki/Aspect-oriented_programming][Aspect-oriented programming]]
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- [[https://en.wikipedia.org/wiki/Separation_of_concerns][Separation of Concerns]]
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- [[https://en.wikipedia.org/wiki/Information_hiding][Information hiding]] and [[https://en.wikipedia.org/wiki/Encapsulation_(computer_programming)][encapsulation]]
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* Why?
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It has a very pragmatic reason behind it: When something is a module
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unto itself, presumably it is relying on specific abstractions, and it
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is possible to freely change this module's internal details (provided
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that it still respects the same abstractions), to move this module to
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other contexts (anywhere that provides the same abstractions), and to
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replace it with other modules (anything that respects the same
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abstractions).
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It also has a more abstract reason: When something is a module unto
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itself, the way it is designed and implemented usually presents more
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insight into the fundamentals of the problem it is solving. It
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contains fewer incidental details, and more essential details.
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That's all very practical for people. It reduces the amount of
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information that they must handle, and it permits them to *reason*
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about the behavior of systems that are unknown or even completely
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hypothetical.
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It can also be seen as serving as a *contract* which reduces the
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amount of communication and often the amount of disagreement. I think
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this is a useful definition too: it conveys the notion that there are
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multiple parties involved, that they have already agreed on some
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specific obligations, and that they are free to behave as needed
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provided that they fulfill those obligations.
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[[https://en.wikipedia.org/wiki/Separation_of_concerns][Separation of Concerns]] gets at this same idea and expresses it in
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terms of "concerns" rather than contracts.
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I referred earlier to the abstractions themselves as both boundaries
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and communications channels, and invoking "communications" raises the
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related question of what *information* is being communicated. (For
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whatever reason, Wikipedia defines a [[https://en.wikipedia.org/wiki/Concern_(computer_science)][concern]] in terms
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of... information).
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Some definitions refer directly to information, like the
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[[https://en.wikipedia.org/wiki/Abstraction_principle_(computer_programming)][abstraction principle]] which aims to reduce duplication of information
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which fits with [[https://en.wikipedia.org/wiki/Don%2527t_repeat_yourself][don't repeat yourself]] so that "a modification of any
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single element of a system does not require a change in other
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logically unrelated elements". [[https://en.wikipedia.org/wiki/Encapsulation_(computer_programming)][Encapsulation]] likewise refers to it
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via [[https://en.wikipedia.org/wiki/Information_hiding][information hiding]]. Alan Perlis in his [[http://www.cs.yale.edu/homes/perlis-alan/quotes.html][epigrams]] had #20:
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"Wherever there is modularity there is the potential for
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misunderstanding: Hiding information implies a need to check
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communication."
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* Examples
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Network stacks, in particular via the OSI 7-layer model, are a good
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example of all of this. Higher-level protocols can work in a way that
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disregards lower-level details (most of the time - matters of
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bandwidth and latency do sometimes matter). Lower-level protocols can
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advance and be replaced without much concern for their higher-level
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use.
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Even the early innovation of packet-switching is a great instance of
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abstracting network and routing details away from communications
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Disk caches, and memory caches, and most other kinds of caches, work
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because they still implement the same underlying abstraction (albeit
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with some minor leakage).
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Even DOS had useful abstractions. Things like
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[[https://en.wikipedia.org/wiki/DriveSpace][DriveSpace/DoubleSpace]]/Stacker worked well enough because most
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software that needed files relied on DOS's normal abstractions to
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access them - so it did not matter to them that the underlying
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filesystem was actually compressed, or was actually a RAM disk, or was
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on some obscure SCSI interface. Likewise, for the silliness known as
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[[https://en.wikipedia.org/wiki/Expanded_memory][EMS]], applications that accessed memory through the EMS abstraction
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could disregard whether it was a "real" EMS board providing access to
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that memory, whether it was an expanded memory manager providing
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indirect access to some other memory or even to a hard disk pretending
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to be memory.
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** Less-Conventional Examples
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One thing I've watched with some interest is when new abstractions
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emerge (or, perhaps, old ones become more widespread) to solve
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problems that I wasn't even aware existed.
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[[https://circleci.com/blog/it-really-is-the-future/][It really is the future]] talks about a lot of more recent forms of
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modularity from the land of devops, most of which were completely
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unheard-of in, say, 2010. [[https://www.functionalgeekery.com/episode-75-eric-b-merritt/][Functional Geekery episode 75]] talks about
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many similar things.
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[[https://jupyter.org/][Jupyter Notebook]] is one of my favorites here. It provides a notebook
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interface (similar to something like Maple or Mathematica) which:
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- allows the notebook to use various different programming languages
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underneath,
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- decouples where the notebook is used and where it is running, due to
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being implemented as a web application accessed through the browser,
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- decouples the presentation of a stored notebook from Jupyter itself
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by using a [[https://nbformat.readthedocs.io/en/latest/][JSON-based file format]] which can be rendered without
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Jupyter (like GitHub does if you commit a .ipynb file).
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I love notebook interfaces already because they simplify experimenting
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by handling a lot of things I'd otherwise have to do manually - like
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saving results and keeping them lined up with the exact code that
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produced them. Jupyter adds some other use-cases I find marvelous -
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for instance, I can let the interpreter run on my workstation which
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has all of the computing power, but I can access it across the
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Internet from my laptop.
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[[https://zeppelin.apache.org/][Apache Zeppelin]] does similar things with different languages; I've
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just used it much less.
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Another favorite of mine is [[https://nixos.org/nix/][Nix]] (likewise its cousin [[https://guix.gnu.org/][Guix]]).
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One excellent article,
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[[http://blog.ezyang.com/2014/08/the-fundamental-problem-of-programming-language-package-management/][The fundamental problem of programming language package management]],
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doesn't ever mention Nix but explains very well the problems it sets
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out to solve. To be able to combine nearly all of the
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programming-language specific package managers into a single module is
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a very lofty goal, but Nix appears to do a decent job of it (among
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other things).
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The [[https://www.lua.org/][Lua]] programming language is noteworthy here. It's written in
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clean C with minimal dependencies, so it runs nearly anywhere that a C
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or C++ compiler targets. It's purposely very easy both to *embed*
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(i.e. to put inside of a program and use as an extension language,
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such as for plugins or scripting) and to *extend* (i.e. to connect
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with libraries to allow their functionality to be used from Lua). [[https://www.gnu.org/software/guile/][GNU
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Guile]] has many of the same properties, I'm told.
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We ordinarily think of object systems as something living in the
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programming language. However, the object system is sometimes made a
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module that is outside of the programming language, and languages just
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interact with it. [[https://en.wikipedia.org/wiki/GObject][GObject]], [[https://en.wikipedia.org/wiki/Component_Object_Model][COM]], and [[https://en.wikipedia.org/wiki/XPCOM][XPCOM]] do this, and to some
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extent, so does [[https://en.wikipedia.org/wiki/Meta-object_System][Qt & MOC]] - and there are probably hundreds of others,
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particularly if you allow dead ones created during the object-oriented
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hype of the '90s. This seems to happen in systems where the object
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hierarchy is in effect "bigger" than the language.
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[[https://zeromq.org/][ZeroMQ]] is another example: a set of cross-language abstractions for
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communication patterns in a distributed system. I know it's likely
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not unique, but it is one of the better-known and the first I thought
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of, and I think their [[http://zguide.zeromq.org/page:all][guide]] is excellent.
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Interestingly, the same iMatix behind ZeroMQ also created [[https://github.com/imatix/gsl][GSL]] and
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explained its value in [[https://imatix-legacy.github.io/mop/introduction.html][Model-Oriented Programming]], for which
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abstraction features heavily. I've not used GSL, and am skeptical of
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its stated usefulness, but it looks like it is meant to help create
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compile-time abstractions that likewise sit outside of any particular
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programming language.
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# TODO: Expand on this.
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[[https://web.hypothes.is/][hypothes.is]] is a curious one that I find fascinating. They're trying
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to factor out annotation and commenting from something that is handled
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on a per-webpage basis and turn it into its own module, and I really
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like what I've seen. However, it does not seem to have caught on
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much.
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The Unix tradition lives on in certain modern tools. [[https://stedolan.github.io/jq/][jq]] has proven
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very useful anytime I've had to mess with JSON data. [[http://www.dest-unreach.org/socat/][socat]] and [[http://netcat.sourceforge.net/][netcat]]
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have saved me numerous times. I'm sure certain people love the fact
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that [[https://neovim.io/][Neovim]] is designed to be seamlessly embedded and to extend with
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plugins. [[https://suckless.org/philosophy][suckless]] perhaps takes it too far, but gets an honorary
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mention...
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People know that I love Emacs, but I also do believe many of the
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complaints on how large it is. Despite that it is basically its own
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operating system, /within this/ it has considerable modularity. The
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same applies somewhat to Blender, I suppose.
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Consider [[https://research.google.com/pubs/pub43146.html][Machine Learning: The High Interest Credit Card of Technical Debt]],
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a paper that anyone working around machine learning should read and
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re-read regularly. Large parts of the paper are about ways in which
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machine learning conflicts with proper modularity and abstraction.
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(However, [[https://colah.github.io/posts/2015-09-NN-Types-FP/][Neural Networks, Types, and Functional Programming]] is still
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a good post and shows some sorts of abstraction that still exist
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at least in neural networks.)
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Even more abstractly: emulators work because so much software
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respected the abstraction of some specific CPU and hardware platform.
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Submitted without further comment:
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https://github.com/stevemao/left-pad/issues/4
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