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Creating and evolving a programming language: funding
The funding for artists and designers/implementors of programming languages shares some similarities.
Rich patrons used to sponsor a few talented painters/sculptors/etc, although many artists had no sponsors and worked for little or no money. Designers of programming languages sometimes have a rich patron, in the form of a company looking to gain some commercial advantage, with most language designers have a day job and work on their side project that might have a connection to their job (e.g., researchers).
Why would a rich patron sponsor the creation of an art work/language?
Possible reasons include: Enhancing the patron’s reputation within the culture in which they move (attracting followers, social or commercial), and influencing people’s thinking (to have views that are more in line with those of the patron).
The during 2009-2012 it suddenly became fashionable for major tech companies to have their own home-grown corporate language: Go, Rust, Dart and Typescript are some of the languages that achieved a notable level of brand recognition. Microsoft, with its long-standing focus on developers, was ahead of the game, with the introduction of F# in 2005 (and other languages in earlier and later years). The introduction of Swift and Hack in 2014 were driven by solid commercial motives (i.e., control of developers and reduced maintenance costs respectively); Google’s adoption of Kotlin, introduced by a minor patron in 2011, was driven by their losing of the Oracle Java lawsuit.
Less rich patrons also sponsor languages, with the idiosyncratic Ivor Tiefenbrun even sponsoring the creation of a bespoke cpu to speed up the execution of programs written in the company language.
The benefits of having a rich sponsor is the opportunity it provides to continue working on what has been created, evolving it into something new.
Self sponsored individuals and groups also create new languages, with recent more well known examples including Clojure and Julia.
What opportunities are available for initially self sponsored individuals to support themselves, while they continue to work on what has been created?
The growth of the middle class, and its interest in art, provided a means for artists to fund their work by attracting smaller sums from a wider audience.
In the last 10-15 years, some language creators have fostered a community driven approach to evolving and promoting their work. As well as being directly involved in working on the language and its infrastructure, members of a community may also contribute or help raise funds. There has been a tiny trickle of developers leaving their day job to work full time on ‘their’ language.
The term Hedonism driven development is a good description of this kind of community development.
People have been creating new languages since computers were invented, and I don’t expect this desire to create new languages to stop anytime soon. How long might a language community be expected to last?
Having lots of commercially important code implemented in a language creates an incentive for that language’s continual existence, e.g., companies paying for support. When little or co commercial important code is available to create an external incentive, a language community will continue to be active for as long as its members invest in it. The plot below shows the lifetime of 32 secular and 19 religious 19th century American utopian communities, based on their size at foundation; lines are fitted loess regression (code+data):
How many self-sustaining language communities are there, and how many might the world’s population support?
My tracking of new language communities is a side effect of the blogs I follow and the few community sites a visit regularly; so a tiny subset of the possibilities. I know of a handful of ‘new’ language communities; with ‘new’ as in not having a Wikipedia page (yet).
One list contains, up until 2005, 7,446 languages. I would not be surprised if this was off by almost an order of magnitude. Wikipedia has a very idiosyncratic and brief timeline of programming languages, and a very incomplete list of programming languages.
I await a future social science PhD thesis for a more thorough analysis of current numbers.
Learning R as a language
Books written to teach a general purpose programming language are usually organized according to the features of the language and examples often show how a particular language feature is interpreted by a compiler. Books about domain specific languages are usually organized in a way that makes sense in the corresponding application domain and examples usually illustrate how a particular domain problem can be solved using the language.
I have spent a lot of time using R over the last year and by dint of reading lots of R code and various introductions to the language I have managed to piece together a model of the language. I rarely have any trouble learning a general purpose language from its reference manual, but users of domain specific languages are rarely interested in language details and so these reference manuals are usually only intended to be read by people who know the language well (another learning problem is that domain specific languages often contain quirky features rarely seen in other languages; in the case of R I was not lucky enough to know enough other languages to cover all its quirky features).
I managed to one introduction to R written from the perspective of the programming language (and not the application domain): the original The Art of R Programming by Norman Matloff has been expanded and is now available as a book.
Summary. If you know another language and want to quickly learn about the languages features of R I recommend this book. I have not taught raw beginners for over 30 years and have no idea if this book would be of any use to them.
This book does not attempt to teach you to think ‘R’, it is not about the art of R programming. The value of this book is as a single source for a broad coverage of lots of language features explained using lots of examples. Yes, more time could have been spent on the organization and fixing inconsistencies in the layout; these are not show stoppers.
Some people might tell you to buy “Software for Data Analysis” by John Chambers. Don’t; if you are a fan of Finnegans Wake and are nostalgic for the mainframe world of the 1970s you might like to give it a go. (I think Bertrand Meyer’s “Object-oriented Software Construction” is still the best book about the design of a language).
Meanderings. What books are good examples of “The Art of …” writing for domain specific languages? Two that spring to mind are: “Algorithms in Snobol 4” by James Gimpel (still spotted from time to time on second hand book sites) and more recently “SQL For Smarties: Advanced SQL Programming” by Joe Celko.
Yes, I know that R is not really a domain specific language but a language that is primarily used in one domain. Frink is an example of a language containing a major behavior feature that is specific to its intended application domain. I cannot think of any major language feature of R that is specific to statistics.
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