\section{Introduction}\label{introduction}

Programming languages and environments for music have developed hand in
hand with the history of creating music using computers. Software and
systems like Max, Pure Data, CSound, and SuperCollider has been referred
to as ``Computer Music
Language''\citep{McCartney2002, Nishino2016, McPherson2020}, ``Language
for Computer Music''\citep{Dannenberg2018}, and ``Computer Music
Programming Systems''\citep{Lazzarini2013}, though there is no clear
consensus on the use of these terms. However, as the shared term
``Computer Music'' implies, these programming languages are deeply
intertwined with the history of technology-driven music, which developed
under the premise that ``almost any sound can be
produced''\citep{mathews_acoustic_1961} through the use of computers.

In the early days, when computers were confined to research laboratories
and neither displays nor mouse existed, creating sound or music with
computers was inevitably equal to the work of programming. Today,
however, programming as a means to produce sound on a computer---rather
than employing Digital Audio Workstation (DAW) software like Pro Tools
is not usual. In other words, programming languages for music developed
after the proliferation of personal computers are the softwares that
intentionally chose programming (whether textual or graphical) as their
frontend for making sound.

Since the 1990s, the theoretical development of programming languages
and the various constraints required for real-time audio processing have
significantly increased the specialized knowledge necessary for
developing programming languages for music today. Furthermore, some
languages developed after the 2000s are not necessarily aimed at
pursuing new forms of musical expression. It seems that there is still
no unified perspective on how the value of such languages should be
evaluated.

In this paper, a critical historical review is conducted by deriving
discussions from sound studies alongside existing surveys, aiming to
consider programming languages for music independently from computer
music as the specific genre. \#\#\# Use of the Term ``Computer Music''

The term ``Computer Music,'' despite its literal and potential broad
meaning, has been noted as being used within a narrowly defined
framework tied to specific styles or communities, as represented in
Ostartag's \emph{Why Computer Music Sucks}\citep{ostertag1998} since the
1990s.

As Lyon observed nearly two decades ago, it is now nearly impossible to
imagine a situation in which computers are not involved at any stage
from production to experience of music\citep[p1]{lyon_we_2006}. The
necessity of using the term ``Computer Music'' to describe academic
contexts, particularly those centered around the ICMC, has consequently
diminished.

Holbrook and Rudi continued Lyon's discussion by proposing the use of
frameworks like Post-Acousmatic\citep{adkins2016} to redefine ``Computer
Music.'' Their approach incorporates the tradition of pre-computer
experimental/electronic music, situating it as part of the broader
continuum of technology-based or technology-driven
music\citep{holbrook2022}.

While the strict definition of the Post-Acousmatic music is not given
deliberately, one of its elements contains the expansion of music
production from institutional settings to individuals and the use of the
technology were diversified\citep[p113]{adkins2016}. However, while the
Post-Acousmatic discourse integrates the historical fact that declining
computer costs and access beyond laboratories have enabled diverse
musical expressions, it simultaneously marginalizes much of the music
that is ``just using computers'' and fails to provide insights into this
divided landscape.

Lyon argues that defining computer music simply as music created with
computers is too permissive, while defining it as music that could not
exist without computers is too strict. He highlights the difficulty of
considering instruments that use digital simulations, such as virtual
analog synthesizers, within these definitions. Furthermore, he suggests
that the term ``computer music'' is style-agnostic definition almost
like ``piano music,'' implying that it ignores the style and form inside
music produced by the instruments.

However, one of the defining characteristics of computers as a medium
lies in their ability to treat musical styles themselves as subjects of
meta-manipulation through simulation and modeling. When creating
instruments with computers, or when using such instruments, sound
production involves programming---manipulating symbols embedded in a
particular musical culture. This recursive embedding of the language and
perception constituting that musical culture into the resulting music is
a process that goes beyond what is possible with acoustic instruments or
analog electronic instruments. Magnusson refers to this characteristic
of digital instruments as ``Epistemic Tools'' and points out that they
tend to work in the direction of reinforcing and solidifying musical
culture:

\begin{quote}
The act of formalising is therefore always an act of fossilisation. As
opposed to the acoustic instrument maker, the designer of the composed
digital instrument frames affordances through symbolic design, thereby
creating a snapshot of musical theory, freezing musical culture in time.
\citep[p173]{Magnusson2009}
\end{quote}

Today, many people use computers for music production not because they
consciously leverage the uniqueness of the meta-medium, but simply
because there are no quicker or more convenient alternatives available.
Even so, within a musical culture where computers are used as a default
or reluctant choice, musicians are inevitably influenced by the
underlying infrastructures like software, protocols, and formats. As
long as the history of programming languages for music remains
intertwined with the history of computer music as it relates to specific
genres or communities, it becomes difficult to analyze music created
with computers as a passive means.

In this paper, the history of programming languages for music is
reexamined with an approach that, opposite from Lyon, takes an extremely
style-agnostic perspective. Rather than focusing on what has been
created with these tools, the emphasis is placed on how these tools
themselves have been constructed. The paper centers on the following two
topics:

\begin{enumerate}
\def\labelenumi{\arabic{enumi}.}
\tightlist
\item
  A critique of the universality of sound representation using
  pulse-code modulation (PCM), the foundational concept underlying most
  of today's sound programming, by referencing early attempts of sound
  generation using electronic computers.
\item
  An examination of the MUSIC-N family, the origin of PCM-based sound
  synthesis, to highlight that its design varies significantly across
  systems from the perspective of modern programming language design and
  that it has evolved over time into a black box, eliminating the need
  for users to understand its internal workings.
\end{enumerate}

Ultimately, the paper concludes that programming languages for music
developed since the 2000s are not solely aimed at creating new music but
also serve as alternatives to the often-invisible technological
infrastructures surrounding music, such as formats and protocols. By
doing so, the paper proposes new perspectives for the historical study
of music created with computers. \#\# PCM and Early Computer Music

Among the earliest examples of computer music research, the MUSIC I
system (1957) from Bell Labs and its derivatives, known as MUSIC-N, are
frequently highlighted. However, attempts to create music with computers
in the UK and Australia prior to MUSIC I have also been
documented\citep{doornbusch2017}. Organizing what was achieved by
MUSIC-N and earlier efforts can help clarify definitions of computer
music.

The earliest experiments with sound generation on computers in the 1950s
involved controlling the intervals between one-bit pulses (on or off) to
control pitch. This was partly because the operational clock frequencies
of early computers fell within the audible range, making the
sonification of electrical signals a practical and cost-effective
debugging method compared to visualizing them on displays or
oscilloscopes. Some computers at this time like Australia's CSIR Mark I
(CSIRAC) often had ``hoot'' primitive instructions that emit a single
pulse to a speaker.

In 1949, the background to music played on the BINAC in UK involved
engineer Louis Wilson, who noticed that an AM radio placed nearby could
pick up weak electromagnetic waves generated during the switching of
vacuum tubes, producing regular sounds. He leveraged this phenomenon by
connecting a speaker and a power amplifier to the computer's output,
using the setup to assist in debugging processes. Frances Elizabeth
Holberton took this a step further by programming the computer to
generate pulses at arbitrary intervals, creating melodies
\citep{woltman1990}. The sound generation on BINAC and CSIR Mark I
represents early instances of using computers to play melodies from
existing music.

However, not all sound generation at this timewas merely the
reproduction of existing music. Doornbusch highlights experiments on the
British Pilot ACE (Prototype for Automatic Computing Engine: ACE), which
utilized acoustic delay line memory to produce unique
sounds\citep[p303-304]{doornbusch2017}. Acoustic delay line memory, used
as main memory in early computers like BINAC and CSIR Mark I, employed
the feedback of pulses traveling through mercury via a speaker and
microphone setup to retain data. Donald Davis, an engineer on the ACE
project, described the sounds it produced as
follows\citep[p19-20]{davis_very_1994}:

\begin{quote}
The Ace Pilot Model and its successor, the Ace proper, were both capable
of composing their own music and playing it on a little speaker built
into the control desk. I say composing because no human had any
intentional part in choosing the notes. The music was very interesting,
though atonal, and began by playing rising arpeggios: these gradually
became more complex and faster, like a developing fugue. They dissolved
into colored noise as the complexity went beyond human understanding.

Loops were always multiples of 32 microseconds long, so notes had
frequencies which were submultiples of 31.25 KHz. The music was based on
a very strange scale, which was nothing like equal tempered or harmonic,
but was quite pleasant.
\end{quote}

This music arose unintentionally during program optimization and was
made possible by ``misusing'' switches installed for debugging acoustic
delay line memory (p20). Media scholar Miyazaki described the practice
of listening to sounds generated by algorithms and their bit patterns,
integrated into programming and debugging, as ``Algo\emph{rhythmic}
Listening''\citep{miyazaki2012}.

Doornbusch warns against ignoring early computer music practices in
Australia and the UK simply because they did not directly influence
subsequent research\citep[p305]{doornbusch2017}. Indeed, the tendency to
treat pre-MUSIC attempts as hobbyist efforts by engineers and post-MUSIC
endeavors as ``serious'' research remains common even
today\citep{tanaka_all_2017}.

The sounds produced by the Pilot ACE challenge the post-acousmatic
historical narrative, which suggests that computer music transitioned
from being confined to specialized laboratories to becoming accessible
to individuals, including amateurs.

This is because the sounds generated by the Pilot ACE were not created
by musical experts, nor were they solely intended for debugging
purposes. Instead, they were programmed with the goal of producing
interesting sounds. Moreover, the sounds were tied to the hardware of
the acoustic delay line memory---a feature that was likely difficult to
replicate, even in modern audio programming environments.

Similarly, in the 1960s at MIT, Peter Samson took advantage of the
debugging speaker on the TX-0, a machine that had become outdated and
freely available for students to use. He conducted experiments where he
played melodies, such as Bach fugues, using square waves
\citep{levy_hackers_2010}. Samson's experiments with the TX-0 later
evolved into the creation of a program that allowed melodies to be
described using text strings within MIT.

Building on this, Samson developed a program called the Harmony Compiler
on the DEC PDP-1, which was derived from the TX-0. This program gained
significant popularity among MIT students. Around 1972, Samson began
surveying various digital synthesizers that were being developed at the
time and went on to create a system specialized for computer music. The
resulting Samson Box was used at Stanford University's CCRMA (Center for
Computer Research in Music and Acoustics) for over a decade until the
early 1990s and became a tool for many composers to create their works
\citep{loy_life_2013}. Considering Samson's example, it is not
appropriate to separate the early experiments in sound generation by
computers from the history of computer music solely because their
initial purpose was debugging. \#\#\# Acousmatic Listening, the premise
of the Universality of PCM

One of the reasons why MUSIC led to subsequent advancements in research
was not simply because it was developed early, but because it was the
first to implement sound representation on a computer based on
\textbf{pulse-code modulation (PCM)}, which theoretically enables the
representation of ``almost any sound.''

PCM, the foundational method of sound representation on today's
computers, involves dividing audio waveforms into discrete intervals
(sampling) and representing the sound pressure at each interval as
discrete numerical values (quantization).

The issue with the universalism of PCM in the history of computer music
is inherent in the concept of Acousmatic, which serves as a premise for
Post-Acousmatic. Acousmatic, introduced by Piegnot as a listening style
for tape music such as musique concrète and later theorized by
Schaeffer, refers to a mode of listening where the listener refrains
from imagining a specific sound source. This concept has been widely
applied in theories of listening to recorded sound, including Chion's
analysis of sound design in film.

However, as sound studies scholar Jonathan Sterne has pointed out,
discourses surrounding acousmatic listening often work to delineate
pre-recording auditory experiences as ``natural'' by
contrast\footnote{Sterne later critiques the phenomenological basis of
  acousmatic listening, which presupposes an idealized, intact body as
  the listening subject. He proposes a methodology of political
  phenomenology centered on impairment, challenging these normative
  assumptions\citep{sterne_diminished_2022}. Discussions of universality
  in computer music should also address ableism, as seen in the
  relationship between recording technologies and auditory disabilities.}.
This implies that prior to the advent of recording technologies,
listening was unmediated and holistic---a narrative that obscures the
constructed nature of these assumptions.

\begin{quote}
For instance, the claim that sound reproduction has ``alienated'' the
voice from the human body implies that the voice and the body existed in
some prior holistic, unalienated, and self present relation.

They assume that, at some time prior to the invention of sound
reproduction technologies, the body was whole, undamaged, and
phenomenologically coherent.\citep[p20-21]{sterne_audible_2003}
\end{quote}

The claim that PCM-based sound synthesis can produce ``almost any
sound'' is underpinned by an ideology associated with recording
technologies. This ideology assumes that recorded sound contains an
``original'' source and that listeners can distinguish distortions or
noise from it. Sampling theory builds on this premise by statistically
modeling human auditory characteristics: it assumes that humans cannot
discern volume differences below certain thresholds or perceive
vibrations outside specific frequency ranges. By limiting representation
to this range, sampling theory ensures that all audible sounds can be
effectively encoded.

By the way, the actual implementation of PCM in MUSIC I only allowed for
monophonic triangle waves with controllable volume, pitch, and timing
(MUSIC II later expanded this to four oscillators)\citep{Mathews1980}.
Would anyone today describe such a system as capable of producing
``infinite variations'' in sound synthesis?

Even when considering more contemporary applications, processes like
ring modulation (RM), amplitude modulation (AM), or distortion often
generate aliasing artifacts unless proper oversampling is applied. These
artifacts occur because PCM, while universally suitable for reproducing
recorded sound, is not inherently versatile as a medium for generating
new sounds. As Puckette has argued, alternative representations, such as
collections of linear segments or physical modeling synthesis, present
other possibilities\citep{puckette2015}. Therefore, PCM is not a
completely universal tool for creating sound.

\section{What Does the Unit Generator
Hide?}\label{what-does-the-unit-generator-hide}

Starting with version III, MUSIC adopted the form of an acoustic
compiler (or block diagram compiler) that takes two types of input: a
score language, which represents a list of time-varying parameters, and
an orchestra language, which describes the connections between
\textbf{Unit Generators} such as oscillators and filters. In this paper,
the term ``Unit Generator'' means a signal processing module used by the
user, where the internal implementation is either not open or
implemented in a language different from the one used by the user.

Beyond performing sound synthesis based on PCM, one of the defining
features of the MUSIC family in the context of computer music research
was the establishment of a division of labor between professional
musicians and computer engineers through the development of
domain-specific languages. Mathews explained that he developed a
compiler for MUSIC III in response to requests for additional features
such as envelopes and vibrato, while also ensuring that the program
would not be fixed in a static form
\citep[13:10-17:50]{mathews_max_2007}. He repeatedly stated that his
role was that of a scientist rather than a musician:

\begin{quote}
The only answer I could see was not to make the instruments myself---not
to impose my taste and ideas about instruments on the musicians---but
rather to make a set of fairly universal building blocks and give the
musician both the task and the freedom to put these together into his or
her instruments. \citep[p16]{Mathews1980}\\
(\ldots) When we first made these music programs the original users were
not composers; they were the psychologist Guttman, John Pierce, and
myself, who are fundamentally scientists. We wanted to have musicians
try the system to see if they could learn the language and express
themselves with it. So we looked for adventurous musicians and composers
who were willing to experiment. (p17)
\end{quote}

This clear delineation of roles between musicians and scientists became
one of the defining characteristics of post-MUSIC computer music
research. Paradoxically, the act of creating sounds never heard before
using computers paved the way for research by allowing musicians to
focus on their craft without needing to grapple with the complexities of
programming.

\subsection{Example: Hiding First-Order Variables in Signal
Processing}\label{example-hiding-first-order-variables-in-signal-processing}

Although the MUSIC N series shares a common workflow of using a Score
language and an Orchestra language, the actual implementation of each
programming language varies significantly, even within the series.

One notable but often overlooked example is MUSIGOL, a derivative of
MUSIC IV \citep{innis_sound_1968}. In MUSIGOL, not only was the system
itself implemented differently, but even the user-written Score and
Orchestra programs were written entirely as ALGOL 60 source code.
Similar to modern frameworks like Processing or Arduino, MUSIGOL
represents one of the earliest examples of a domain-specific language
implemented as an internal DSL within a library\footnote{While MUS10,
  used at Stanford University, was not an internal DSL, it was created
  by modifying an existing ALGOL parser \citep[p248]{loy1985}.}.
(Therefore, according to the definition of Unit Generator provided in
this paper, MUSIGOL does not qualify as a language that uses Unit
Generators.)

The level of abstraction deemed intuitive for musicians varied across
different iterations of the MUSIC N series. This can be illustrated by
examining the description of a second-order band-pass filter. The filter
mixes the current input signal \(S_n\), the output signal from \(t\)
time steps prior \(O_{n-t}\), and an arbitrary amplitude parameter
\(I_1\), as shown in the following equation:

\[O_n = I_1 \cdot S_n + I_2 \cdot O_{n-1} - I_3 \cdot O_{n-2}\]

In MUSIC V, this band-pass filter can be used as in \ref{lst:musicv}
\citep[p78]{mathews_technology_1969}.

\begin{lstlisting}[label={lst:musicv}, caption={Example of the use of RESON UGen in MUSIC V.}]
FLT I1 O I2 I3 Pi Pj;
\end{lstlisting}

Here, \passthrough{\lstinline!I1!} represents the input bus, and
\passthrough{\lstinline!O!} is the output bus. The parameters
\passthrough{\lstinline!I2!} and \passthrough{\lstinline!I3!} correspond
to the normalized values of the coefficients \(I_2\) and \(I_3\),
divided by \(I_1\) (as a result, the overall gain of the filter can be
greater or less than 1). The parameters \passthrough{\lstinline!Pi!} and
\passthrough{\lstinline!Pj!} are normally used to receive parameters
from the Score, specifically among the available
\passthrough{\lstinline!P0!} to \passthrough{\lstinline!P30!}. In this
case, however, these parameters are repurposed as general-purpose memory
to temporarily store feedback signals. Similarly, other Unit Generators,
such as oscillators, reuse note parameters to handle operations like
phase accumulation.

As a result, users needed to manually calculate feedback gains based on
the desired frequency characteristics\footnote{It is said that a
  preprocessing feature called \passthrough{\lstinline!CONVT!} could be
  used to transform frequency characteristics into coefficients
  \citep[p77]{mathews_technology_1969}.}, and they also had to account
for using at least two sample memory spaces.

On the other hand, in MUSIC 11, developed by Barry Vercoe, and its later
iteration, CSound, the band-pass filter is defined as a Unit Generator
(UGen) named \passthrough{\lstinline!reson!}. This UGen accepts four
parameters: the input signal, center cutoff frequency, bandwidth, and Q
factor. Unlike previous implementations, users no longer need to be
aware of the two-sample feedback memory space for the output
\citep[p248]{vercoe_computer_1983}. However, in MUSIC 11 and CSound, it
is still possible to implement this band-pass filter from scratch as a
User Defined Opcode (UDO) as in \ref{lst:reson}. Vercoe emphasized that
while signal processing primitives should allow for low-level
operations, such as single-sample feedback, and eliminate black boxes,
it is equally important to provide high-level modules that avoid
unnecessary complexity (``avoid the clutter'') when users do not need to
understand the internal details \citep[p247]{vercoe_computer_1983}.

\begin{lstlisting}[label={lst:reson}, caption={Example of scratch implementation and built-in operation of RESON UGen respectively, in MUSIC11. Retrieved from the original paper. (Comments are omitted for the space restriction.)}]
      instr  1 
la1   init   0 
la2   init   0 
i3    = exp(-6.28 * p6 / 10000)               
i2    = 4*i3*cos(6.283185 * p5/10000) / (1+i3)
i1    = (1-i3) * sqrt(1-1 - i2*i2/(4*i3))    
a1    rand   p4                               
la3   =      la2                              
la2   =      la1                              
la1   =      i1*a1 + i2 * la2 - i3 * la3      
      out    la1
      endin

      instr 2
a1    rand   p4                      
a1    reson  a1,p5,p6,1
      endin
\end{lstlisting}

On the other hand, in programming environments that inherit the Unit
Generator paradigm, such as Pure Data \citep{puckette_pure_1997}, Max
(whose signal processing functionalities were ported from Pure Data as
MSP), SuperCollider \citep{mccartney_supercollider_1996}, and ChucK
\citep{wangChucKStronglyTimed2015}, primitive UGens are implemented in
general-purpose languages like C or C++. If users wish to define
low-level UGens (External Objects), they need to set up a development
environment for C or C++.

As an extension, ChucK later introduced ChuGen, which is equivalent to
CSound's UDO, allowing users to define low-level UGens within the ChucK
language itself \citep{Salazar2012}. However, both CSound and ChucK face
performance limitations with UDOs during runtime compared to natively
implemented UGens. Consequently, not all existing UGens are replaced by
UDOs, which remain supplemental features rather than primary tools.

When UGens are implemented in low-level languages like C, even if the
implementation is open-source, the division of knowledge effectively
forces users (composers) to treat UGens as black boxes. This reliance on
UGens as black boxes reflects and deepens the division of labor between
musicians and scientists that Mathews helped establish---a structure
that can be seen as both a cause and a result of this paradigm.

For example, Puckette, the developer of Max and Pure Data, noted that
the division of labor at IRCAM between researchers, Musical
Assistants/realizers, and composers has parallels in the current Max
ecosystem, where the roles are divided into software developers,
External Objects developers, and Max users \citep{puckette_47_2020}. As
described in the ethnography of 1980s IRCAM by anthropologist Georgina
Born, the division of labor between fundamental research scientists and
composers at IRCAM was extremely clear. This structure was also tied to
the exclusion of popular music and its associated technologies in
IRCAM's research focus \citep{Born1995}.

However, such divisions are not necessarily the result of differences in
values along the axes analyzed by Born, such as
modernist/postmodernist/populist or low-tech/high-tech
distinctions\footnote{David Wessel revealed that the individual referred
  to as RIG in Born's ethnography was himself and commented that Born
  oversimplified her portrayal of Pierre Boulez, then director of IRCAM,
  as a modernist. \citep{taylor_article_1999}}. This is because the
black-boxing of technology through the division of knowledge occurs in
popular music as well. Paul Théberge pointed out that the
``democratization'' of synthesizers in the 1980s was achieved through
the concealment of technology, which transformed musicians as creators
into consumers.

\begin{quote}
Lacking adequate knowledge of the technical system, musicians
increasingly found themselves drawn to prefabricated programs as a
source of new sound material. As I have argued, however, this assertion
is not simply a state ment of fact; it also suggests a
reconceptualization on the part of the industry of the musician as a
particular type of consumer. \citep[p89]{theberge_any_1997}
\end{quote}

This argument can be extended beyond electronic music to encompass
computer-based music in general. For example, media researcher Lori
Emerson noted that while the proliferation of personal computers began
with the vision of ``metamedia''---tools that users could modify
themselves, as exemplified by Xerox PARC's Dynabook---the vision was
ultimately realized in an incomplete form through devices like the
Macintosh and iPad, which distanced users from programming by
black-boxing functionality \citep{emerson2014}. In fact, Alan Kay, the
architect behind the Dynabook concept, remarked that while the iPad's
appearance may resemble the ideal he originally envisioned, its lack of
extensibility through programming renders it merely a device for media
consumption \citep{kay2019}.

Although programming environments as tools for music production are not
widely used, the Unit Generator concept, alongside MIDI, serves as a
foundational paradigm for today's consumer music production software and
infrastructure, including Web Audio. It is known that the concept of
Unit Generators emerged either simultaneously with or even slightly
before modular synthesizers \citep[p20]{park_interview_2009}. However,
UGen-based languages have actively incorporated the user interface
metaphors of modular synthesizers, as Vercoe said that the distinction
between ``ar'' (audio-rate) and ``kr'' (control-rate) processing
introduced in MUSIC 11 is said to have been inspired by Buchla's
differentiation between control and audio signals in its plug type
\citep[1:01:38--1:04:04]{vercoe_barry_2012}.

However, adopting visual metaphors comes with the limitation that it
constrains the complexity of representation to what is visually
conceivable. In languages with visual patching interfaces like Max and
Pure Data, meta-operations on UGens are often restricted to simple
tasks, such as parallel duplication. Consequently, even users of Max or
Pure Data may not necessarily be engaging in expressions that are only
possible with computers. Instead, many might simply be using these tools
as the most convenient software equivalents of modular synthesizers.

\section{Context of Programming Languages for Music After
2000}\label{context-of-programming-languages-for-music-after-2000}

Based on the discussions thus far, music programming languages developed
after the 2000s can be categorized into two distinct directions: those
that narrow the scope of the language's role by attempting alternative
abstractions at a higher level, distinct from the Unit Generator
paradigm, and those that expand the general-purpose capabilities of the
language, reducing black-boxing.

Languages that pursued alternative abstractions at higher levels have
evolved alongside the culture of live coding, where performances are
conducted by rewriting code in real time. The activities of the live
coding community, including groups such as TOPLAP since the 2000s, were
not only about turning coding itself into a performance but also served
as a resistance against laptop performances that relied on black-boxed
music software. This is evident in the community's manifesto, which
states, ``Obscurantism is dangerous''
\citep{toplap_manifestodraft_2004}.

Languages implemented as clients for SuperCollider, such as \textbf{IXI}
(on Ruby) \citep{Magnusson2011}, \textbf{Sonic Pi}(on Ruby),
\textbf{Overtone} (on Clojure) \citep{Aaron2013}, \textbf{TidalCycles}
(on Haskell) \citep{McLean2014}, and \textbf{FoxDot} (on Python)
\citep{kirkbride2016foxdot}, leverage the expressive power of more
general-purpose programming languages. While embracing the UGen
paradigm, they enable high-level abstractions for previously
difficult-to-express elements like note values and rhythm. For example,
the abstraction of patterns in TidalCycles is not limited to music but
can also be applied to visual patterns and other outputs, meaning it is
not inherently tied to PCM-based waveform output as the final result.

On the other hand, due to their high-level design, these languages often
rely on ad hoc implementations for tasks like sound manipulation and
low-level signal processing, such as effects.

McCartney, the developer of SuperCollider, once stated that if
general-purpose programming languages were sufficiently expressive,
there would be no need to create specialized languages
\citep{McCartney2002}. This prediction appears reasonable when
considering examples like MUSIGOL. However, in practice, scripting
languages that excel in dynamic program modification face challenges in
modern preemptive OS environments. For instance, dynamic memory
management techniques such as garbage collection can hinder the ability
to guarantee deterministic execution timing required for real-time
processing \citep{Dannenberg2005}.

Historically, programming in languages like FORTRAN or C served as a
universal method for implementing audio processing on computers,
independent of architecture. However, with the proliferation of
general-purpose programming languages, programming in C or C++ has
become relatively more difficult, akin to programming in assembly
language in earlier times. Furthermore, considering the challenges of
portability across not only different CPUs but also diverse host
environments such as operating systems and the Web, these languages are
no longer as portable as they once were. Consequently, systems targeting
signal processing implemented as internal DSLs have become exceedingly
rare, with only a few examples like LuaAV \citep{wakefield2010}.

Instead, an approach has emerged to create general-purpose languages
specifically designed for use in music from the ground up. One prominent
example is \textbf{Extempore}, a live programming environment developed
by Sorensen \citep{sorensenExtemporeDesignImplementation2018}. Extempore
consists of Scheme, a LISP-based language, and xtlang, a
meta-implementation on top of Scheme. While xtlang requires users to
write hardware-oriented type signatures similar to those in C, it
leverages the LLVM compiler infrastructure \citep{Lattner} to
just-in-time (JIT) compile signal processing code, including sound
manipulation, into machine code for high-speed execution.

The expressive power of general-purpose languages and compiler
infrastructures like LLVM have given rise to an approach focused on
designing languages with formalized abstractions that reduce
black-boxing. \textbf{Faust} \citep{Orlarey2009}, for example, is a
language that retains a graph-based structure akin to UGens but is built
on a formal system called Block Diagram Algebra. This system integrates
primitives for reading and writing internal states, which are essential
for operations like delays and filters. Thanks to its formalization,
Faust can be transpiled into general-purpose languages such as C, C++,
or Rust and can also be used as an External Object in environments like
Max or Pure Data.

Languages like \textbf{Kronos}
\citep{noriloKronosReimaginingMusical2016} and \textbf{mimium}
\citep{matsuura2021}, which are based on the more general computational
model of lambda calculus, focus on PCM-based signal processing while
exploring interactive meta-operations on programs \citep{Norilo2016} and
balancing self-contained semantics with interoperability with other
general-purpose languages \citep{matsuura2024}.

Domain-specific languages (DSLs) are constructed within a double bind:
they aim to specialize in a particular purpose while still providing a
certain degree of expressive freedom through programming. In this
context, efforts like Extempore, Kronos, and mimium are not merely
programming languages for music but are also situated within the broader
research context of Functional Reactive Programming (FRP), which focuses
on representing time-varying values in computation. Most computer
hardware lacks an inherent concept of real time and instead operates
based on discrete computational steps. Similarly, low-level
general-purpose programming languages do not natively include primitives
for real-time concepts. Consequently, the exploration of computational
models tied to time---a domain inseparable from music---remains vital
and has the potential to contribute to the theoretical foundations of
general-purpose programming languages.

However, strongly formalized languages come with their own trade-offs.
While they allow UGens to be defined without black-boxing, understanding
the design and implementation of these languages often requires advanced
knowledge. This can create a significant divide between language
developers and users, in contrast to the more segmented roles seen in
the Multi-Language paradigm---such as SuperCollider developers, external
UGen developers, client language developers (e.g., TidalCycles),
SuperCollider users, and client language users.

Although there is no clear solution to this trade-off, one intriguing
idea is the development of self-hosting languages for music---that is,
languages where their own compilers are written in the language itself.
At first glance, this may seem impractical. However, by enabling users
to learn and modify the language's mechanisms spontaneously, this
approach could create an environment that fosters deeper engagement and
understanding among users.

\section{Conclusion}\label{conclusion}

This paper has reexamined the history of computer music and music
programming languages with a focus on the universalism of PCM and the
black-boxing tendencies of the Unit Generator paradigm. Historically, it
was expected that the clear division of roles between engineers and
composers would enable the creation of new forms of expression using
computers. Indeed, from the perspective of Post-Acousmatic discourse,
some, like Holbrook and Rudi, still consider this division to be a
positive development:

\begin{quote}
Most newer tools abstract the signal processing routines and variables,
making them easier to use while removing the need for understanding the
underlying processes in order to create meaningful results. Composers no
longer necessarily need mathematical and programming skills to use the
technologies. These abstractions are important, as they hide many of the
technical details and make the software and processes available to more
people, and form the basis for what can arguably be seen as a new folk
music. \citep[p2]{holbrook2022}
\end{quote}

However, this division of labor also creates a shared
vocabulary---exemplified by the Unit Generator itself, pioneered by
Mathews---and works to perpetuate it. By portraying new technologies as
something externally introduced, and by focusing on the agency of those
who create music with computers, the individuals responsible for
building the programming environments, software, protocols, and formats
are rendered invisible \citep{sterne_there_2014}. This leads to an
oversight of the indirect power relationships produced by these
infrastructures.

For this reason, future research on programming languages for music must
address how the tools, including the languages themselves, contribute
aesthetic value within musical culture (and what forms of musical
practice they enable), as well as the social (im)balances of power they
produce.

It has been noted in programming language research that evaluation
criteria such as efficiency, expressiveness, and generality are often
ambiguous \citep{Markstrum2010}. This issue is even more acute in fields
like music, where no clear evaluation criteria exist. Thus, as McPherson
et al.~have proposed with the concept of Idiomaticity
\citep{McPherson2020}, we need to develop and share a vocabulary for
understanding the value judgments we make about programming languages in
general.

In a broader sense, the creation of programming languages for music has
also expanded to the individual level. Examples include \textbf{Gwion}
by Astor, which builds on ChucK and enhances its abstraction
capabilities with features like lambda functions \citep{astorGwion2017};
\textbf{Vult}, a DSP transpiler language created by Ruiz for his modular
synthesizer hardware \citep{ruizVultLanguage2020}; and a UGen-based live
coding environment designed for web execution, \textbf{Glicol}
\citep{lan_glicol_2020}. However, these efforts have not yet been
adequately integrated into academic discourse.

Conversely, practical knowledge of university-researched languages from
the past, as well as real-time hardware-oriented systems from the 1980s,
is gradually being lost. While research efforts such as \emph{Inside
Computer Music}, which analyzes historical works of computer music, have
begun \citep{clarke_inside_2020}, an archaeological practice focused on
the construction of computer music systems will also be necessary in the
future. This includes not only collecting primary resources, such as
oral archives from those involved, but also reconstructing the knowledge
and practices behind these systems.
