Paterson, Justin ORCID: https://orcid.org/0000-0001-7822-319X
(2025)
Whose line is it anyway? A case study in Generative AI for
software development: MIDI-processing plug-in design.
In:
Innovation in music: suffix TBC.
Innovation in music.
Routledge, Abingdon and New York.
(In Press)
Abstract
This chapter delves into the use of artificial intelligence (AI), particularly large language models (LLMs), for generating software code to create a MIDI-processing plug-in designed for channel multiplexing and pattern-based output routing. Traditionally the domain of skilled developers, audio plug-in creation is now increasingly accessible thanks to AI-powered code generation tools, both browser-based and integrated into custom development environments. The plug-in introduced here demonstrates advanced algorithmic strategies – such as LFO-driven channel cycling, velocity-based channel distribution, and CC-modulated note routing – that allow MIDI data from one channel to be dynamically routed across multiple channels, enabling real-time, musically expressive arrangements.
Drawing from Ascott’s technoetic design philosophy, the research emphasizes AI’s role in simplifying and accelerating the coding process for both novices and seasoned programmers, highlighting how tools like GPT-4o, Claude-4-opus, and Gemini 2.5 Pro support the development of intricate, functional DAW plug-ins. It also evaluates how strategic prompting affects code quality, and presents real-world testing of the generated plug-in, confirming that AI-produced code can perform on par with human-written code. Ultimately, this work contributes to creative software engineering by showing how AI democratizes plug-in development, boosts i
Item Type: | Book Chapter or Section |
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Subjects: | Music |
Depositing User: | Justin Paterson |
Date Deposited: | 05 Sep 2025 07:48 |
Last Modified: | 05 Sep 2025 07:48 |
URI: | https://repository.uwl.ac.uk/id/eprint/14038 | Sustainable Development Goals: | Goal 4: Quality Education |
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