PROGRAMMING LOGIC APPLIED TO ALGORITHMIC MUSIC COMPOSITION

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Authors: Clenio Batista Gonçalves
Cited by: 0

Abstract

Creating music software relies fundamentally on elements such as programming languages, reasoning paradigms, libraries, APIs, and frameworks, which together shape both the technical architecture and creative potential of musical composition. This work presents the design and implementation of a multi-paradigm environment that enables building software for comprehensive sound manipulation, while addressing specific demands of automatic music composition. The proposed environment integrates imperative, object-oriented, functional, and logic programming, bringing together structural control, expressiveness, and declarative reasoning within a unified platform. Entirely based on free software, it employs open-source tools to ensure flexibility, transparency, and community-driven evolution. Java acts as the structural backbone, organizing the system’s architecture; Scala offers functional abstractions for concise musical transformations; and Prolog provides logical inference and knowledge representation for modeling musical structures and rules. In addition, integration with APIs such as Java Sound and jMusic allows tasks like score generation, harmonic analysis, and synthesis of musical phrases and chords. This setup supports automating the creation of musical excerpts and encoding compositional knowledge, fostering algorithmic creativity. The resulting environment offers an effective, extensible, and accessible solution for computer music research, teaching, and creative experimentation. By leveraging open-source technologies, it promotes interdisciplinary collaboration and continuous innovation in algorithmic composition, ultimately contributing to advancing knowledge representation and automatic music generation.

Fields of Study & Subjects

Music Technology and Sound Studies Machine Learning in Materials Science Music and Audio Processing

Publication details

Journal / source
International Contemporary Management Review
Volume
7
Issue
1
Pages
e435–e435
Publication date
7 January 2026