Digital History; LLM; Prompt engineering; Apple Lisa; Born Digital Heritage
Abstract :
[en] This presentation explores how Large Language Models (LLMs) assist in analyzing the 1983 Apple Lisa source code. Using AI-driven methodologies like prompt engineering and structured reasoning, it enhances code translation, contextualization, and interpretation. By treating LLMs as analytical assistants, this approach uncovers insights into early software development, coder culture, and the evolution of graphical user interfaces.
Research center :
Luxembourg Centre for Contemporary and Digital History (C2DH) > Contemporary European History (EHI)
Disciplines :
History
Author, co-author :
KAUFFMANN WILL, Titaÿna ; University of Luxembourg > Luxembourg Centre for Contemporary and Digital History (C2DH) > Digital History and Historiography
Language :
English
Title :
Leveraging LLM for Code Studies : Methodological Approach to Read the Apple Lisa’s Source Code
Publication date :
04 March 2025
Event name :
Internal Seminar of the European History Team of the C2DH
Event date :
04.03.2025
FnR Project :
FNR16758026 - Data Science Of Digital History, 2022 (01/01/2023-...) - Andreas Fickers
