Softwaretechnik-Trends 44(2) - 2024

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Konferenzbeitrag
ATDLLMD: Acceptance test-driven LLM development
(Softwaretechnik-Trends Band 44, Heft 2, 2024) Faragó, David
Since the capabilities of Large Language Models (LLMs) have massively increased in the last years, many new applications based on LLMs are possible. However, these new applications also pose new challenges in LLM development. This article proposes an acceptance test-driven development (ATDD) style, baptized ATDLLMD, where the LLM’s training and test sets are extended in each iteration by data coming from validation of the previous iteration’s LLM and system around the LLM. So the validation phase supplies the additional or updated data for training and verification of the LLM. ATDLLMD is made possible by two major innovative solutions: applying the innovative CPMAI process, and applying our own verification tool, LM-Eval, leading to a red-train green cycle for LLM development, which resembles ATDD, but integrates data science best practices.
Konferenz-Abstract
Bericht
(Softwaretechnik-Trends Band 44, Heft 2, 2024) Sokenou, Dehla; Friske, Mario; Güldali, Baris; Faragó, David; Winter, Mario
Das 49. Treffen der GI-Fachgruppe TAV fand am 15. und 16. Februar 2024 statt und stand unter dem Motto Qualität sichtbar, messbar und bewertbar machen. Das Programm umfasste neben der Keynote von Mario Winter acht weitere Vorträge aus den Bereichen Best Practices, KI und Qualitätssicherung und Erfahrungen mit Toolchains.