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Increasing the Reliability of a Critical Software System Using a Large Language Model Based Solution for Onboarding
Version 1
: Received: 28 May 2024 / Approved: 29 May 2024 / Online: 29 May 2024 (10:27:36 CEST)
A peer-reviewed article of this Preprint also exists.
Schuszter, I.C.; Cioca, M. Increasing the Reliability of Software Systems Using a Large-Language-Model-Based Solution for Onboarding. Inventions 2024, 9, 79. Schuszter, I.C.; Cioca, M. Increasing the Reliability of Software Systems Using a Large-Language-Model-Based Solution for Onboarding. Inventions 2024, 9, 79.
Abstract
Software systems are often maintained by a group of experienced software developers, in order to ensure that faults which may bring the system down are less likely. Large turnover in organizations such as CERN makes it important to think of ways of onboarding newcomers on a technical project rapidly. This paper focuses on optimizing the way that people get up-to-speed on the business logic and technologies used on the project, using a knowledge-imbued large language model that is enhanced using domain-specific knowledge from the group or team’s internal documentation.
Keywords
critical systems, software engineering, onboarding, large language models; LLM; GPT
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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