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A State-of-the-practice Release-readiness Checklist for Generative AI-based Software Products

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arxiv 2403.18958 v1 pith:TICQSLL7 submitted 2024-03-27 cs.SE cs.AI

classification cs.SEcs.AI
keywords challengeschecklistllmsproductsreadinessreleasesoftwareai-based
verification ladder T0 review T1 audit T2 compute T3 formal

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This paper investigates the complexities of integrating Large Language Models (LLMs) into software products, with a focus on the challenges encountered for determining their readiness for release. Our systematic review of grey literature identifies common challenges in deploying LLMs, ranging from pre-training and fine-tuning to user experience considerations. The study introduces a comprehensive checklist designed to guide practitioners in evaluating key release readiness aspects such as performance, monitoring, and deployment strategies, aiming to enhance the reliability and effectiveness of LLM-based applications in real-world settings.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. "So what if I used GenAI?" -- Implications of Using Cloud-based GenAI in Software Engineering Research

    cs.SE 2024-12 conditional novelty 4.0 of 10

    The paper proposes the GATE checklist of transparency and accountability questions for researchers using cloud-based GenAI, framed as a risk-mitigation tool.

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