Enhancing Interpretability in Software Change Management with Chain-of-Thought Reasoning

Sun, Yongqian, Kuang, Weihua, Shen, Chao, Wen, Xidao, Zheng, Tinghua, Liu, Heng, Zhang, Shenglin, Wu, Bo, Pei, Dan

arXiv.org Artificial Intelligence 

In modern online services, frequent software changes introduce significant risks. To tackle this challenge, we propose SCELM (Software Change Evaluation and Lifecycle Management), an end-to-end automated framework for software change management. SCELM aims to manage software changes efficiently and precisely, significantly reducing service failures and economic losses.

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