Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4-Reference-Cited by-同舟云学术

Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4

Published:2024-07-10 Issue: Volume:33 Page:266-277
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Container-title:Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering
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Author:

Zhang Xuchao¹^ORCID,Ghosh Supriyo²^ORCID,Bansal Chetan³^ORCID,Wang Rujia¹^ORCID,Ma Minghua¹^ORCID,Kang Yu⁴^ORCID,Rajmohan Saravan¹^ORCID

Affiliation:

1. Microsoft, Redmond, United States

2. Microsoft, Bangalore, India

3. Microsoft, Redmond, USA

4. Microsoft, Shanghai, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3663529.3663846

Reference45 articles.

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4. Satanjeev Banerjee and Alon Lavie. 2005. METEOR: An automatic metric for MT evaluation with improved correlation with human judgments. In Proceedings of the acl workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization. 65–72.

5. Chetan Bansal, Sundararajan Renganathan, Ashima Asudani, Olivier Midy, and Mathru Janakiraman. 2020. DeCaf: Diagnosing and Triaging Performance Issues in Large-Scale Cloud Services. In 2020 IEEE/ACM 42nd International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP).