Software logs play a vital role in ensuring the reliability and availability of large-scale software systems. In recent years, researchers have made significant efforts to build log analysis approaches to manage software systems. However, these approaches focus on log compression, log parsing and log anomaly detection. In the current context, engineers continue to spend substantial time and effort on resolving errors once anomalous logs have been detected. To achieve truly automated software system management and high-level Artificial Intelligence for IT Operations (AIOps), it's necessary to bridge the gap between anomalous logs and their resolutions.
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Wang et al. (2024) studied this question.
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