CL-MMAD: A Contrastive Learning Based Multimodal Software Runtime Anomaly Detection Method

CL-MMAD: A Contrastive Learning Based Multimodal Software Runtime Anomaly Detection Method

Software plays a critical role in the infrastructure of modern society. Due to the increasing complexity, it suffers runtime reliability issues. Online anomaly detection can detect partial failures within the program based on manifestations exhibited internally or externally before serious failures...

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Bibliographic Details
Main Authors: Shiyi Kong, Jun Ai, Minyan Lu
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Applied Sciences
Subjects:
software anomaly detection
contrastive learning
multimodal learning
functional failures
performance issues
Online Access:https://www.mdpi.com/2076-3417/13/6/3596

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https://www.mdpi.com/2076-3417/13/6/3596

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