Identifying New Fault Types Using Transformer Embeddings

Identifying New Fault Types Using Transformer Embeddings

Continuous integration/delivery and deployment consist of many automated tests, some of which may fail leading to faulty software. Similar faults may occur in different stages of the software production lifecycle and it is necessary to identify similar faults and cluster them into fault types in ord...

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Bibliographic Details
Main Author: Karlsson, Mikael
Format: Others
Language:English
Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2021
Subjects:
Transformer Models
Clustering
Embeddings
Deep Learning
Fault Identification
Transformatorbaserade modeller
Klustering
Djupinlärning
Felidentifiering
Computer Sciences
Datavetenskap (datalogi)
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-303009

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-303009

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