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Found 6 papers, 0 papers with code
Language Models for Novelty Detection in System Call Traces
Due to the complexity of modern computer systems, novel and unexpected behaviors frequently occur.
A Practical Survey on Faster and Lighter Transformers
Recurrent neural networks are effective models to process sequences.
On Improving Deep Learning Trace Analysis with System Call Arguments
Such tasks may be used to detect anomalies, pre-train neural networks to improve their performance, and extract a contextual representation of the events.
Automatic Cause Detection of Performance Problems in Web Applications
In this paper, we propose a method of extracting the internal behavior of web requests as well as introduce a pipeline that detects performance issues in web requests and provides insights into their root causes.
Empirical comparison between autoencoders and traditional dimensionality reduction methods
The four different dimensionality reduction techniques were separately employed on each dataset to project data into a low-dimensional space.
DepGraph: Localizing Performance Bottlenecks in Multi-Core Applications Using Waiting Dependency Graphs and Software Tracing
In this paper, we use a system level tracing approach to extract a Waiting Dependency Graph that shows the breakdown of a task execution among all the interleaving threads and resources.
Software Engineering
