An empirical study of the impact of hyperparameter tuning and model optimization on the performance properties of deep neural networks
Deep neural network (DNN) models typically have many hyperparameters that can be
configured to achieve optimal performance on a particular dataset. Practitioners usually tune …
configured to achieve optimal performance on a particular dataset. Practitioners usually tune …
On the effectiveness of log representation for log-based anomaly detection
Logs are an essential source of information for people to understand the running status of a
software system. Due to the evolving modern software architecture and maintenance …
software system. Due to the evolving modern software architecture and maintenance …
PrePass-Flow: A Machine Learning based technique to minimize ACL policy violation due to links failure in hybrid SDN
The centralized architecture of Software-Defined Networking (SDN) reduces networking
complexity and improves network manageability by omitting the need for box-by-box …
complexity and improves network manageability by omitting the need for box-by-box …
Performance regression testing initiatives: A systematic map**
Context: Issues related to the performance of software systems are crucial, as they have the
potential to impede the effective utilization of products, compromise user satisfaction …
potential to impede the effective utilization of products, compromise user satisfaction …
A case study on the stability of performance tests for serverless applications
Context: While in serverless computing, application resource management and operational
concerns are generally delegated to the cloud provider, ensuring that serverless …
concerns are generally delegated to the cloud provider, ensuring that serverless …
IoPV: On inconsistent option performance variations
Maintaining a good performance of a software system is a primordial task when evolving a
software system. The performance regression issues are among the dominant problems that …
software system. The performance regression issues are among the dominant problems that …
Logsd: Detecting anomalies from system logs through self-supervised learning and frequency-based masking
Log analysis is one of the main techniques that engineers use for troubleshooting large-
scale software systems. Over the years, many supervised, semi-supervised, and …
scale software systems. Over the years, many supervised, semi-supervised, and …
Understanding Web Application Workloads and Their Applications: Systematic Literature Review and Characterization
Web applications, accessible via web browsers over the Internet, facilitate complex
functionalities without local software installation. In the context of web applications, a …
functionalities without local software installation. In the context of web applications, a …
CoMSA: A Modeling-Driven Sampling Approach for Configuration Performance Testing
Highly configurable systems enable customers to flexibly configure the systems in diverse
deployment environments. The flexibility of configurations also poses challenges for …
deployment environments. The flexibility of configurations also poses challenges for …
Performance regression detection in devops
J Chen - Proceedings of the ACM/IEEE 42nd International …, 2020 - dl.acm.org
Performance is an important aspect of software quality. The goals of performance are
typically defined by setting upper and lower bounds for response time and throughput of a …
typically defined by setting upper and lower bounds for response time and throughput of a …