Using deep reinforcement learning for exploratory performance testing of software systems with multi-dimensional input spaces
During exploratory performance testing, software testers evaluate the performance of a
software system with different input combinations in order to identify combinations that cause …
software system with different input combinations in order to identify combinations that cause …
Learning input-aware performance models of configurable systems: An empirical evaluation
Modern software-based systems are highly configurable and come with a number of
configuration options that impact the performance of the systems. However, selecting …
configuration options that impact the performance of the systems. However, selecting …
Capture the feature flag: Detecting feature flags in open-source
J Meinicke, J Hoyos, B Vasilescu… - Proceedings of the 17th …, 2020 - dl.acm.org
Feature flags (aka feature toggles) are a mechanism to keep new features hidden behind a
boolean option during development. Flags are used for many purposes, such as A/B testing …
boolean option during development. Flags are used for many purposes, such as A/B testing …
Transfer learning for performance modeling of deep neural network systems
Modern deep neural network (DNN) systems are highly configurable with large a number of
options that significantly affect their non-functional behavior, for example inference time and …
options that significantly affect their non-functional behavior, for example inference time and …
CRSExtractor: Automated configuration option read sites extraction towards IoT cloud infrastructure
There are a large number of solutions for big data processing in the Internet of Things (IoT)
environments, among which the IoT cloud infrastructure is one of the most mature solutions …
environments, among which the IoT cloud infrastructure is one of the most mature solutions …
A survey of access control misconfiguration detection techniques
B Shen - arXiv preprint arXiv:2304.07704, 2023 - arxiv.org
Access control mechanisms have been adopted in many real-world systems to control
resource sharing for the principals in the system. An error in the access control policy …
resource sharing for the principals in the system. An error in the access control policy …
Cello: Efficient computer systems optimization with predictive early termination and censored regression
Sample-efficient machine learning (SEML) has been widely applied to find optimal latency
and power tradeoffs for configurable computer systems. Instead of randomly sampling from …
and power tradeoffs for configurable computer systems. Instead of randomly sampling from …
" Project smells" experiences in analysing the software quality of ML projects with mllint
Machine Learning (ML) projects incur novel challenges in their development and
productionisation over traditional software applications, though established principles and …
productionisation over traditional software applications, though established principles and …
Deep Configuration Performance Learning: A Systematic Survey and Taxonomy
Performance is arguably the most crucial attribute that reflects the behavior of a configurable
software system. However, given the increasing scale and complexity of modern software …
software system. However, given the increasing scale and complexity of modern software …
To preserve or not to preserve invalid solutions in search-based software engineering: a case study in software product lines
J Guo, K Shi - Proceedings of the 40th International Conference on …, 2018 - dl.acm.org
Multi-objective evolutionary algorithms (MOEAs) have been successfully applied for
software product lines (SPLs) to search for optimal or near-optimal solutions that balance …
software product lines (SPLs) to search for optimal or near-optimal solutions that balance …