Applying machine learning in self-adaptive systems: A systematic literature review
Recently, we have been witnessing a rapid increase in the use of machine learning
techniques in self-adaptive systems. Machine learning has been used for a variety of …
techniques in self-adaptive systems. Machine learning has been used for a variety of …
How to evaluate solutions in Pareto-based search-based software engineering: A critical review and methodological guidance
With modern requirements, there is an increasing tendency of considering multiple
objectives/criteria simultaneously in many Software Engineering (SE) scenarios. Such a …
objectives/criteria simultaneously in many Software Engineering (SE) scenarios. Such a …
The application of machine learning in self-adaptive systems: A systematic literature review
TRD Saputri, SW Lee - IEEE Access, 2020 - ieeexplore.ieee.org
Context: Self-adaptive systems have been studied in software engineering over the past few
decades attempting to address challenges within the field. There is a continuous significant …
decades attempting to address challenges within the field. There is a continuous significant …
A survey and taxonomy of self-aware and self-adaptive cloud autoscaling systems
Autoscaling system can reconfigure cloud-based services and applications, through various
configurations of cloud software and provisions of hardware resources, to adapt to the …
configurations of cloud software and provisions of hardware resources, to adapt to the …
FEMOSAA: Feature-guided and knee-driven multi-objective optimization for self-adaptive software
Self-Adaptive Software (SAS) can reconfigure itself to adapt to the changing environment at
runtime, aiming to continually optimize conflicted nonfunctional objectives (eg, response …
runtime, aiming to continually optimize conflicted nonfunctional objectives (eg, response …
Multi-objectivizing software configuration tuning
Automatically tuning software configuration for optimizing a single performance attribute (eg,
minimizing latency) is not trivial, due to the nature of the configuration systems (eg, complex …
minimizing latency) is not trivial, due to the nature of the configuration systems (eg, complex …
Deep configuration performance learning: A systematic survey and taxonomy
Performance is arguably the most crucial attribute that reflects the quality 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 …
Does configuration encoding matter in learning software performance? An empirical study on encoding schemes
Learning and predicting the performance of a configurable software system helps to provide
better quality assurance. One important engineering decision therein is how to encode the …
better quality assurance. One important engineering decision therein is how to encode the …
All versus one: an empirical comparison on retrained and incremental machine learning for modeling performance of adaptable software
T Chen - 2019 IEEE/ACM 14th International Symposium on …, 2019 - ieeexplore.ieee.org
Given the ever-increasing complexity of adaptable software systems and their commonly
hidden internal information (eg, software runs in the public cloud), machine learning based …
hidden internal information (eg, software runs in the public cloud), machine learning based …
Lifelong dynamic optimization for self-adaptive systems: Fact or fiction?
T Chen - 2022 IEEE International Conference on Software …, 2022 - ieeexplore.ieee.org
When faced with changing environment, highly-configurable software systems need to
dynamically search for promising adaptation plan that keeps the best possible performance …
dynamically search for promising adaptation plan that keeps the best possible performance …