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 …
Maintainability challenges in ML: A systematic literature review
K Shivashankar, A Martini - 2022 48th Euromicro Conference …, 2022 - ieeexplore.ieee.org
Background: As Machine Learning (ML) advances rapidly in many fields, it is being adopted
by academics and businesses alike. However, ML has a number of different challenges in …
by academics and businesses alike. However, ML has a number of different challenges in …
The weights can be harmful: Pareto search versus weighted search in multi-objective search-based software engineering
In presence of multiple objectives to be optimized in Search-Based Software Engineering
(SBSE), Pareto search has been commonly adopted. It searches for a good approximation of …
(SBSE), Pareto search has been commonly adopted. It searches for a good approximation of …
Data set quality in machine learning: consistency measure based on group decision making
Abstract Performance of Machine Learning models heavily depends on the quality of the
training dataset. Among others, the quality of training data relies on the consistency of the …
training dataset. Among others, the quality of training data relies on the consistency of the …
Lifelong self-adaptation: Self-adaptation meets lifelong machine learning
In the past years, machine learning (ML) has become a popular approach to support self-
adaptation. While ML techniques enable dealing with several problems in self-adaptation …
adaptation. While ML techniques enable dealing with several problems in self-adaptation …
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 …
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 …
Predicting configuration performance in multiple environments with sequential meta-learning
Learning and predicting the performance of given software configurations are of high
importance to many software engineering activities. While configurable software systems will …
importance to many software engineering activities. While configurable software systems will …
How do we evaluate self-adaptive software systems?: A ten-year perspective of SEAMS
With the increase of research in self-adaptive systems, there is a need to better understand
the way research contributions are evaluated. Such insights will support researchers to …
the way research contributions are evaluated. Such insights will support researchers to …
Predicting Software Performance with Divide-and-Learn
Predicting the performance of highly configurable software systems is the foundation for
performance testing and quality assurance. To that end, recent work has been relying on …
performance testing and quality assurance. To that end, recent work has been relying on …