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Learning software configuration spaces: A systematic literature review
Most modern software systems (operating systems like Linux or Android, Web browsers like
Firefox or Chrome, video encoders like ffmpeg, x264 or VLC, mobile and cloud applications …
Firefox or Chrome, video encoders like ffmpeg, x264 or VLC, mobile and cloud applications …
Finding Faster Configurations Using FLASH
Finding good configurations of a software system is often challenging since the number of
configuration options can be large. Software engineers often make poor choices about …
configuration options can be large. Software engineers often make poor choices about …
Transfer learning for performance modeling of configurable systems: An exploratory analysis
Modern software systems provide many configuration options which significantly influence
their non-functional properties. To understand and predict the effect of configuration options …
their non-functional properties. To understand and predict the effect of configuration options …
Using bad learners to find good configurations
Finding the optimally performing configuration of a software system for a given setting is
often challenging. Recent approaches address this challenge by learning performance …
often challenging. Recent approaches address this challenge by learning performance …
DeepPerf: Performance prediction for configurable software with deep sparse neural network
Many software systems provide users with a set of configuration options and different
configurations may lead to different runtime performance of the system. As the combination …
configurations may lead to different runtime performance of the system. As the combination …
Arrow: Low-level augmented bayesian optimization for finding the best cloud vm
With the advent of big data applications, which tend to have longer execution time, choosing
the right cloud VM has significant performance and economic implications. For example, in …
the right cloud VM has significant performance and economic implications. For example, in …
Learning to sample: Exploiting similarities across environments to learn performance models for configurable systems
Most software systems provide options that allow users to tailor the system in terms of
functionality and qualities. The increased flexibility raises challenges for understanding the …
functionality and qualities. The increased flexibility raises challenges for understanding the …
Sampling effect on performance prediction of configurable systems: A case study
Numerous software systems are highly configurable and provide a myriad of configuration
options that users can tune to fit their functional and performance requirements (eg …
options that users can tune to fit their functional and performance requirements (eg …
Machine learning meets quantitative planning: Enabling self-adaptation in autonomous robots
Modern cyber-physical systems (eg, robotics systems) are typically composed of physical
and software components, the characteristics of which are likely to change over time …
and software components, the characteristics of which are likely to change over time …
Unicorn: Reasoning about configurable system performance through the lens of causality
Modern computer systems are highly configurable, with the total variability space sometimes
larger than the number of atoms in the universe. Understanding and reasoning about the …
larger than the number of atoms in the universe. Understanding and reasoning about the …