Learning software configuration spaces: A systematic literature review

JA Pereira, M Acher, H Martin, JM Jézéquel… - Journal of Systems and …, 2021 - Elsevier
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 …

Finding Faster Configurations Using FLASH

V Nair, Z Yu, T Menzies, N Siegmund… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
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 …

Transfer learning for performance modeling of configurable systems: An exploratory analysis

P Jamshidi, N Siegmund, M Velez… - 2017 32nd IEEE …, 2017 - ieeexplore.ieee.org
Modern software systems provide many configuration options which significantly influence
their non-functional properties. To understand and predict the effect of configuration options …

Using bad learners to find good configurations

V Nair, T Menzies, N Siegmund, S Apel - … of the 2017 11th joint meeting …, 2017 - dl.acm.org
Finding the optimally performing configuration of a software system for a given setting is
often challenging. Recent approaches address this challenge by learning performance …

DeepPerf: Performance prediction for configurable software with deep sparse neural network

H Ha, H Zhang - 2019 IEEE/ACM 41st International Conference …, 2019 - ieeexplore.ieee.org
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 …

Arrow: Low-level augmented bayesian optimization for finding the best cloud vm

CJ Hsu, V Nair, VW Freeh… - 2018 IEEE 38th …, 2018 - ieeexplore.ieee.org
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 …

Learning to sample: Exploiting similarities across environments to learn performance models for configurable systems

P Jamshidi, M Velez, C Kästner… - … of the 2018 26th ACM Joint …, 2018 - dl.acm.org
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 …

Sampling effect on performance prediction of configurable systems: A case study

J Alves Pereira, M Acher, H Martin… - Proceedings of the ACM …, 2020 - dl.acm.org
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 …

Machine learning meets quantitative planning: Enabling self-adaptation in autonomous robots

P Jamshidi, J Cámara, B Schmerl… - 2019 IEEE/ACM 14th …, 2019 - ieeexplore.ieee.org
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 …

Unicorn: Reasoning about configurable system performance through the lens of causality

MS Iqbal, R Krishna, MA Javidian, B Ray… - Proceedings of the …, 2022 - dl.acm.org
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 …