Distance-based sampling of software configuration spaces

C Kaltenecker, A Grebhahn… - 2019 IEEE/ACM 41st …, 2019 - ieeexplore.ieee.org
Configurable software systems provide a multitude of configuration options to adjust and
optimize their functional and non-functional properties. For instance, to find the fastest …

Identifying software performance changes across variants and versions

S Mühlbauer, S Apel, N Siegmund - Proceedings of the 35th IEEE/ACM …, 2020 - dl.acm.org
We address the problem of identifying performance changes in the evolution of configurable
software systems. Finding optimal configurations and configuration options that influence …

Uniform and scalable sampling of highly configurable systems

R Heradio, D Fernandez-Amoros, JA Galindo… - Empirical Software …, 2022 - Springer
Many analyses on configurable software systems are intractable when confronted with
colossal and highly-constrained configuration spaces. These analyses could instead use …

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 …

Mastering uncertainty in performance estimations of configurable software systems

J Dorn, S Apel, N Siegmund - Proceedings of the 35th IEEE/ACM …, 2020 - dl.acm.org
Understanding the influence of configuration options on performance is key for finding
optimal system configurations, system understanding, and performance debugging. In prior …

Analysing the Impact of Workloads on Modeling the Performance of Configurable Software Systems

S Mühlbauer, F Sattler, C Kaltenecker… - 2023 IEEE/ACM 45th …, 2023 - ieeexplore.ieee.org
Modern software systems often exhibit numerous configuration options to tailor them to user
requirements, including the system's performance behavior. Performance models derived …

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 …

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 …

A comparison of 10 sampling algorithms for configurable systems

F Medeiros, C Kästner, M Ribeiro, R Gheyi… - Proceedings of the 38th …, 2016 - dl.acm.org
Almost every software system provides configuration options to tailor the system to the target
platform and application scenario. Often, this configurability renders the analysis of every …

White-box analysis over machine learning: Modeling performance of configurable systems

M Velez, P Jamshidi, N Siegmund… - 2021 IEEE/ACM …, 2021 - ieeexplore.ieee.org
Performance-influence models can help stakeholders understand how and where
configuration options and their interactions influence the performance of a system. With this …