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cs.SE2025
Evaluating Useful Surrogate Models for Configuration Tuning Beyond Accuracy: A Fitness Landscape Analysis Perspective
Pengzhou Chen, Hongyuan Liang, Tao Chen
To efficiently tune configuration for better software system performance (e.g., latency) at the deployment and maintenance stage, many tuners have leveraged a surrogate model to ex…
cs.SE2025
PromiseTune: Unveiling Causally Promising and Explainable Configuration Tuning
Pengzhou Chen, Tao Chen
The high configurability of modern software systems has made configuration tuning a crucial step for assuring system performance, e.g., latency or throughput. However, given the ex…
cs.SE2025
Accuracy Can Lie: On the Impact of Surrogate Model in Configuration Tuning
Pengzhou Chen, Jingzhi Gong, Tao Chen
To ease the expensive measurements during configuration tuning, it is natural to build a surrogate model as the replacement of the system, and thereby the configuration performance…