English

Less Is More: Tuning Configurable Systems with Imperfect Fidelity

Software Engineering 2026-08-01 v1 Artificial Intelligence Databases Performance

Abstract

Configuration tuning is essential for optimizing the performance of highly configurable systems, e.g., throughput or runtime, under a given environment. Yet, this is a challenging process as there can be many options to tune, and configuration measurement is often highly expensive. In this paper, we demonstrate the phenomenon of ``less can be more'': system configuration tuning can be greatly improved with much superior budget utilization by partially tuning under the imperfect-fidelity---an environment that is similar, but cheaper to measure, compared with the concerned perfect-fidelity of environment under which the system should be tuned. We codify a conceptual framework of fidelity for configurable systems, drawing on which allows us to propose MFTune, a tuner that proactively explores in the space of >104>10^4 possible imperfect-fidelity settings to approximate a useful one, which strikes for the wideness of tuning. This creates high-quality seeds for the perfect-fidelity, which in turn ensures the tuning depth. Experiment results against 1010 state-of-the-art tuners, obtained from running diverse real-world systems for 1919 months 24×724 \times 7, show that MFTune performs considerably better on 83.3383.33\% cases with up to 19.34%19.34\% improvement while achieving hours of budget saving in general.

Keywords

Cite

@article{arxiv.2608.00759,
  title  = {Less Is More: Tuning Configurable Systems with Imperfect Fidelity},
  author = {Yulong Ye and Miqing Li and Tao Chen},
  journal= {arXiv preprint arXiv:2608.00759},
  year   = {2026}
}

Comments

Accepted by the 41st IEEE/ACM International Conference on Automated Software Engineering (ASE 2026)