Performance Analysis with Bayesian Inference

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Sammanfattning

Statistics are part of any empirical science, and performance analysis is no exception. However, for non-statisticians, picking the right statistical tool to answer a research question can be challenging; each statistical tool comes with a set of assumptions, and it is not clear to researchers what happens when those assumptions are violated. Bayesian statistics offers a framework with more flexibility and with explicit assumptions. In this paper, we present a method to analyse benchmark results using Bayesian inference. We demonstrate how to perform a Bayesian analysis of variance (ANOVA) to estimate what factors matter most for performance, and describe how to investigate what factors affect the impact of optimizations. We find the Bayesian model more flexible, and the Bayesian ANOVA’s output easier to interpret.
Originalspråkengelska
Titel på värdpublikation2023 IEEE/ACM 45th International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER)
FörlagIEEE - Institute of Electrical and Electronics Engineers Inc.
ISBN (elektroniskt)979-8-3503-0039-0
ISBN (tryckt)979-8-3503-0040-6
DOI
StatusPublished - 2023
EvenemangThe 45th International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER) - Melbourne, Australien
Varaktighet: 2023 maj 142023 maj 20
https://conf.researchr.org/track/icse-2023/icse-2023-NIER

Konferens

KonferensThe 45th International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER)
Förkortad titelICSE-NIER
Land/TerritoriumAustralien
OrtMelbourne
Period2023/05/142023/05/20
Internetadress

Ämnesklassifikation (UKÄ)

  • Sannolikhetsteori och statistik
  • Datavetenskap (datalogi)

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