Gregory M. Kapfhammer
Phil McMinn and Chris J. Wright
Inherent in SBST techniques
Necessitates careful experiment design
Statistical analysis of results required!
A Hitchhiker's Guide to Statistical Tests for Assessing Randomized Algorithms in Software Engineering
Arcuri and Briand recommend statistical techniques
Code snippets provided in the R language
A tremendous asset to the SBST community!
Well-meaning researchers may make small mistakes
Marco Torchiano revealed paradoxical effect sizes
Shared repositories of statistical code
Well-tested implementations of procedures
Additional documentation and guidelines
Replication packages for completed analyses
Use GitHub to store data and analysis code
Create R packages using
Reveal your full analysis with
Use "best of breed" tools to support your work!
dplyr for fast data manipulation
tidyr for disciplined data restructuring
ggplot2 for impressive data visualization
Or, use the languages and packages you prefer
But, seriously, Hadley Wickham's code is awesome!
What statistical analysis do you regularly perform?
What is needed to move the SBST community forward?
What types of vehicles do hitchhikers really need?
Sharing data sets larger than what GitHub supports?
Use Git Large File Storage (LFS)
Why don't we release scripts for running experiments?
They are often customized. But, yes, we should!