Code and data used to create the examples in "Empirical Software Engineering using R"
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Rlang Multiple plots now vertical Aug 3, 2016
benchmark 2017 Jan update Jan 20, 2017
common Initial release Jan 9, 2016
communicating 2017 Jan update Jan 20, 2017
data-check 2017 Jan update Jan 20, 2017
developers Human cognitive characteristics release Jan 29, 2017
economics 2017 Jan update Jan 20, 2017
ecosystem December update Dec 6, 2016
evolution December update Dec 6, 2016
experiment 2017 Jan update Jan 20, 2017
faults 2017 Jan update Jan 20, 2017
group-compare 2017 Jan update Jan 20, 2017
hardware More minor updates Oct 5, 2016
introduction 2017 Jan update Jan 20, 2017
machine-learning pdf draft almost here Oct 17, 2016
maintenance Human cognitive characteristics release Jan 29, 2017
misc Improvements to help figures stand on their own Aug 21, 2016
not_R Human cognitive characteristics release Jan 29, 2017
probability 2017 Jan update Jan 20, 2017
projects 2017 Jan update Jan 20, 2017
regression 2017 Jan update Jan 20, 2017
reliability December update Dec 6, 2016
social Improvements to help figures stand on their own Aug 21, 2016
src_measure pdf draft almost here Oct 17, 2016
statistics pdf draft almost here Oct 17, 2016
survival pdf draft almost here Oct 17, 2016
time-series pdf draft almost here Oct 17, 2016
CHANGES Human cognitive characteristics release Jan 29, 2017
ESEUR_config.r 2017 Jan update Jan 20, 2017
README.md December update Dec 6, 2016
hello_world.csv Initial release Jan 9, 2016
install.R pdf draft almost here Oct 17, 2016
nanozip-comp-power.csv Multiple plots now vertical Aug 3, 2016

README.md

The code and data used to create the examples in "Empirical Software Engineering using R" by Derek M. Jones.

Blog post giving some background on the book.

Plots of the data.

If you know of any software engineering data that you think should be included, please let me know.

To install all of the R library packages used by the code type:

source("install.R")

at the R command line (if binaries are not available for your system, then they will be built from source and any dependencies will not automatically be detected).

All programs read the file: ESEUR_config.r. Put a copy of this file in what R considers to be its home directory.

This file sets the variable ESEUR_dir to contain the base directory containing all the code+data. The default value is R's home directory.

The .R files are a superset of what appear in the book. If some data was analyzed and I thought it useful, but could not find a place for it in the book, it was put in a misc/ directory (some files may not have been moved).

The data was very recently compressed to get under Github size limits and reduce download time. You might find some filename strings are missing a .xz.