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Green Dataset: A Dataset for Mining the Impact of Software Change on Energy Consumption

Description of the datasets:

The datasets consist of energy consumption of applications over multiple versions, associated with execution traces under various test cases.

Our datasets were generated by analyzing two open source applications, the text editor gedit and the audio player mpg123. For each application, we have built multiple versions and developed two test cases to gather the data. The data gathered from each test case forms a dataset and it contains the mean power consumption and the corresponding invocation count of system calls for each version. Each dataset is in CSV format and each row in the CSV file represents the data of each application version. The number of columns in each dataset varies because of the number of different system calls traced in different applications as well as test cases. But the first column is always the mean power consumption of each application version ordered chronologically. The rest of the columns are different system calls and each entry shows the number of system call invocations.

Explanation of the text files:

gedit-versions stores the gedit version numbers we have tested under text editing and syntax highlighting test cases.

gedit-commit-version stores the tested gedit version numbers with the corresponding git commit hash.

mpg123-play-mp3-versions stores the mpg123 version numbers we have tested under mp3 playing test case.

mpg123-play-stream-versions stores the mpg123 version number we have tested under stream playing test case.

This is a dataset of data used in

@inproceedings{zhangtrace
  title={Green Trace: The Impact of Software Change on System Calls and Energy Consumption},
  author={Zhang, Chenlei and Campbell, Joshua, and Hindle, Abram},
  booktitle={in submission to Mining Software Repositories (MSR), 2014 11th IEEE Working Conference on},
  year={2014},
  organization={IEEE}
}

LICENSING

The LICENSE for the Source Code is generally GPL-2+ or GPL-2 compatible.

For DATA http://creativecommons.org/licenses/by/4.0/ The LICENSE for the Data is CC-BY 4.0 please attribute Abram Hindle using the following instructions:

To properly attribute Chenlei Zhang on as per the requirements of CC-BY 4.0:

@MastersThesis{zhang2013thesis, author = {Chenlei Zhang}, title = {The Impact of User Choice and Software Change on Energy Consumption}, school = {University of Alberta}, year = {2013}, }

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