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tosem2021-personality-rep-package

Replication package for the manuscript "Using Personality Detection Tools for Software Engineering Research: How Far Can We Go?" submitted to TOSEM

https://github.com/collab-uniba/tosem2021-personality-rep-package

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 4 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (13.2%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

Replication package for the manuscript "Using Personality Detection Tools for Software Engineering Research: How Far Can We Go?" submitted to TOSEM

Basic Info
  • Host: GitHub
  • Owner: collab-uniba
  • License: mit
  • Language: HTML
  • Default Branch: main
  • Size: 98.8 MB
Statistics
  • Stars: 1
  • Watchers: 5
  • Forks: 0
  • Open Issues: 1
  • Releases: 1
Created almost 5 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

tosem2021-personality-rep-package DOI

Replication package for the manuscript F. Calefato and F. Lanubile (2021) "Using Personality Detection Tools for Software Engineering Research: How Far Can We Go?" ACM TOSEM, DOI: 10.1145/3491.039.

Requirements

Ensure that your box fulfills the following requirements: * Python 3.8.3+ * R 4.0.4+ * Java 1.8+ * python3-venv * pandoc * LaTeX * homebrew (macOS-only)

On macOS, you can install LaTeX and pandoc by executing brew install mactex pandoc.

On Ubuntu, run sudo apt install texlive-latex-extra pandoc.

Finally, after installing Java, ensure that the environment variable $JAVA_HOME is properly set.

Cloning

The repository uses git submodules. To clone the code and its submodules, run git clone --recursive <repo-url.git>

Setup

Setup instructions are contained in the file setup.sh and must be run only once. The script has been tested on macOS Big Sur and Ubuntu 20.04 LTS. To complete the setup, simply run bash setup.sh. Please, note that the installation of the R packages will prompt you to enter the your password via sudo.

If you have anaconda installed, ensure that the conda base environment is not active during setup.

Reproducible pipeline

To reproduce the pipeline, run bash repro.sh: text Usage: repro.sh [-h] [-v] -s all|phase1|phase2 -d test|full Available options: -h, --help Print this help and exit -v, --verbose Print script debug info -s, --stage Pipeline stage. Accepted values: all, phase1, phase2 -d, --dataset Dataset size. Accepted values: test, full

You can choose to reproduce the full pipeline by passing the argument -s|--stage all. Otherwise, you can reproduce individually the two phases of the experiment by passing instead the arguments phase1 or phase2. Also, to reduce the computational time, you can chose between running the script on the full dataset or on a random test subsample.

Notes

  1. Phase Two is quite time-consuming---it can take hours, in not days, depending on your box specs. For test purposes, you can supply the argument test to work with a very small, random subsample of the original dataset and keep the computational time within minutes.

  2. The script ph1_0-goldstandard_creation.sh is intentionally not part of the reproducible pipeline. It is meant to be executed only once, to create the anonymized gold standard in which email addresses have been replaced with hashed ids and all the sensitive content from emails (e.g., names, urls) have been scrubbed. This is intended to prevent others from tracking down the participants by searching for matching text into the public email archives of the Apache Software Foundation.

Owner

  • Name: Collaborative Development Group
  • Login: collab-uniba
  • Kind: organization
  • Email: info@peopleware.ai
  • Location: University of Bari, Italy

As a research group we address challenges that must be overcome in collaborative environments, even if distributed by time or distance

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Last synced: about 1 year ago

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  • Total issues: 0
  • Total pull requests: 19
  • Average time to close issues: N/A
  • Average time to close pull requests: 1 day
  • Total issue authors: 0
  • Total pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.05
  • Merged pull requests: 17
  • Bot issues: 0
  • Bot pull requests: 19
Past Year
  • Issues: 0
  • Pull requests: 5
  • Average time to close issues: N/A
  • Average time to close pull requests: 4 days
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 4
  • Bot issues: 0
  • Bot pull requests: 5
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