Tracing the Footsteps of Technical Debt in Microservice Architectures: A Preliminary Case Study

This repository is a companion page for the following publication:

Verdecchia, R., Maggi, K., Scommegna, L., Vicario, E. 2023. Tracing the Footsteps of Technical Debt in Microservice Architectures: A Preliminary Case Study. 1st International Workshop on Quality in Software Architecture (QUALIFIER)

It contains all the material required for replicating the study, including: repository mining script, mining raw data and data analysis script.

How to cite us

The scientific article describing design, execution, and main results of this study is available here.

If this study is helping your research, consider to cite it is as follows, thanks!

@article{verdecchia2023tracing,
  title={Tracing the Footsteps of Technical Debt in Microservices: A Preliminary Case Study},
  author={Verdecchia, Roberto and Maggi, Kevin and Scommegna, Leonardo and Vicario, Enrico},
  journal={International Workshop on Quality in Software Architecture (QUALIFIER)},
  publisher={Springer},
  year={2023}
}

Quick start

Here a documentation on how to use the replication material should be provided.

Requirements

• Python 3.10
• Docker (Docker Engine + Docker Compose)

Preliminary

• Clone the repo in the directory you want (we refer to it as $CLONE_DIR):

  git clone https://github.com/STLab-UniFI/QUALIFIER-2023-TD-microservices-rep-pkg $CLONE_DIR
  

• Move to src folder:

  cd $CLONE_DIR/src
  

Repository mining phase

• Move to mining folder:

  cd mining
  

• Install all the Python package required:

  pip install -r requirements.txt
  

• Run the script:

  python geoserver_analysis.py
  

  N.B. The script starts Docker containers so Docker Engine must be started and on Linux/macOS you could have to precede the commands with sudo if the user is not in the Docker group.

Data analysis phase

Repository Structure

This is the root directory of the repository. The directory is structured as follows:

QUALIFIER-2023-TD-microservices-rep-pkg
 .
 |
 |
 |--- src/                                   Source code used in the paper
 |      |
 |      |--- mining/                         Scripts for the repository mining phase
 |      |
 |      |--- analysis/                       Scripts for the data analysis phase
 |
 |--- data/                                  Data used in the paper 
 |      |
 |      |--- raw/                            Results from the repository mining phase
 |      |
 |      |--- final/                          Results from the data analysis phase
 |
 |--- Interview_supporting_slide_deck.pdf    Slide deck utilized for the qualitative interview

License

The source code is licensed under the MIT license, which you can find in the LICENSE file.

All graphical/text assets are licensed under the Creative Commons Attribution 4.0 (CC BY 4.0).