The submitted artifacts constitute the replication package of the article “A Study on the Pythonic Functional Constructs’ Understandability” accepted in the research track of ICSE 2024.

Availability: - Paper’s preprint: https://mdipenta.github.io/files/ICSE24_funcExperiment.pdf - Artifacts: https://doi.org/10.5281/zenodo.8191782 - License: GPL 3.0

The artifacts feature: - The material used in the experiments (the web forms, all code examples used according to the assignment reported in Table 1 of the paper); - The raw quantitative results; - The datasets and scripts used to produce figures and tables reported in the paper; - The spreadsheet used to perform the study’s qualitative analysis.

We claim both the available and reusable badges for our artifacts.

There are different alternatives for running the (R) script that produces the results: 1) If one does not want to install R with all the required libraries, through a Docker image, by simply running a shell script 2) Using own R environment installation (it requires the installation of the needed libraries) 3) Using a Jupyter Notebook, by running a customized version of Jupyter from a Docker image 4) Using own Jupyter Notebook installation (it requires the installation of Jupyter and its R kernel) See https://irkernel.github.io/installation/

(Note: typically option 1 is the simplest one)

Requirements: - Possibly, a Unix machine (it has also been tested on Windows 11 with a Power Shell) - A Docker engine (for options 1 and 3) - R statistical environment (for option 2) - Jupyter with R kernel (for option 4)