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Software sustainability of global impact models (Dataset and analysis script) - MaRDI portal

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Software sustainability of global impact models (Dataset and analysis script)

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DOI10.5281/zenodo.13819603Zenodo13819603MaRDI QIDQ6697866

Dataset published at Zenodo repository.

Author name not available (Why is that?)

Publication date: 20 September 2024

Copyright license: No records found.



Description

slocount.py: This script calculates the number of comment lines, total lines of code (TLOC) and source lines of code (SLOC). It uses a code line counter developed by Ben Boyter, which must be installed (https://github.com/boyter/scc.). The source code links to the global impact models (GIMs) can be found in the 'ISIMIP_models.xlsx' file. active_dev.py: This script plots the number of active developers for each GIM across 10 sectors. It utilizes data from the 'active_dev.csv' file, which lists the GIMs and their respective number of developers. cocomo.py: This script estimates the effort required for software development using the methodology proposed by Sachan et al. 2016 (https://doi.org/10.1016/j.procs.2016.06.107). It also generates plots for these estimates. comment_density_modularity.py: This script calculates the comment density and evaluates the modularity of the modules. It also produces plots for these metrics. code_standard.py: This script uses Pylint (https://pylint.readthedocs.io/en/latest/user_guide/usage/output.html) to check if the source code, either in part or in its entirety, adheres to the PEP8 coding standard. It also generates lint scores for the source code. line_count.zip: This file contains the results of counting the number of comment lines, TLOC and SLOC for each GIM. lint_score.zip: This file contains the results of running pylint on GIMs that include Python in their source code. Results also include lint score per GIM






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