This repository contains the data used in and generated by our data analysis and literature search to ensure reproducibility, repeatability, and transparency.
publication:
Marvin Muñoz Barón, Marvin Wyrich, and Stefan Wagner. 2020. An Empirical Validation of Cognitive Complexity as a Measure of Source Code Understandability. In ESEM ’20: ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) (ESEM ’20), October 8–9, 2020, Bari, Italy. ACM, New York, NY, USA, 12 pages. https://doi.org/10.1145/3382494.3410636
The data-analysis folder contains all files that relate to the data analysis part of our work.
- The dataset.xlsx file contains all the data we used to conduct our meta-analysis including the values for Cognitive Complexity and proxy variables for understandability of all code snippets.
- The data-analysis.R script contains the code written in R that was used to calculate the correlations, to test for the normality of the data and to generate the forest plots for our meta-analysis.
- The dataset-descriptions.md document provides summaries of each of the studies and their corresponding datasets.
Please note that we could not publish the code snippets in this repo due to missing licenses. If you need the code snippets for your work and do not want to extract them yourself from the supplemental materials of the listed studies, you are welcome to contact us.
The systematic-literature-search folder contains all files that relate to the systematic literature search part of our work.
- The literature-search-overview.md document provides detailed instructions for each step and technical information about the tools that were used.
- The subfolders labeled with
1.1_...to6_...correspond to the files generated by the corresponding step as described in the overview, such as a list of papers remaining after each step and raw export files from the search engines.