Replication Package for the Paper: "Code Smells Detection via Code Review: An Empirical Study"

This repository contains the data and results from the paper "Code Smells Detection via Code Review: An Empirical Study" submitted to ESEM 2020. 1. data folder The data folder contains the retrieved 269 reviews that discuss code smells. Each review includes four parts: Code Change URL, Code Smell Term, Code Smell Discussion, and Source Code URL. 2. scripts floder The scripts folder contains the Python script that was used to search for code smell terms and the list of code smell terms. smell-term/general_smell_terms.txt contains general code smell terms, such as "code smell". smell-term/specific_smell_terms.txt contains specific code smell terms, such as "dead code". smell-term/misspelling_terms_of_smell.txt contains the misspelling terms of 'smell', such as "ssell". get_changes.py is used for getting code changes from OpenStack. get_comments.py is used for getting review comments for each code change. smell_search.py is used for searching review comments that contain code smell terms. 3. project folder The project folder contains the MAXQDA project files. The files can be opened by MAXQDA 12 or higher versions, which are available at https://www.maxqda.com/ for download. You may also use the free 14-day trial version of MAXQDA 2018, which is available at https://www.maxqda.com/trial for download. Data Labeling & Encoding for RQ2.mx12 is the results of data labeling and encoding for RQ2, which were analyzed by the MAXQDA tool. Data Labeling & Encoding for RQ3.mx12 is the results of data labeling and encoding for RQ3, which were analyzed by the MAXQDA tool