This is a replication package of the paper titled "A Longitudinal Exploratory Study on Code Smells in Server Side Web Applications"

In this package you will find:

1. For every studied project, we provide the associated datasets including the LOC and code churn values for all smelly and non smelly files.

2. We provide in the folder Script, the scripts we used to:

   • extract all files LOC, code churn, changes types, commits, and identify all bug-inducing commits related to every file. FindingFault-Inducing-CommitsAndFault-Fixing-Comits.py
   • the script to get all issues state and ID FindingIssuesStateAndID.java.
   • the apriori algorithm implementation AprioriAlgorithm.py
   • the code smells occurrence frequency CodeSmellsOccurrenceFrequency.py

3. The OccAllApp.csv contain all types of code smells found in each smelly file of the 400+ studied releases.

Please, use the following bibtex entry:

@article{bessghaier2021longitudinal,
  title={A longitudinal exploratory study on code smells in server side web applications},
  author={Bessghaier, Narjes and Ouni, Ali and Mkaouer, Mohamed Wiem},
  journal={Software Quality Journal},
  volume={29},
  pages={901--941},
  year={2021},
  publisher={Springer}
}