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:
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For every studied project, we provide the associated datasets including the LOC and code churn values for all smelly and non smelly files.
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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
- extract all files LOC, code churn, changes types, commits, and identify all bug-inducing commits related to every file.
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The
OccAllApp.csv
contain all types of code smells found in each smelly file of the 400+ studied releases.