Collected Data
NOTE: due to this spreadsheet being created in Google Drive, containing formulas that both do not exist and are not formatted properly for Microsoft, it must be uploaded to a folder in Google Drive to avoid errors with formulas.
Co-occurrences of Code Smells: A Systematic Mapping Study
In this systematic mapping study, we reviewed papers on code smell co-occurrences to collect and summarize data on the subject. We investigated the following research questions:
RQ1) What are the different code smells that studies look at?
RQ2) What are the measurements that researchers use to identify code smells?
RQ3) What are the tools used to identify code smells?
RQ4) What are the algorithms and techniques used to identify code smells?
RQ5) What is the comparison between the results from different studies?
Below is a Python script that can be used to generate a network graph of the code smell co-occurrences from the studies we reviewed (NOTE: be sure to update the line of code that starts with codeSmellCooccurrencesArray with the value of value of the cell from the column "Multiple Co-occurrences as One Python String Array" in the tab "RQ5" of the Google Spreadsheet "Systematic Mapping Data"):
Figures
Figure 1: Network Graph of All Code Smell Co-occurrences
Figure 2: Network Graph of Code Smell Co-occurrences Upper-Left Section
Figure 3: Network Graph of Code Smell Co-occurrences Lower-Left Section
Figure 4: Network Graph of Code Smell Co-occurrences Bottom Section
Figure 5: Network Graph of Code Smell Co-occurrences Right Section