Code Smells Prioritizer (CSP) tool

This is a tool for prioritizing code smells using developers' context. Note that this tool supports only class level code smells. Please refer to our publication for more details.

How to use

1. Prepare the input files: code smell file and impact analysis file (see Input File Format).
2. Use the following command to generate the result.
3. The result will be generated as Result.csv (see Output File Format).

Usage:

 python CSP.py code_smell_file_name impact_analysis_file_name [alpha=1] [cut_point=40] 

alpha = The combination ratio of CRI and Severity
cut_point = The maximum number of impact analysis results of each issue that are going to be considered
For the details, please refer to our publication.

Example:

python CSP.py Smells.csv IA.csv 1 40

Input File Format

Code smell file:

Smell ID	Severity	Class Name	Package Name	Smell Type
1	7	ClassA	com.package.ui	God
2	8	ClassB	com.package.model	Blob
.	.	.	.	.

Smell ID = A Unique ID of each smell
Severity = An integer representing the severity of each smell (e.g. 1-10)
Package Name = Package name of the class (in case there is folder name in front of it, the tool will automatically remove the folder name, e.g., src/java/com.package.ui → com.package.ui)

Example: Smells.csv

Impact analysis file:

Issue ID	Class Full Name	Score
1001	com.package.ui.ClassA	0.321
1001	com.package.model.ClassB	0.211
.	.	.

Please remove the header line of the file before using the tool (if any).

Example: IA.csv

Output File Format

Result file:

Smell ID	Ranking	CRI	Severity	Class Name	Package Name
70	1.0	3.21	2	com.package.ui	God
25	0.9	2.13	3	com.package.model	Blob
.	.	.	.	.	.

Ranking = A criterion used for prioritizing code smell generated by combining CRI and Severity.
CRI = Context Relevance Index
For the details on the calculation of Ranking and CRI, please refer to our publication.

Example: Result.csv

Publication

To be added