WiFLF-main

Source code and all the datasets used in the paper "WIFLF: An Approach Independing The Target Project for Cross-Project Defect Prediction".

There are the following three main subfolders in WiFLF-main

Datasets -- This folder includes two subfolders (AEEEM,PROMISE1, PROMISE2 and Relink), each subfolder contains the corresponding datasets used in the paper. Each dataset is a csv file.
Datasets-inOne -- All the datasets are put in one folder.
results -- the results of RQ1, RQ2, RQ3 & Q4.
WIFLF -- This folder includes the source code of WIFLF and the baselines.

Step1: Download WiFLF-main;
Step2: Open Pycharm and add the path of WiFLF-main and its subfolders;
Step3: Configure your Pycharm and ensure the Python can be called to implement the funcitions. Python supports version 3.6.5;
Step4: Visit the WiFLF folder and open the script main.py for WIFLF with your Python; (RQ1.py for the baselines of RQ1; RQ2.py for the baselines of RQ2; RQ3.py or RQ3； RQ4.py for RQ4) ;
Step5: Click the run button in the menu of Pycharm Editor to run main.py;

If you have any problem about our code, feel free to contact