Change-Patterns-Mapping

Code for the TSE article: 'Change-Patterns Mapping: A Boosting Way for Change Impact Analysis'

Author: Yuan Huang, Jinyu Jiang, Xiapu Luo, Xiangping Chen, Member, IEEE, Zibin Zheng, Senior Member, IEEE, Nan Jia, and Gang Huang Senior Member, IEEE

Overview

If you try to reproduce the same experiment results in this paper, you should follow the following steps:

STEP 1: Prepare data (dataset and testdata)

STEP 2: Generate coreclass of each commit

STEP 3: Generate coupling relationship of each commit

STEP 4: Generate corpus of each commit

STEP 5: On the testdata, use JRipples, Rose, Impactminer to generate the original result

STEP 6: Run Impactanalysis code to boost the result.

STEP 1

Sample dataset can be found at ./dataset, these files are used to store change-patterns which may later be used to boost the results.

Sample testdata can be found at ./testdata, these files are used to do experiments.

Notice: You'd better use the same file structure to store data if you want to do this experiment with ease. Otherwise, you should change the code in order to adapt to your file structure.

STEP 2

See ./coreclass_generation_project for details

STEP 3

See ./CouplingRel_generation_project for details

STEP 4

See ./Corpus_generation_project for details

STEP 5

The output of these tools should organize as follow:

This file include orginal sorted(according to their probability of being impacted) predicted impacted classes.

STEP 6

See ./ImpactAnalysis_project for details

Xstar9 / Change-Patterns-Mapping