Replication Package of the study "Exploring the Notion of Risk in Reviewer Recommendation"

Description
This is a Dockerized version of the repository https://github.com/software-rebels/RAR_Recommender . The package is developed to ease the replication of our study for researchers and practitioners.

This package contains the necessary information to replicate the study "Exploring the Notion of Risk in Reviewer Recommendation." This code extends the RelationalGit package (https://github.com/CESEL/RelationalGit) from the study of E. Mirsaeedi and P. C. Rigby [1]. It adds some functionality needed to incorporate the concept of the fix-inducing likelihood of a project.

In addition to our dataset, this repository also has the supporting materials for our study. The supporting materials are in the "ICSME_online_materials_ICSME.pdf" and contain the following items:

Table 1 contains the detail of the dataset and some related statistics for each studied project. 
Table 2 shows the risk measures used in our defect prediction model. We use Commit Guru Tool to extract the data from the GitHub repositories and then use this data to train our defect prediction model.
Figure 1 illustrates the distribution of predicted defect probability of different projects. This distribution shows how the defect probability of different periods is similar to the adjacent periods. 

Replication Steps:

Read Requirements.md and ensure the necessary software/hardware requirements.
Read Install.md and install the necessary packages to run the containers.
Follow the steps in ReadMe.md to reproduce the results of our study.

References:

[1] E. Mirsaeedi and P. C. Rigby, 'Mitigating turnover with code review recommendation: Balancing expertise, workload, and knowledge distribution', στο Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering, 2020.