## 2 Background
In a study aiming to predict whether a user would join a project in the future, the metrics used included a developer's GitHub age (i.e., when their account was opened), the number of projects that they had joined, the programming languages of their commits, how many times a project was starred, the number of developers that joined a project, and the number of commits made to a project [25]. In another study that explored the factors that led a user to join a project, the metrics used included a developer's social connections, programming with a common language, and contributions to the same projects or files [26]. [PERSON] et al. designed a neural network-based recommendation system that used metrics such as working at the same company, previous collaboration with the project owner, and different time-related features of a project [27]. [PERSON] et al. relied on basic user activity to develop a project recommendation model using GitHub data. Specifically, when rating a project for a developer, they used \"like-star-create\" activities related to projects [5]. To sum up, some developer metrics that were noted as considerable in their papers are given in Table 1. In this table, we have also presented the fields of the metrics (the related feature), their definitions, and the target challenge, along with the reference studies. These metrics have been used to address various challenges in OSS development, among them project characterization, reviewer assignment for issues or PRs, and project recommendation are prominent ones. Generally, researchers have aimed to use these metrics to characterize developers by analyzing their activities in order to solve a problem [28]. Thus, developer metrics become crucial factors for solving these challenges. In this study, we offer a number developer metrics that can be used for a variety of challenges. \begin{table}
\begin{tabular}{c l l l l} \hline \hline  & **Metric Name** & **Definition** & **Target Challenge** & **Ref** \\ \hline \multirow{6}{*}{**GeoL**} & Maintenance Type & The type of issue that related with (feature, bug, etc.) & Finding issue resolution time factors & [29] \\  & A\_D\_issue\_rep\_assi & The total number of issues that assigned to specific developers & Understanding issue closure rates & [30] \\  & ContainsFix & Is the pull request whether solve an issue? & Pull request prioritization & [15] \\  & Owned\_issues & The number of issues which is opened by the project’s owner & Prediction of joining a repository & [25] \\ \hline \multirow{6}{*}{**GeoL**} & D\_languages & The committed programming languages of a developer & [25] \\  & Contibutors\_SLOC & The number of contributors per 1K code lines & Exploring of reliability metrics & [18] \\  & TotalLoc & The number of lines in the last commit & Defect prediction with developer experience & [6] \\  & ExpLoc & The code line experience of a developer & [6] \\  & ExpCom & The experience of a developer on a committed file & [6] \\  & NumoffFile & The number of modified file in the last & [6] \\  & Past Experience & The number of files committed the past & Finding factors of joining & [26] \\  & & same-language. & a project & [3] \\  & Readme tf\_idf & The tf-idf values of ReadMe and code files of project & Project recommendation & [5] \\ \hline \multirow{6}{*}{**GeoL**} & NumCommits & The number of commit in a PR & Automatic assignment of & [3] \\  & AcceptanceRate & The acceptance rates of PRs on a project & [3] \\  & TotalLines & The number of changed lines in a PR & [3] \\  & Age & Time between opening and closing a PR & Pull request prioritization & [15] \\  & FileLocation & The directory of files in a PR & Automatic code-reviewer & [12] \\  & DecisionTime & PR decision time & Assignment & [16] \\  & Files\_changes & The number of changed files (some vs & Understanding the factors & [31] \\  & Comment Network & The network of pull request comments & Discovering factors of the PR process & [32] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Used metrics samples in the literature with GitHub data.