CSC/ECE 517 Fall 2017/E1783 Convolutional data extraction from Github

GOAL:

A feature that integrate Github metrics into Expertiza to help instructors grade the projects by providing more information of the workload of individuals and could do early detection on failing projects based on groups’ working pattern. This wiki page documents the changes made as a part of E1783 which allows users with instructor to view Github metrics for a students' submitted assignment.

Introduction

Expertiza is a web application where students can submit and peer-review learning objects such as assignments, articles, code, web sites, etc. A feature that integrates Github metrics into 'Expertiza'- an Open source project in order to help instructors grade the projects by providing more information of the workload of individuals and could do early detection on failing projects based on groups’ working pattern. By convolutional data, here we refer to the fields of the dataset which cannot be extracted directly, such as the working pattern, which is the amount of commits/code/files the pull request added/modified/deleted on each day in the whole project period. The project period is a range of days that can be tracked on Expertiza.

For Metrics we have considered following :

o Number of commits everyday throughout the project’ s period o Number of files changed everyday throughout the project’ s period o Lines of code changed everyday throughout the project’ s period