Dataset of the Paper "Understanding Bugs of Learning Management Systems: An Exploratory Study on Moodle and Sakai"

The datasets collected from JIRA and GitHub are used for an empirical study and data analysis of bug classification issues in learning management systems (Moodle and Sakai). A brief description of each document in the dataset is provided below:

1. "LMS_bugs_data.sql" contains bug data items collected from JIRA for LMS (Moodle and Sakai), specifically including: BugID (D1), BugKey (D2), BugSummary (D3), BugStatus (D4), BugResolution (D5), BugDescription (D6), BugCreateAt (D7), BugCloseAt (D8), and BugComments (D9). Additional data items (e.g., fixversions, priority) are provided to support further research.

2. "LMS_commits_data.sql" contains the commits corresponding to bug fixes in LMS (Moodle and Sakai) from GitHub, specifically including: CommitSha (D10), CommittedDate (D11), CommitMessage (D12), CommitTotal (D13), Changefiles (D14), Files (D15), and BugKey(D2). Other data items (e.g., commitauthor, additions)  are provided for supporting the research.

3. OT, LOCM, NOFM, Entropy, NODP, NOC (D16-D21) require the above data for calculation.

4. "LMS_Moodle_Bug_Classification_Results_7898.xlsx" contains the bug classification results for Moodle, including: BugID, BugKey, Summary, ClusterId, GPT-4 Label Topic, BugType, and the mapping between BugType and ClusterId.

5. "LMS_Sakai_Bug_Classification_Results_6089.xlsx" contains the bug classification results for Sakai, including: BugID, BugKey, Summary, ClusterId, GPT-4 Label Topic, BugType, and the mapping between BugType and ClusterId.