## 4 Results
### Descriptive Statistics  
Before we explore the research questions, we will explore the summary statistics of our resulting data. We were able to gather the initial commit (init omit) of 36,407 bugs. However, because some bugs were classified under multiple bug types, our total dataset consists of 47,914 members. The average time to fix a bug (fix time) was 7140.04 Commit Cycles while the median fix time was 304.13. These numbers changed substantially when looking into different groupings, which we will investigate in the rest of this section. The summary statistics for these groupings are shown in Table 1.  
To find a time factor, we aimed to find a correlation between the amount of Commit Cycles taken to fix a bug and which hour the programmer introduced the bug. Previous research compared the time it takes to repair a bug to understand the bug-fixing process with the bug's opening date [10]. Related research also considered the bug-fix times [11; 32; 33; 34], but, to our knowledge, none have aimed to determine a correlation between the time it takes to fix a bug, and the hour, or day, the bug was introduced. Thus, we sought to find a statistical difference between which day of the week the programmer introduced the buggy commit and the commit cycle. Results from our custom-made algorithm were extracted and categorized into the days of the week and the number of bug-introducing commits introduced in its corresponding day. As illustrated in Figure 1, the initial commits, or buggy commits, were published during a workday, Monday through Friday. The maximum number of commits occurred on Thursday; while, Saturday and Sunday had the minimum number of commits out of the entire week. Further analysis focused on the hour the programmer introduced the fix commit and the buggy commit. The statistical relationship between the number of bug-introducing commits and fix commits introduced by the programmer each hour was analyzed. Similar to our analysis in the number of commits introduced on each day of the week, we categorized the number of commits made in each hour of the day, in the commits corresponding to a time zone in the 24-h format, as shown in Figure 2. This means that the bug-introducing and fixed commit dates and times were not modified since we wanted to analyze the time from the programmer's perspective. As shown in Figure 2, programmers published bug-introducing commits between 10 am and 6 pm, during typical working hours. The maximum number of bug-introducing commits occurred at 4 pm; meanwhile, the minimum \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Group** & **Count** & **Mean** & **Standard Deviation** & **Median** \\ \hline Research Questions (A) & & & & \\ Initial Buggy Commit on Weekday & 32,276 & 7611.25 & 26,156.3 & 330.392661 \\ Initial Buggy Commit on Weekend & 4131 & 3458.431 & 13,390.04 & 160.079725 \\ Initial Buggy Commit Work Hours & 22,800 & 6396.583 & 21,265.25 & 287.917833 \\ Initial Buggy Commit not Work Hours & 13,607 & 8385.787 & 30,359.9 & 329.574957 \\ Research Questions (B) & & & & \\ Same Author Bug Fix & 18,201 & 2489.816 & 9565.716 & 72.961409 \\ Different Author Bug Fix & 18,206 & 11,788.99 & 33,501.36 & 987.887367 \\ Same User is Author Committer & 31,359 & 7651.337 & 26,528.25 & 280.848463 \\ Different User is Author Committer & 5048 & 3963.789 & 12,252.026 & 431.233376 \\ More than 25 Committers & 34,688 & 7485.949 & 25,635.98 & 344.932187 \\ Less than 25 Committers & 1719 & 159.916 & 434.1329 & 21.776339 \\ More than 40 Authors & 34,534 & 7504.619 & 25,690.44 & 343.853362 \\ Less than 40 Authors & 1873 & 418.0325 & 1404.526 & 25.125066 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary statistics per research question. Figure 1: Buggy commits made per day of the week. number of bug-introducing commits were committed to the repository at 6 am. Figure 2 further demonstrated that most of the fix commits were published between 10 am and 6 pm.