The ability of students to accurately rate the programming ability of their peers was investigated. Two studies were performed in the context of undergraduate Computer Science courses to measure how closely student peer ratings matched class grades given by course instructors. The results showed that peer ratings did correlate with instructor grades. Additional data was collected regarding how the students related to each other through previous projects and social network connections. These relations were treated as measures of familiarity. Networks of familiarity were created and clusters within these networks were identified to show which students were more familiar with each other. Analyzing these clusters showed that familiarity plays a role in the accuracy of the peer ratings. Students who were more familiar with each other generally provided more accurate ratings of their peers. Further testing is warranted to validate these results, since the data gathered was more sparse than anticipated at the beginning of the study. Also, further analysis of the effect of familiarity may yield more compelling results if different network clustering methods are applied.