Peer code reviews involve students conducting a code review of a classmate's submission to a programming assignment. While peer code reviews have an established history of being used and studied in computing education, they have primarily been documented in introductory computing courses. This experience report describes how we implemented peer code reviews in an upper-division software engineering course that focuses on making modifications to large, existing code bases (i.e., brownfield development). We discuss the perceived learning benefits, perceived challenges, and agreement between peer and course staff reviews. Overall, students enjoyed being able to see different approaches to the programming task they had just submitted, but expressed concerns about feeling qualified to make effective peer code reviews due to their limited software engineering experience and the difficulty of assessing code design. We also find that students are capable of evaluating the functional correctness of their peer's submission, but struggle to give accurate assessments of their peer's design and code style. We conclude with recommendations specifically for instructors who wish to use peer code reviews in upper-division software engineering courses, such as using a structured template to scaffold the peer code reviews and allowing multiple opportunities to provide code reviews to improve students' self-efficacy.

Low-quality code can cost a company significant time and effort. As a result, code quality has been consistently studied in computing education research, especially in the context of CS1 students. However, less research has examined students' code quality while working on existing code bases (i.e., in tasks they are expected to do in industry). In this paper, we identify 1) common code quality defects introduced by upper-division students while contributing to an existing code base, 2) the severity, tool support, and language independence of those defects, and 3) programming experiences that may be associated with students' frequencies of defects, such as internship experience and use of Python (which was the language used in the programming tasks). In an upper division software engineering course, 48 students worked individually to 1) modify an existing feature and 2) implement a new feature in an open-source code base. Using an existing framework of code quality defects by Řechtáčková et al., we conducted a manual code review of all student submissions and found that students created defects related to Poor Design, Poor Documentation, Poor Formatting, and Unused Code at a high frequency. Students also seemed to copy-paste code from other files, which introduced defects related to Unused Code and Poor Design to their submission. Though our regression analysis did not reveal statistically significant predictors, students with prior internships, on average, introduced more code quality defects than those without any internship experience.