Concerns identified in code review: A fine-grained, faceted classification

Context: Code review is a valuable software process that helps software practitioners to identify a variety of defects in code. Even though many code review tools and static analysis tools used to improve the efficiency of the process exist, code review is still costly. Objective: Understanding the types of defects that code reviews help to identify could reveal other means of cost improvement. Thus, our goal was to identify defect types detected in real-world code reviews, and the extent to which code review can be benefited from defect detection tools. Method: To this end, we classified 417 comments from code reviews of 7 OSS Java projects using thematic analysis. Results: We identified 116 defect types that we grouped into 15 groups to create a defect classification. Additionally, 38% of these defects could be automatically detected accurately. Conclusion: We learnt that even though many capable defect detection tools are available today, a substantial amount of defects that can be detected automatically, reach code review. Also, we identified several code review cost reduction opportunities.