Background: Code reviewing is an essential part of software development to ensure software quality. However, the abundance of review tasks and the intensity of the workload for reviewers negatively impact the quality of the reviews and result in short and ineffective descriptions. The short review comments are written in a natural language and are often unactionable, which needs further interaction between the reviewer and the developer. The problem becomes more significant in dynamic teams and in the case of new team members who are less familiar with their reviewers and perspectives.

Aims: We are proposing the Example Driven Review Explanation (EDRE) method to facilitate the code review process by adding additional explanations through examples. EDRE recommends similar code reviews as examples to further explain a review and help a developer to understand the received reviews with less communication overhead.

Method: Through an empirical study in an industrial setting and by analyzing 3,722 code reviews across three open-source projects, we compared five methods of data retrieval, text classification, and text recommendation.

Results: EDRE using TF-IDF word embedding along with an SVM classifier can provide practical examples for each code review with 92% F-score and 90% Accuracy. Conclusions: The example-based explanation is an established method for assisting experts in explaining decisions. EDRE was developed based on the same philosophy and can accurately provide a set of context-specific examples to facilitate the code review process in software teams.