Review cycles
What is review cycles?
Review cycles is a metric used in software engineering to measure the efficiency and effectiveness of the code review process. It tracks the number of times a pull request (PR) is reviewed and subsequently updated before it is finally merged into the main codebase. To calculate review cycles, one counts each iteration of the cycle starting from the initial code review, followed by any changes made to the code (commits or merges), and ending when the code is accepted and merged. Each full loop from review to code modification and back to review counts as one review cycle. The metric essentially quantifies the interaction between the developers who propose changes and their peers who review those changes.
Why is review cycles important?
Quality Assurance. Review cycles are critical for maintaining high code quality. Each cycle provides an opportunity for peers to identify potential issues and improvements, ensuring that only well-vetted and refined code makes it to production. This iterative scrutiny helps in minimizing bugs and enhances the overall stability and security of the software.
Collaboration and Knowledge Sharing. Through multiple review cycles, team members interact frequently, which promotes better collaboration and knowledge sharing. This process not only helps in spreading domain knowledge and coding practices among team members but also fosters a culture of collective code ownership and continuous learning.
Predictability in Releases. Tracking the number of review cycles can help project managers estimate the time and effort required for future changes to reach production readiness. A higher number of cycles might indicate complex features or issues with code quality, while a lower number suggests smoother development processes. This metric thus aids in predicting release schedules more accurately and planning iterations effectively.
What are the limitations of review cycles?
Not a Standalone Metric. Review cycles should not be used as a standalone measure of code or developer performance. A high number of cycles might indicate thoroughness and diligence in refinement, or it could point to inefficiencies and problems in the coding or reviewing process. Conversely, fewer cycles might imply efficiency or, conversely, a lack of thorough review.
Context Dependency. The effectiveness and implications of review cycles vary widely depending on the team’s size, the complexity of the project, and organizational standards. What constitutes a "normal" range for review cycles in one context may be considered too high or too low in another, making it difficult to benchmark without additional contextual data.
Potential for Misuse. If not contextualized and communicated properly, there's a risk that teams might game the metric by minimizing their review cycles artificially, which can compromise code quality. It is crucial that teams maintain a balance and understand that the goal is to improve the code and collaboration, not just to reduce the number of cycles.
Metrics related to review cycles
Code churn. Code churn, which measures how much code is added, removed, or modified over a period, is closely related to review cycles. Frequent changes in a pull request often lead to increased review cycles. Understanding code churn can help teams manage the complexity and frequency of changes, thus optimizing review cycles.
Review time. Review time measures the duration between a pull request being submitted and its final approval. This metric is directly impacted by the number of review cycles; more cycles typically lead to a longer review time. By monitoring both metrics, teams can better understand their code review processes and look for ways to make them more efficient.
Defect removal efficiency. This metric quantifies the effectiveness of the development process in identifying and removing defects before software is released. Higher defect removal efficiency often correlates with more thorough review cycles, as each cycle can help in identifying more issues prior to release. Tracking this alongside review cycles can provide insights into the quality assurance strength of a team’s review process.