Code review is a crucial step in ensuring the quality and maintainability of software systems. However, this process can be time-consuming and resource-intensive, especially in large-scale projects where a significant number of code changes are submitted every day. Fortunately, not all code changes require human reviews, as some may only contain syntactic modifications that do not alter the behavior of the system, such as format changes, variable / function renamings, and constant extractions.

In this paper, we propose a multi-language automated code approver — Last Diff Analyzer for Go and Java, which is able to detect if a reviewable incremental unit of code change (diff) contains only changes that do not modify system behavior. It is built on top of a novel multi-language static analysis framework that unifies common features of multiple languages while keeping unique language constructs separate. This makes it easy to extend to other languages such as TypeScript, Kotlin, Swift, and others. Besides skipping unnecessary code reviews, Last Diff Analyzer could be further applied to skip certain resource-intensive end-to-end (E2E) tests for auto-approved diffs for significant reduction of resource usage. We have deployed the analyzer at scale within Uber, and data collected in production shows that approximately 15% of analyzed diffs are auto-approved weekly for code reviews. Furthermore, 13.5% reduction in server node usage dedicated to E2E tests (measured by number of executed E2E tests) is observed as a result of skipping E2E tests, compared to the node usage if Last Diff Analyzer were not enabled.