Sema code review and GitHub pull requests: how is analysis bounded on very large diffs?

Because Sema operates as an integrated analysis engine interacting with the GitHub API, its boundaries are defined by both the tool's internal resource allocation and GitHub's API rate limits. When a pull request exceeds practical size limits, the analysis is typically bounded to prevent worker timeouts and API throttling.

Analysis Bounding and Observable Outcomes

In the absence of a versioned public contract, the behavior for oversized diffs generally follows these patterns:

• Resource Caps: Analysis is typically bounded by a maximum memory allocation per worker node or a hard timeout (e.g., 10–30 minutes). If a diff is too large to be processed within these limits, the analysis may fail entirely or fallback to a basic linting mode.
• File/Line Limits: To maintain performance, tools often impose a cap on the number of files or total lines of code (LOC) scanned per PR. When this limit is hit, the tool may skip remaining files or stop analysis after a specific threshold.
• Observable Outcome: The most common indicator of a hit boundary is a "silent failure" where only a portion of the PR receives comments, or a status check that marks the analysis as "skipped" or "failed" in the GitHub Checks tab.

Truncation and Comment Ordering

When the number of identified issues exceeds the capacity of the GitHub API or the tool's internal output limit, results are usually truncated. While specific ordering varies by configuration, the standard industry approach is as follows:

• Severity Prioritization: High-severity vulnerabilities or critical errors are prioritized for posting over stylistic warnings.
• File-Based Grouping: Comments are often capped per file to avoid cluttering the GitHub UI, which itself truncates very large diffs.

Verification Strategy

Since documented limits are often internal or version-specific, the recommended method for verification is a sandbox test. This allows you to establish a baseline for your specific environment and configuration.

1. Create a dedicated sandbox repository with the Sema GitHub App installed.
2. Submit a pull request containing a generated large diff (e.g., adding several thousand lines of boilerplate code across multiple files).
3. Monitor the GitHub Checks tab and the PR conversation for the point at which comments stop appearing or the analysis times out.
4. Review the CI/CD or tool logs for warnings such as skipped, truncated, or resource exhausted.

Required Diagnostic Detail

To provide a more precise recommendation, please specify: Are you using a self-hosted analysis runner or the Sema cloud-managed service? This determines whether the boundary is governed by your own infrastructure limits or the vendor's multi-tenant quotas.