Common LGTM Issues and Solutions

1. LGTM Code Scans Failing

Code analysis fails to complete, preventing results from being generated.

Root Causes:

  • Incorrect LGTM configuration file.
  • Incompatible or missing build dependencies.
  • Repository access issues.

Solution:

Verify the lgtm.yml configuration:

"lgtm": {  "build": {    "command": "mvn clean install"  }}

Check build dependencies and update them:

npm install --legacy-peer-deps

Ensure the repository is accessible to LGTM:

Settings > Repository > Access Control > Allow LGTM

2. False Positives in LGTM Alerts

LGTM reports security or quality issues that are not actual problems.

Root Causes:

  • Overly strict analysis rules.
  • Misclassification of certain coding patterns.
  • LGTM database not updated with recent code changes.

Solution:

Suppress false positives using lgtm.ignore:

// lgtm [ignore: unused-variable]const temp = "This variable is intentional.";

Adjust severity levels in LGTM settings:

Analysis > Custom Rules > Adjust Threshold

Force a re-scan to update analysis results.

3. LGTM Not Integrating with GitHub/GitLab

Code quality analysis does not trigger automatically after commits.

Root Causes:

  • LGTM webhook not properly configured.
  • Repository permissions blocking LGTM.
  • Misconfigured CI/CD pipeline preventing execution.

Solution:

Verify LGTM webhook settings in GitHub/GitLab:

Repository > Settings > Webhooks > LGTM Hook

Ensure correct repository access permissions:

Settings > Repository Access > Grant LGTM Read & Write

Check CI/CD pipeline logs for execution errors.

4. LGTM Analysis Running Slowly

Code analysis takes too long to complete, delaying development workflows.

Root Causes:

  • Large codebase increasing analysis time.
  • Complex queries slowing down the analysis engine.
  • Insufficient computing resources for the LGTM instance.

Solution:

Limit analysis scope to critical directories:

"queries": {  "exclude": ["test/**", "docs/**"]}

Optimize database queries in custom LGTM rules.

Upgrade LGTM service tier for better processing power.

5. Incorrect Alert Classifications

LGTM mislabels certain issues as high-risk or low-priority incorrectly.

Root Causes:

  • Inconsistent analysis thresholds in configuration.
  • Custom rules not properly defined.
  • Outdated LGTM query database.

Solution:

Manually reclassify incorrect alerts:

Analysis > Alerts > Change Severity

Update LGTM query database:

Settings > Analysis Engine > Update Queries

Define precise rules for custom code patterns.

Best Practices for LGTM Code Analysis

  • Regularly update lgtm.yml to reflect project changes.
  • Suppress false positives only when necessary.
  • Optimize custom queries for faster analysis.
  • Ensure webhook integration with GitHub/GitLab is functioning.
  • Monitor LGTM dashboards for potential configuration errors.

Conclusion

By troubleshooting scanning failures, false positives, integration issues, slow performance, and alert classification errors, developers can effectively use LGTM for maintaining high code quality. Implementing best practices ensures efficient and accurate static analysis across projects.

FAQs

1. Why is my LGTM analysis failing?

Check the lgtm.yml file, ensure dependencies are installed, and verify repository access.

2. How do I suppress false positives in LGTM?

Use lgtm.ignore comments or adjust severity levels in the LGTM dashboard.

3. Why is LGTM not integrating with my repository?

Verify webhook settings, check repository permissions, and ensure CI/CD triggers are configured correctly.

4. How can I speed up LGTM analysis?

Limit analysis scope, optimize database queries, and upgrade computing resources.

5. What should I do if LGTM classifies alerts incorrectly?

Manually reclassify alerts, update LGTM query databases, and define precise custom rules.