Automated Code Review Tools for Developers in 2021

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Why Use Automated Code Review Tools?

CodeBeat

  • Provides an integrated dashboard with project reviews
  • Issues grouped into categories like complexity, code issues, and duplication
  • Provides E-Mail updates for project and pull request quality continuously
  • Provides immediate feedback to improve the codebase quality through “quick wins”
  • Easy to integrate and use with minimal setup required
  • Lack of security analysis.
  • Lack of support for open-source tools and linters.

DeepSource

  • Single-File Configuration for automated code analysis
  • Integrates with continuous integration pipelines like Travis CI and Circle CI
  • Supports code formatters like black, rubocop, and gofmt
  • Provides auto-fix for common issues across the codebase
  • Provides analysis for every issue and pull request
  • Lack of support for PHP, C++, and Rust
  • Lack of support for Azure DevOps

CodeClimate

  • Easy installation with automated Git updates.
  • Identifies hotspots in the codebase to identify portions that need a refactor.
  • Provides a security dashboard to identify application vulnerabilities.
  • Provides an API to be used locally for automated code reviews.
  • Provides alerts and instance notifications over Mail and RSS feeds.
  • Lack of issue description and search/filtering.
  • Lack of customization capabilities and high pricing.

Codacy

  • Automated code reviews with minimal installation
  • Integration with various services including GitHub, GitLab, GitHub Actions, CircleCI
  • Help define particular goals for the Project and provides a recommendation to fulfill them
  • Analyzes pull requests and commit individually
  • Only new issues are taken into account to prevent noise and duplication
  • Lack of issue search apart from a few filters
  • Lacks support for exporting code patterns

Veracode

  • Easy to configure and quick to use.
  • Provides binary scanning to have less false positives in the code.
  • Pin-points to real vulnerabilities in the code and recommends solutions.
  • Intuitive and friendly User-Interface with custom dashboards
  • Lack of customization for analysis rules
  • Lack of a well-defined user experience

Conclusion

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