As AI models continue to evolve, development teams need objective data to evaluate testing automation options. Our October 2025 benchmark study examines how GitHub Copilot with GPT-5 performs against Diffblue Cover across three production Java applications. The findings reveal important considerations for enterprises seeking to scale their testing efforts efficiently.
What You’ll Learn in This Report:
Testing three complex Java applications (Apache Tika, Halo, and Sentinel), we measured real-world performance across critical dimensions that matter to development teams. The results provide clear insights into the strengths and limitations of different AI-powered testing approaches.
This 12-page report includes:
- Detailed performance metrics across three production codebases
- Compilation success rates and mutation testing scores
- Time-to-value analysis for different testing approaches
- Recommendations for tool selection based on project requirements
Whether you’re evaluating testing solutions, building an AI-augmented development strategy, or simply staying informed about the latest in software automation, this research provides the data-driven insights you need to make confident decisions.
