Why Engineering Leaders Choose AI Agents Over AI Assistants
Research: Diffblue Cover vs. GitHub Copilot - Evaluating AI for Java Unit Testing at Scale
Diffblue Cover’s autonomous AI agent delivers a 26x increase in unit test productivity compared to GitHub Copilot – find out how in our report.
AI-assisted coding went mainstream in 2024. But can it meaningfully scale enterprise testing?
We investigated by comparing GitHub Copilot to Diffblue Cover, an AI agent built for Java unit testing.
What’s the difference?
Assistants like GitHub Copilot require ongoing developer input and oversight.
Autonomous agents like Diffblue Cover operate independently - removing developer burden to a large extent.
The Strategic Difference: AI Assistant vs. Autonomous AI Agent
AI Assistants (GitHub Copilot) Require Continuous Developer Interaction
Developers must prompt the AI, evaluate test suggestions, and fix errors manually.
Every test requires oversight; increasing cognitive load and reducing efficiency
The assistant-enhanced developer still spends significant time on test writing & debugging.
AI Agents (Diffblue Cover) Operate Without Developer Supervision
Autonomously writes, runs, and maintains test suites - with minimal developer intervention.
100% unattended execution. Developers don’t need to supervise the process.
Fully integrated into CI pipelines, ensuring regression tests stay up to date.
GitHub Copilot helps engineers write tests. Diffblue Cover ensures tests are written – without engineers having to do it.
How Diffblue Cover Outperforms GitHub Copilot in Real-World Testing
Within 260 minutes:
- Diffblue Cover autonomously reached 53% coverage – completely unattended.
- The Copilot-enhanced developer achieved 15% coverage – but required full developer engagement.
GitHub Copilot requires developers to stop feature work to focus on test creation. Diffblue Cover runs in parallel, allowing you to hit your code coverage targets faster and keep shipping.
The Diffblue Cover Impact: Enterprise-Scale AI Test Generation
Engineering teams at global enterprises use Diffblue Cover to:
Automate test creation at scale - eliminating manual unit testing efforts.
Boost productivity - freeing engineers to focus on innovation.
Ensure software stability - with deterministic, high-coverage test generation.
Goldman Sachs
100% increase in code coverage with Diffblue Cover.
Legacy System Modernization
750K lines of Java legacy code covered with AI-driven testing.
Scalability: How Diffblue Cover Enables Continuous Testing Without Developer Effort
GitHub Copilot: Limited by Developer Availability
A GitHub Copilot-enhanced developer can cover ~1.4M lines of test code annually—assuming full-time engagement in test writing.
Diffblue Cover: Runs 24/7 Without Input
A single Diffblue Cover agent can cover ~25M lines of test code annually—with minimal developer effort.
GitHub Copilot is constrained by developer availability. Diffblue Cover scales testing continuously across teams and applications.
Security, Compliance & Enterprise Integration
Diffblue Cover Runs Fully On-Premises
GitHub Copilot operates in the cloud, sending proprietary code to an external AI model.
Diffblue Cover runs locally—ensuring your source code never leaves your infrastructure.
Seamless CI Pipeline Integration
GitHub Copilot integrates into IDE workflows but lacks robust CI automation.
Diffblue Cover integrates directly with GitHub Actions, GitLab, Jenkins, and enterprise CI/CD systems.
Secure, scalable, and compliant; Diffblue Cover is built for enterprise-grade software testing.
When to Use Diffblue Cover vs. GitHub Copilot?
GitHub Copilot
GitHub Copilot enhances individual developer workflows.
Developers seeking test suggestions for small projects
Writing tests for new features in small increments
Diffblue Cover
Diffblue Cover scales test writing across entire engineering teams.
Scaling fully autonomous unit testing across enterprise applications
Improving test coverage without developer effort
Automating regression testing & modernizing legacy systems
Get Started with Diffblue Cover Today
Enterprise engineering teams trust Diffblue Cover to drive AI-powered unit testing at scale.
Improve software stability with deterministic test generation.
Scale test coverage effortlessly across large codebases.
Reduce technical debt and increase development velocity.
Want to see the full picture?
Download the full report
In this free report, you’ll get:
- Hard data on coverage achieved by Copilot vs. Cover in a real 20k-line codebase.
- Productivity insights on developer effort saved through automation.
- Everything you need to help justify AI-driven unit testing at scale