Today, we’re announcing breakthrough advances to our flagship product, Diffblue Cover, that solve the industry’s most persistent challenge: achieving high-quality test coverage at enterprise scale. These new capabilities enable development teams to systematically surpass coverage ceilings and accelerate critical application modernization, compliance, and productivity initiatives.
This bold claim is supported by a new benchmark study that shows Diffblue’s reinforcement learning approach to agentic unit test code generation is 20x more productive than LLM-based coding assistants such as Claude Code, GitHub Copilot, and Qodo Gen. The study reveals that while AI-powered coding assistants have made remarkable progress, Diffblue Cover’s purpose-built autonomous testing solution maintains decisive advantages in speed, reliability, and true automation.
Our expertise in shift left testing showed us that the solution to breaking through coverage barriers is not about generating more tests faster with AI tools. It’s about orchestrating every available resource—including your existing tests, your team’s domain knowledge, and your approved AI tools—into a coordinated system that achieves what no single approach can accomplish on its own.
The next generation of Diffblue Cover introduces three new capabilities that offer quick, easy ways to improve test coverage and quality: Test Asset Insights, LLM-Augmented Intelligence, and Guided Coverage Improvement. Collectively, they extend Diffblue’s market-leading capabilities far beyond what LLM-based coding assistants can deliver.
1. Test Asset Insights: Leveraging Existing Test Infrastructure
Test Asset Insights enables Diffblue Cover to analyze pre-existing unit test coverage and extract intelligence that it leverages to write additional tests. The agent learns from existing patterns, reuses established helper methods and fixtures, and builds upon domain-specific test infrastructure to generate high-quality, idiomatic test coverage.
Tests are clearly annotated to distinguish user-written, Diffblue-contributed, and Diffblue-managed tests, enabling hybrid workflows in which the Diffblue agent autonomously maintains coverage as production code evolves. This clear separation of ownership enables powerful CI/CD integration, where Diffblue-managed tests are automatically updated while user-modified tests remain protected.
2. LLM-Augmented Intelligence: Context-Aware Test Data Generation
LLM-Augmented Intelligence fuses the power of customer-approved large language models with Diffblue’s reinforcement learning-based test generation to deliver better coverage and quality than any single generative AI technique can deliver in isolation. This eliminates months of security reviews and compliance assessments required for introducing new models.
By tapping into the capabilities of in situ LLMs using a bring-your-own-model approach, Diffblue Cover generates even higher quality test coverage for complex business logic, while maintaining the product’s signature promise: deterministically generated, high-quality tests that always compile and pass. The process is designed to be highly optimized and cost-effective, only prompting the LLM for specific, required data. A soon-to-be-released MCP server provides an optional, standardized approach to connect to LLMs and automate agentic workflows transparently.
Read our CEO Toffer Winslow‘s take on the latest Gartner Hype Cycle for AI in Software Engineering 2025, while AI-Augmented Testing moves to the “Trough of Disillusionment.”
3. Guided Coverage Improvement: Intelligent Issue Prioritization
Guided Coverage Improvement dramatically speeds up the rate at which Diffblue Cover improves coverage beyond the agent’s first pass over a code base. It accelerates the resolution of coverage-blocking issues by automatically identifying and prioritizing the underlying problems and generating an actionable turnkey coverage improvement plan.
The feature aggregates output codes into prioritized issues and provides step-by-step guidance and automation. Each issue is assigned a severity level to aid in prioritization and is associated with a dynamically generated prompt designed for AI coding assistants or human developers. Internal testing on several repositories has shown that this new capability can, in just one hour, raise coverage by 50% beyond out-of-the-box coverage.
“Together, these three new capabilities represent a fundamental shift in how enterprises can deal with under-tested applications. We’re not just generating more tests faster; we’re orchestrating a complete solution that understands existing test infrastructure, leverages enterprise-approved AI models, and provides intelligent guidance to systematically achieve coverage goals faster and more efficiently than any alternative on the market.”
Benchmark Study: 20x More Productive Than LLM-Powered Code Assistants
Our reinforcement learning approach to agentic unit test generation isn’t just incrementally better. While LLM-based coding assistants like Claude Code and GitHub Copilot can help developers write individual tests, they struggle with the systematic generation of comprehensive test suites at scale.
The numbers speak for themselves: Diffblue Cover is 20x more productive than these LLM-powered alternatives. This isn’t about writing tests faster—it’s about autonomous, guaranteed-to-compile test generation that achieves coverage goals without constant human intervention. While a developer using Copilot might spend days writing tests to reach 60% coverage, Diffblue Cover achieves the same result in hours, automatically.
New Benchmark Report: Diffblue Cover vs. Leading AI Coding Assistants
Unlocking Java Modernization: From Legacy to Latest
These three capabilities converge to solve one of enterprise Java’s most expensive problems: modernization paralysis. When Oracle’s Java 8 support ends or you need Java 21’s performance improvements, the blocker isn’t technology—it’s test coverage.
Test Asset Insights transforms your years of test infrastructure into intelligent templates for modern test suites, preserving institutional knowledge while expanding coverage. LLM-Augmented Intelligence generates contextual test data that validates behavior across Java versions, catching subtle breaking changes in streams, optionals, and collection APIs that generic test data would miss.
And when modernization tools flag thousands of compatibility warnings, Guided Coverage Improvement transforms that chaos into a prioritized modernization roadmap: “Fix this DateTimeFormatter issue first, it affects 200 test cases across your payment processing module.”
The result? Our customers are completing Java 8 to Java 17 migrations in months rather than the previously required two-year programs. The coverage that unblocks your CI/CD pipeline today becomes the safety net for your modernization tomorrow
What This Means for Your Team
Organizations with deployment pipelines blocked by coverage requirements can now ship within quarters. Enterprises dealing with million-line untested codebases from acquisitions can complete integration in months rather than years. Teams facing regulatory audits with insufficient coverage can meet and exceed compliance standards with confidence.
The next generation of Diffblue Cover addresses the unmet need for automated, high-quality unit test generation at scale. These capabilities empower software development teams to systematically break through typical test coverage barriers that have historically blocked modernization, compliance, and productivity initiatives.
The Future of Test Coverage
The next generation of Diffblue Cover represents a fundamental shift in how enterprises address under-tested applications. By orchestrating existing test infrastructure, enterprise-approved AI models, and intelligent guidance systems, organizations can achieve coverage goals that no single approach could deliver in isolation.
This transformation moves beyond incremental improvements in test generation speed. Diffblue Cover’s three new capabilities—Test Asset Insights, LLM-Augmented Intelligence, and Guided Coverage Improvement—work together to create a comprehensive solution that systematically achieves enterprise coverage requirements while maintaining the deterministic quality and reliability that mission-critical applications demand.
Ready to Break Through?
If your organization is facing compliance deadlines, blocked CI/CD pipelines, or stalled modernization initiatives due to insufficient test coverage, we should talk.
See how Diffblue Cover’s next-generation capabilities can transform your testing strategy. Book a demo and we’ll show you how leading enterprises are meeting their coverage requirements in quarters, not years.
