Discover TÜV-certified GoogleTest with Agentic AI for C/C++ testing!
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WEBINAR
Open-source unit testing frameworks like GoogleTest have become the standard for modern C and C++ software development. But for organizations building safety- and security-critical embedded systems, adopting GoogleTest is only the beginning. Demonstrating structural code coverage, requirements traceability, tool qualification, and the compliance evidence needed for functional safety and cybersecurity standards requires more than a traditional open-source testing framework.
Watch this interactive discussion led by Chris Rommel, executive vice president at VDC Research, featuring Arthur Hicken, evangelist, and Ricardo Camacho, director of product, both from Parasoft, as they discuss how engineering organizations can confidently adopt and scale GoogleTest within regulated development environments.
The panel explores:
Learn practical strategies for modernizing embedded software verification workflows, improving software quality, streamlining compliance, and reducing certification risk, all while continuing to use the open-source tools your developers already know and trust, even as software complexity and AI-assisted development continue to grow.
Software has become the defining feature of today’s products, driving innovation across industries. Engineering teams expect software complexity to continue growing, with more than half anticipating at least a 25% increase in internally developed code on their next projects. This isn’t simply more code; it’s a fundamental shift in how software is being developed. Several factors are driving this complexity:
Together, these trends require engineering teams to deliver more software, integrate code from more sources, and produce greater compliance evidence, all while working with the same or fewer resources. The result is growing pressure to adopt more efficient, scalable verification strategies.
As software complexity grows, effective unit testing becomes even more important. Data shows that projects with mature unit testing practices report over 70% fewer customer-reported defects annually compared to those without. Organizations with mature unit testing practices also report lower-severity defects, reducing remediation effort from an average of 81 person-hours to 51 person-hours per defect.
However, a paradox exists: even with clear evidence of best practices, many organizations veer from established methods when adopting new technologies or facing time pressures. This can lead to projects falling behind schedule, which is particularly costly in the safety-critical space where delays can translate to hundreds of thousands of dollars in operational costs, not to mention lost revenue and certification risks.
This raises an important question: How can organizations continue using modern, open-source unit testing frameworks like GoogleTest while meeting the rigorous verification and compliance requirements of regulated industries?
GoogleTest has become the preferred unit testing framework for embedded C++ development. Its native C++ support, broad community adoption, seamless CI/CD integration, and open-source licensing make it an excellent choice for modern software teams.
However, organizations developing safety- and security-critical software soon discover that unit testing alone isn’t enough. Meeting the verification and compliance expectations of regulated industries requires additional capabilities that GoogleTest wasn’t designed to provide.
Engineering teams often encounter challenges in four key areas:
Without these capabilities, teams often rely on manual processes, disconnected tools, and custom integrations that increase engineering effort and certification risk. Safe software never happens by accident. It’s the outcome of intentional engineering.
When an organization identifies a certification gap with their GoogleTest workflow, there are typically three paths:
This approach enables teams to preserve their existing GoogleTest workflows while making them certification-ready. Instead of starting over, organizations can continue using the tools their developers know and trust while satisfying the verification and compliance expectations of regulated industries.
AI is transforming software development by helping engineers generate code, create tests, and remediate defects faster than ever before. But for safety- and security-critical software, AI doesn’t replace rigorous verification; it makes it even more important. Regardless of how code is created, organizations must still demonstrate structural code coverage, requirements traceability, compliance evidence, and confidence that software meets functional safety and cybersecurity requirements.
Parasoft combines AI-assisted testing with trusted verification technologies, including static analysis, unit testing, code coverage, requirements traceability, and compliance reporting, to help teams improve productivity while maintaining the rigor required for certification. This webinar explores how engineering organizations can confidently embrace AI without compromising software quality, safety, or compliance.
GoogleTest is an excellent unit testing framework, but safety- and security-critical software demands more than unit testing alone. Organizations also need structural code coverage, requirements traceability, compliance evidence, audit-ready reporting, and tool qualification support.
Parasoft C/C++test CT extends existing GoogleTest workflows with TÜV SÜD-certified GoogleTest packaging, structural code coverage, requirements traceability, compliance reporting, AI-assisted testing capabilities, and support for leading functional safety and cybersecurity standards. The result is a modern, certification-ready verification solution that helps teams improve productivity, simplify compliance, and deliver safer, more secure software.
