Parasoft is outlining a future of AI-driven, autonomous testing workflows via a Model Context Protocol that lets AI agents reason about quality, safety, and compliance, automatically close coverage gaps, adapt static analysis, and integrate into safety-critical CI/CD environments.

At Embedded World, Parasoft announced integrating GoogleTest into a TÜV-certified toolchain with C/C++test CT to pre-qualify unit testing for ISO 26262 and IEC 62304, enabling faster onboarding and smoother CI/CD integration.

With growing complexity, connectivity, and regulatory pressure such as the EU Cyber Resilience Act, demand for automated testing in embedded systems is rising, making continuous verification in CI/CD essential for speed and trust.

A core challenge is proving freedom from interference in mixed-criticality systems; Parasoft tackles this with deeper, integrated testing that reveals non-deterministic interference between high- and low-criticality components.

Parasoft emphasizes secure-by-design and compliance with IEC 62443 and the Cyber Resilience Act by embedding security checks and audit-ready reporting (MISRA/CWE/CERT/OWASP) into the development lifecycle and CI/CD pipelines.

Transparency and traceability are highlighted through a connected model tying requirements, test cases, and analysis results in DTP, delivering end-to-end visibility into testing methods and compliance progress.

As an established player in automated software testing and application security, Parasoft brings a global footprint and a suite including C/C++test, Jtest, dotTEST, SOAtest, and Virtualize, designed to support safety-critical and regulated industries across the SDLC.

The company notes smooth integration with modern build and CI tools (Jenkins, GitLab, Azure DevOps), support for heterogeneous toolchains and cross-compilation, and scalable automation across distributed teams with policy gates and quality thresholds.

Parasoft anticipates a shift toward automation in DevOps/CI for embedded systems, automating repetitive tasks like static analysis remediation, regression testing, coverage analysis, and compliance reporting to free engineers for higher-level design and assurance work.

To manage scale and complexity, Parasoft introduced agentic AI workflows that contextualize data across requirements, traceability, static analysis, tests, and coverage, while keeping engineers responsible for validation and decisions in safety-critical contexts.