What is TC Auto-Generation? — The Era of AI-Powered Test Case Creation

What is TC Auto-Generation?

Software testing is an inseparable part of automotive software development. And testing requires test cases (TCs) — definitions of what inputs to provide, what results to expect, and under what conditions to execute.

The challenge is that creating these TCs manually is time-consuming. Reading requirements documents, designing test scenarios, and writing test code consumes a significant portion of the overall development timeline. With dozens to hundreds of software components in a single ECU, manual TC creation has clear limitations.

TC Auto-Generation automates this process by analyzing requirements, design models, or source code to create test cases automatically.

Three Approaches to Auto-Generating Test Cases

Requirements-Based

Analyzes requirements documents to derive test scenarios. For a requirement like "trigger warning when vehicle speed exceeds 120km/h," the system generates TCs such as "verify warning at >120km/h," "verify no warning at ≤120km/h," and "verify boundary at exactly 120km/h."

Recent advances in AI enable natural language processing of requirements documents to extract technical requirements automatically and generate corresponding test cases.

Model-Based

Analyzes input/output interfaces and state transitions from design models like ARXML or Simulink to generate TCs. Port definitions and runnable specifications of software components serve as inputs for automatic application of boundary value analysis, equivalence partitioning, and other test design techniques.

Code-Based

Statically analyzes source code branches, conditions, and paths to generate TCs that maximize code coverage. Particularly effective for achieving MC/DC (Modified Condition/Decision Coverage) required by ISO 26262.

Why TC Auto-Generation Matters for ASPICE

In ASPICE (Automotive SPICE), verification-related processes are central to software development: SWE.4 (Unit Verification), SWE.5 (Integration Testing), and SWE.6 (Qualification Testing).

What OEMs require is not simply "tests were executed." Bidirectional traceability between requirements and TCs, quantitative coverage measurement, and systematic test strategy are essential.

TC auto-generation accelerates this significantly — automatically mapping requirement IDs to TCs for traceability matrices, generating coverage reports, and identifying impacted TCs when requirements change.

ASPICE 4.0, released in November 2023, expanded its scope to include Agile and DevOps methodologies. With iterative and continuous verification becoming more critical, the limitations of manual TC management are increasingly apparent.

AI is Changing Automotive Testing

In 2025-2026, AI adoption in automotive software testing is accelerating rapidly.

Across the global automotive industry, generative AI is already being applied to requirements-based TC generation, AI-powered test script automation, and automated ASPICE/ISO 26262 compliance verification in real projects.

The common direction is clear: automate requirements analysis, TC generation, coverage measurement, and traceability management with AI, so engineers can focus on design and judgment.

Considerations for Adopting TC Auto-Generation

When adopting TC auto-generation, key considerations include: ASPICE artifact integration (traceability matrices must accompany auto-generated TCs), understanding limitations (auto-generated TCs excel at structural coverage but domain-specific scenarios still require engineer judgment), and toolchain integration (CI/CD pipeline connectivity and seamless integration with existing development environments).

PARVIS-Verify: Automating from Design to Verification

PopcornSAR's PARVIS connects the entire design-development-verification process into a single data flow, automatically generating artifacts that comply with ASPICE processes.

PARVIS-Verify handles test coverage analysis and automated test code generation. It automatically generates test scenarios based on test requirements and continuously updates coverage reflecting code change history. In real projects, PARVIS-Verify achieved 86.4% test coverage, generating 247 test cases with a 100% pass rate.

PARVIS-Verify works alongside PARVIS-Spec (automated requirements analysis) and PARVIS-Coder (MISRA-C automation) to provide 3-step automation from requirements analysis to code verification to test generation.

Learn more on the PARVIS product page. If you'd like to explore specific use cases, feel free to contact us.