A Research-Backed Hybrid-AI Engine
Eliminate "Spaghetti Code" and automate certification with the world’s first Hybrid AI engine.
From Architecture Analysis to 100% MC/DC Coverage.
The Total Testing Platform for Autonomous Functional Safety
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In safety-critical industries, software defects are not just inconveniences—they are liabilities. History has taught us that a lack of rigorous testing and architectural discipline leads to catastrophe.
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The Challenge: Standardized testing (DO-178C, IEC 61508, ISO 26262) is mandatory, but manual compliance is broken. It is slow, prone to human error, and struggles to keep pace with modern iterative development.
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The Solution: TimeZero is the "Total Testing Platform" that solves these headaches by combining advanced Static Analysis, Architectural Visualization (DSM), and AI-driven Test Generation into a single, autonomous workflow.
Architectural Integrity & "Spaghetti Code" Prevention
VISUALIZE DEPENDECIES
We move beyond simple flowcharts to partition modules hierarchically, making hidden dependencies visible.
PREVENT EROSION
Our platform identifies "bad" dependencies (e.g., a Driver layer calling a Scheduler layer improperly) and flags them immediately.
LATTIX INTEGRATION
Leveraging powerful Lattix LDM technology, we allow you to establish independence rules and track architectural health over time with "Delta Reports".
Advanced Static Code Analysis (SCA) & Security
We have evolved far beyond the basic "Lint" checkers of the 1970s. Tymaton provides "Smart On-the-Fly Analysis" that includes whole-program inter-procedural control and data-flow analysis
SECURITY STANDARDS
We support 7 out of the OWASP Top 10 (the maximum statically verifiable), 12 of the CWE/SANS Top 25, and full CERT Secure Coding standards.
CODING STANDARDS
Full enforcement of MISRA C/C++ and AUTOSAR C++14, integrated directly into the developer's IDE.
MEMORY SAFETY
Detection of buffer overruns, memory leaks, and uninitialized variables before dynamic testing even begins.
Hybrid AI
NEW SCIENCE-BASED TOOL
Tymaton is not a wrapper for a generic chatbot. It is a specialized tool developed in collaboration with the Department of Computer Science at the University of Bath.
RAG ARCHITECTURE
We utilize a Retrieval-Augmented Generation (RAG) architecture. Source code is chunked and stored in a Vector Database, allowing our embedded AI models to query context-specific code segments for accurate test generation.
SYMBOLIC EXECUTION + LLM
We solve the "100% MC/DC" challenge by using a hybrid approach. When traditional SMT solvers (like Z3) hit complexity limits, our LLM engine (Claude/OpenAI) decomposes the constraints to generate valid test vectors for complex logic.