Data Driven System Engineering (DDSE) Consulting, LLC

DDSE Consulting, LLC is the sole owner of granted patent:"Data Driven Computing System Development", which has wide range applications, and this website is intend to promote the innovation by collaboration.

Overview

This invention introduces a systematic approach for constructing computing system software and implementing safety mechanisms, focusing on two key attributes: Data Value and Data Timing. The methodology aims to optimize development processes and ensure system correctness and reliability.

Construct Computing System Software

The invention proposes a definitive method to:

• Based on three essential components:
• Input Data
• Middle Data
• Output Data
• Define calculations or relationships between these components.

Develop Safety Mechanisms

• Ensure the software functions correctly by monitoring and controlling:
• Data Value: Ensures accurate computation and relationships.
• Data Timing: Manages system latency, including transmission and calculation durations.

Key Concepts

1. Data Attributes: Every computing system software has two, and only two, fundamental attributes:
   • Data Value: Represents the correctness of the output data derived from the input and middle data through predefined calculations.
   • Data Timing: Represents the system latency, including:
     • Data transmission durations.
     • Data calculation durations.
2. System Development Goals: The primary goal is to:
   • Realize the required Data Value and Data Timing for each output data.
   • Develop safety mechanisms to:
     • Detect deviations in Data Value and Data Timing.
     • Prevent the system from impacting others by outputting deviated data.
3. Safety Mechanism Objectives:
   • Identify deviations in Data Value and Data Timing.
   • Prevent undesired system behaviors by addressing deviations effectively.
   • Optimize development activities by integrating safety mechanisms with software construction.

Benefits

• Unified Framework: Defines software construction and safety mechanism development once the data and their relationships are established.
• Efficiency: Reduces complexity by focusing on two attributes.
• Reliability: Ensures that deviations are detected and mitigated, minimizing the risk of failure.

Conclusion

This approach provides a clear and systematic method to construct and validate computing system software and its safety mechanisms. By focusing exclusively on Data Value and Data Timing, development processes are significantly optimized while ensuring robust system functionality.