Introduction to RequirementsAssistant

Context And Problem: The Growing Complexity of Engineering Projects

Over the past few years, I’ve been working in regulated industries and on large-scale projects where well–defined requirements are essential. These requirements not only help ensure compliance with constraints (e.g., regulatory standards) but also significantly reduce development costs by minimizing ambiguity and rework. However, as systems become more complex, developing these requirements effectively has become increasingly challenging.

Key challenges include:

• Increasing system complexity: Modern systems are too intricate to be mentally processed or fully understood without advanced tools. Interdependencies between system components sometimes lead to cascading effects of changes that are difficult to foresee.
• Communication gaps: Stakeholders often struggle to align their understanding of requirements, leading to misinterpretations and inefficiencies.
• Fragmented models: Different departments or teams working on the same project may lack a common source of truth, resulting in conflicting visions of the system.
• Limited flexibility in existing tools: Current model-based development tools, while offering simulation and validation capabilities, often fall short in adaptability. They struggle to accommodate varying levels of detail or provide instant feedback mechanisms. Moreover, these tools frequently have limited capacity to address the diverse communication needs of a wide range of stakeholders, resulting in a relatively narrow audience.

These issues not only slow down development but also lead to significant risks in terms of quality, cost overruns, and delays. Without a unified approach to modeling and validating systems, engineers struggle to confidently design robust systems while ensuring alignment across teams.

I believe there is the need for a solution that not only handles complexity but also fosters collaboration, provides actionable insights throughout the development process, and makes systems more tangible at an early stage—beyond just a set of written requirements in a document.

The Solution: A Smarter System for Requirements Development

To address these challenges, I’m developing an application that provides engineers with a system model capable of being validated, simulated, and debugged. The goal is to create a tool that offers instant feedback on potential issues while remaining flexible enough to adapt to various domains and levels of detail.

Key benefits of my solution include:

1. Clarity Through Structured Modeling:
   The system is specified as an ontology instance, where entities, rules, relations, and interactions are clearly defined. This structured approach ensures clarity in representing the system’s components and their relationships. By creating a tangible model early in the process, stakeholders can move beyond abstract written requirements and gain a clearer understanding of how the system will behave.
2. Powerful Core Functionality for System Manipulation:
   At its heart, the application includes core modules that provide essential functionality for creating, manipulating, and refining the system model. These modules act as the backbone of the tool, allowing engineers to efficiently define and adjust system details while maintaining consistency across all components.
3. Customizable Extensions for Diverse Needs:
   A flexible plugin system allows users to extend the tool’s capabilities for specific tasks such as:
   • Simulating system behavior.
   • Exporting specifications in preferred formats or templates.
   • Supporting domain-specific needs through custom extensions.
4. AI-Powered Assistance for Smarter Interaction:
   The system is designed as a foundation for future AI integration. This will enable advanced features such as:
   • Automatically detecting inconsistencies or gaps in requirements.
   • Proposing optimizations based on simulations.
   • Offering real-time suggestions during requirement development.
   • Enhancing interaction with the system through intuitive interfaces powered by AI assistance.
   • Saving valuable time by streamlining how users interact with the model and retrieve insights.
5. Enhanced Collaboration Across Teams:
   By providing a clear, shared model of the system, my application promotes better communication among stakeholders. This ensures alignment across teams and reduces misinterpretation of requirements while offering a common source of truth.
6. Applicable Across Domains and Complexity Levels:
   While the primary focus of this tool is on complex systems—such as embedded systems or large-scale GUI-based applications—it is also versatile enough to assist with simpler projects. Its flexibility allows stakeholders to choose the appropriate level of detail for their specific needs, making it suitable for a wide range of use cases.