Artificial intelligence in software development

Generating documentation\nwith AI

Norm-compliant, fast and traceable

Initial situation

Documentation in safety-critical systems

In industries such as rail transportation and manufacturing, traceable and norm-compliant documents are mandatory but time-consuming and error-prone.

Documentation, Standards and Liability

Rail Transportation

In the rail industry, documents are a central part of the safety case. Since they serve as the basis for homologation and tests, they must be traceable, complete, and norm-compliant. Relevant standards, such as EN 50716, define strict requirements for development processes, documentation obligations, and proof of evidence. Faulty or incomplete documentation can have far-reaching consequences: from project delays and missing approvals to liability risks during operation. Therefore, an enormous effort is often required to keep documents consistent and maintain them in a norm-compliant manner. However, these processes can be structured and made more efficient with AI-based tools – without compromising the high safety requirements.

Documentation, Standards and Responsibility

Industry

In industrial automation, similarly strict requirements apply to safety, reliability, and traceability. Standards such as IEC 61508 or ISO 13849 require precise documentation of all safety-relevant functions, development phases, and test results. These documents not only serve internal quality assurance but are also binding evidence towards certification bodies. Incomplete or inconsistent documentation can lead to significant liability risks in an industrial environment, especially if malfunctions could lead to plant shutdowns, production losses, or even personal injury. Therefore, the effort for clean, up-to-date, and norm-compliant documents is often very high. AI can assist by creating documents faster, updating them consistently, and reducing sources of error.

Document types

AI can help with these document types

In safety-critical projects, various document types are maintained – and required to be complete, consistent and in compliance with norms and standards. AI helps to recognize recurring structures and to generate or update content faster. This results in documentation that remains technically precise and requires less effort.

Requirements

AI can formulate, structure or derive requirements from notes and ensure consistent wording. This reduces misunderstandings and clarifies the basis for further development phases.

Architecture

AI can generate understandable texts about the structure, components, and interfaces from existing architecture models or descriptions. This facilitates both reviews and knowledge transfer within the project team.

Design

Design decisions, patterns and technical background can be described automatically and documented consistently. This makes it easier to continuously update the document during development.

Test Specification

Based on requirements, rules, and examples, AI can generate test specifications that serve as the basis for black-box or integration tests. This saves time and ensures a uniform structure.

Core Goals

More complete and
up-to-date documentation

Less effort for
creation and maintenance

Input

What the AI needs

For AI to generate reliable documents, it needs a clear understanding of project content, standards, and system structures. The more comprehensive and precise the information provided is, the better the quality and consistency of the generated documentation will be.

Architecture & system descriptions
Project notes
Comparable projects
Norms & guidelines
Glossary
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