Bits & Chips event 2024

Bits & Chips event 2024

Date: October 10, 2024

Venue: Van der Valk, Best

Bits & Chips event 2024

On 10 October 2024, the fourth edition of the Bits&Chips event will take place at van der Valk Eindhoven-Best.
This year’s edition is actively supported by TNO-ESI. We look forward to meeting you there.

The conference program will cover the following topics:

  • Generative AI

  • Machine learning

  • Software quality

  • System architecture

Are you interested to visit the event? Please contact us

ESI presentations

Sezen Acur and Bram van der Sanden

What can systems engineering offer to the high-tech equipment industry for continuous innovation?

Systems engineering complexity in the high-tech equipment industry has increased, as the systems themselves steadily evolved with increased functionality and complexity. Current systems have a long lifetime, undergo rapid technological advancement, are increasingly software-intense, and connected to other systems. Growing system complexity, the global competition, successful adoption of new technologies as AI, and scarcity of systems engineers provide challenges to continuous innovation of the high-tech equipment industry. 

Improved Systems Architecting and Systems Engineering (SA/SE) methodologies and competence development are needed to address these challenges. TNO-ESI has created an outlook on the required SA/SE capabilities. This presentation provides an overview of identified relevant trends and challenges across the high-tech equipment industry, the derived needs, and a research outlook on what is needed to upgrade their Systems Architecting and Systems Engineering capabilities.

Nan Yang

Leveraging large language models for legacy software

Legacy code is challenging to maintain and understand, yet it is crucial for the operation of complex systems, especially in the Dutch high-tech industry. Static analysis techniques are often used to extract insights from codebases. While reliable, these techniques require parser-specific and domain-specific knowledge, resulting in a steep learning curve that limits their adoption in industrial environment. In contrast, Large Language Models (LLMs) excel in general human-machine interpretation and user-friendliness but lack the precise domain-specific knowledge needed for in-depth accurate code analysis.

At TNO-ESI, we are developing a hybrid method that combines traditional static analysis with LLMs to better support software understanding and development. By using parser-based static analysis we extract code details into a graph database. We enable LLMs to interact with this graph database to provide natural language responses with accurate knowledge on the codebase. This hybrid approach demonstrates how LLM accuracy can be augmented using traditional static analysis methods and conversely traditional software engineering techniques can be enhanced by integrating abstraction capabilities and user-friendliness of LLMs, allowing users to obtain answers that neither static analysis tools nor LLMs could address independently.

Wytse Oortwijn and Sjoerd Zwart (VDL-ETG)

Do you still develop supervisory controllers by hand?!

Supervisory control is a key part of cyber-physical systems, to orchestrate all system resources to work together in a safe, correct and optimal way. Developing supervisory controllers by hand becomes increasingly challenging, for instance due to increasing performance demands, the need to support more and more system variants, shortage of skilled engineers, and so on. In contrast, with Synthesis-Based Engineering (SBE), correct-by-construction supervisory controllers can automatically be computed based on requirement specifications of what the system should do. These are typically much easier to specify than having to work out how the system should realize its requirements in every possible situation, as is done traditionally. SBE has successfully been applied in industry, for example in the semiconductor domain, the industrial printing domain, and the healthcare domain. TNO-ESI is currently investigating the application of SBE together with ASML and VDL-ETG, which we will elaborate upon in this presentation.

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Sezen Acur

Bram van der Sanden

Nan Yang

Wytse Oortwijn

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