Many companies are investing significant resources in software development, but the use of Artificial Intelligence (AI) in development and design techniques is still immature. AIDOaRt focuses on supporting the continuous development of embedded systems with artificial intelligence. Built-in systems are all the systems of built-in micro-computers that control our cars, trains, planes and telephones, almost everything in our environment. With AI, the project must be able to support development at all stages, as well as operation, improvement and maintenance of the products. There is thus a strong industrial interest in the project's solutions, as development is made more efficient and cheaper, and in the end they will also benefit the consumer level, in the form of better, cheaper, safer and more sustainable products.
The project aims to support development teams during the automated continuous development of embedded computers using integrated AI-enhanced solutions. The overall AIDOaRT infrastructure must work together with existing data sources, but we must also ensure that systems are designed responsibly and contribute to our confidence in their behavior. AIDOaRT aims to contribute to companies where continuous distribution and operation is the core business. The project's framework will be validated in concrete industrial cases involving complex embedded systems, in Sweden's cases including trains, construction machinery, etc.
AIDOaRt is coordinated by MDH and has a total turnover of € 24.4 million and employs 80 full-time equivalents with academic and industrial researchers, project managers and other staff in our 32 organizations. MDH's total cost for the project is SEK 26.5 million and we have almost 8 full-time equivalent researchers and project managers involved. The funding comes partly from ECSEL-JU and the European Commission, and partly from VINNOVA. Our Swedish partners are Alstom, VCE, RISE and Westermo.
Requirements Ambiguity Detection and Explanation with LLMs: An Industrial Study (Sep 2025) Sarmad Bashir, Alessio Ferrari , Muhammad Abbas Khan, Per Erik Strandberg, Zulqarnain Haider, Mehrdad Saadatmand, Markus Bohlin 41st International Conference on Software Maintenance and Evolution (ICSME 2025)
Model Driven Engineering, Artificial Intelligence, and DevOps for Software and Systems Engineering: A Systematic Mapping Study of Synergies and Challenges (Aug 2025) Luca Berardinelli , Vittoriano Muttillo , Romina Eramo , Hugo Bruneliere , Abbas Rahimi , Antonio Cicchetti, Joan Giner-Miguelez , Abel Gomez , Pasqualina Potena , Mehrdad Saadatmand ACM Transactions on Software Engineering and Methodology (TOSEM)
A Road-Map to Readily Available Early Validation and Verification of System Behaviour in Model-Based Systems Engineering using Software Engineering Best Practices (May 2025) Johan Cederbladh, Antonio Cicchetti, Robbert Jongeling ACM Transactions on Software Engineering and Methodology (TOSEM)
Learning single and compound-protocol automata and checking behavioral equivalences (Apr 2025) Stefan Marksteiner, David Schögler , Marjan Sirjani, Mikael Sjödin International Journal on Software Tools for Technology Transfer (STTT)
ReqRAG: Enhancing Software Release Management through Retrieval-Augmented LLMs: An Industrial Study (Apr 2025) Md Saleh Ibtasham , Sarmad Bashir, Muhammad Abbas Khan, Zulqarnain Haider, Mehrdad Saadatmand, Antonio Cicchetti Requirements Engineering: Foundation for Software Quality (REFSQ 2025)
Requirements Similarity and Retrieval (Mar 2025) Muhammad Abbas Khan, Sarmad Bashir, Mehrdad Saadatmand, Eduard Paul Enoiu, Daniel Sundmark Handbook on Natural Language Processing for Requirements Engineering (HNLPRE)