Modern software engineering tasks, from synthesis and AI-assisted development to testing and program repair, increasingly rely on automation. Automated tools now support developers in many stages of the software lifecycle, including code generation, dependency management, vulnerability detection, testing, and maintenance. While automation quickens development and maintenance processes, its impact on trustworthiness, reliability, and accountability remains unclear. Recent incidents in the software supply chain, the widespread propagation of vulnerabilities across dependencies, and the rapid adoption of AI-based code generation assistants and automated development agents have highlighted how automation can increase risks as quickly as it accelerates development. At the same time, regulatory frameworks and industry practices increasingly demand traceability, accountability, and verifiable assurance in modern software systems. To fill this gap, RASE focuses on advancing automated techniques that strengthen software transparency, protection, and assurance as core pillars of trustworthy systems. Besides fostering the development of trustworthy software systems, RASE aims to establish automation itself as a trustworthy actor within the software lifecycle, ensuring that automated tools and AI-based development assistants produce verifiable, auditable, and robust outcomes.

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome.

• Full papers (maximum of 8 pages, including references). Original research on Trustworthy Automated Software Engineering, either empirical, theoretical, or showing practical experience of using techniques and/or tools for addressing the challenge of enhancing the trustworthiness of software systems.
• Education tools and material (maximum of 8 pages, including references). Original contributions covering all dimensions of learning and teaching approaches and techniques for enhancing the accountability, transparency, dependability, and integrity in software engineering courses. This also includes experience reports providing informal proof by outlining a particular experience connected to education and training, such as a course, an educational or training method. The submission should translate the experience into practical guidance and insights gained, without the requirement for thorough evaluation or the application of rigorous research techniques to back its claims.
• Replication Studies and Negative results (maximum of 8 pages, including references). Research papers and reviews focusing on negative results or the reproducibility of previously published work. We believe that publishing negative results, alongside positive ones, provides a more holistic view of the research landscape, fostering transparency, credibility, and the elimination of publication bias.
• Short and Demonstration papers (maximum of 4 pages, including references). Work that describes novel techniques, tools, ideas, and positions that have yet to be fully developed; or are a discussion of the importance of a recently published result by another author in setting a direction for the SE community, and/or the potential applicability (or not) of the result in an industrial context.
• Position papers (maximum of 2 pages, including references). Contributions that analyze impact of automated software engineering techniques on trustworthiness, raising issues of importance. Position papers are intended to seed discussion and debate at the workshop, and thus will be reviewed with respect to relevance and their ability to spark discussions.

Contact

All questions about submissions should be emailed to alessandro.sanna96@unica.it