========================================================================
CALL FOR PAPERS
========================================================================

The workshop on Reliable and trustworthy Automated Software Engineering 2026 (RASE 2026)
in conjunction with the 41st IEEE/ACM International Conference on Automated Software Engineering (ASE 2026)

Mon 12 - Fri 16 October 2026, Munich, Germany

For more details, please visit the RASE 2026 official website:
https://conf.researchr.org/home/ase-2026/rase-2026

SCOPE
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.

Researchers and practitioners are invited to submit:

- 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.
In all cases, papers should address a problem at the intersection between trustworthiness and software engineering or combine elements of transparency, accountability, or dependability research with other concerns in the software engineering lifecycle.

TOPICS OF INTEREST
Pragmatically, RASE welcomes contributions on foundations, techniques, tools, and empirical studies related to automating trustworthy software engineering, including but not limited to:

Automation for Software Transparency
- Automated generation, validation, verification, and evolution of Software Bills of Materials (SBOMs) and AI Bills of Materials (AIBOMs)
- Dependency analysis, supply-chain visibility, and provenance tracking
- Behavioral transparency through automated logging, monitoring, and runtime explainability
- Automated compliance checking and transparency auditing
- Automating regulatory compliance checks (e.g., EU Cyber Resilience Act, AI Act …)
- Software Composition Analysis
- Automated traceability across software artifacts, models, and dependencies
- Transparency mechanisms for AI-assisted software development tools and pipelines

Automation for Software Trustworthiness
- Automated vulnerability detection, localization, and repair
- Impacts, problems, and risks of the vulnerability fixing process
- Protection against supply-chain attacks and dependency confusion
- Automated integrity verification and tamper detection
- Secure-by-construction and policy-driven code generation
- Automated hardening, sandboxing, and isolation techniques
- Protection of software assets
- Protection of ML-enabled and AI-assisted software system
- Security mechanisms for AI-generated code and automated software artifacts

Trustworthy Automation
- Verification and validation of automated SE tools
- Confidential computing impacts on software effectiveness
- Trustworthiness of AI-based code generation and repair
- Empirical studies of automation-induced risk
- Human-in-the-loop approaches for trustworthy automation
- Transparency and explainability of automated software engineering tools
- Accountability and governance mechanisms for automated development agents

Foundations and Evaluation
- Metrics and benchmarks for trustworthy automation
- Large-scale empirical studies on software supply-chain risk
- Industrial case studies and tool demonstrations
- Empirical evaluation of AI-assisted development tools
- Benchmarking trustworthiness properties of automated SE systems

SUBMISSION GUIDELINES
All submissions must conform to the ASE 2026 formatting and submission instructions. All submissions must be anonymized, in PDF format and should be submitted electronically through EasyChair: https://easychair.org/conferences/?conf=rase2026