CASE2Space 2027

Mission-critical and autonomous systems are increasingly built around software that must make decisions, coordinate physical assets, and operate under high degrees of uncertainty. Such systems operate in environments that are remote, partially observable, bandwidth-limited, safety-constrained, and difficult or expensive to reproduce. The growing role of AI in and for these systems further amplifies software engineering challenges, raising questions on how AI-enabled functions can be engineered, validated, monitored, and governed, and how AI-based techniques can support development, testing, simulation, and operation.

The 1st International Workshop on Software Engineering for Mission-Critical and Autonomous Systems: from Earth to Outer Space (CASE2Space 2027) focuses on three software engineering challenge clusters that cut across mission-critical autonomous systems, combining concerns about development, verification, validation, and certification with practical software solutions for systems deployed in challenging operational environments:

• Autonomous and Robotic Systems: engineering approaches for specifying and validating autonomy, coordination, human oversight, and fallback behavior, as well as technical software solutions for cyber-physical systems operating in uncertain, safety-constrained, and resource-constrained environments.

• AI for Critical Systems and AI in Critical Systems: how AI can support engineering activities for critical systems, and how AI-enabled functions can be engineered, integrated, monitored, when they become part of systems whose failures may affect mission success or safety. This cluster covers both software engineering processes, methods, and tools for AI components and practical solutions concerning AI-based functionalities.

• Digital Twins and Simulation-based Engineering: how models, simulators, and digital twins can be used for design, testing, maintenance, and during system operation to provide enhanced adaptation and decision support.

These clusters define the core of CASE2Space: a forum to discuss how software engineering research and concrete industrial experience can jointly address the development, validation, assurance, and operation of AI-enabled, autonomous, and mission-critical systems. By bringing together researchers and practitioners, the workshop aims to create a meeting point between academic and industrial communities: research can benefit from concrete operational constraints, and evidence needs from real-world use cases, while practitioners can benefit from methodological advances in design, testing, verification, and validation.

Call for Papers

Mission-critical and autonomous systems are increasingly built around software that must make decisions, coordinate physical assets, and operate under high degrees of uncertainty. Especially in domains such as space exploration, Earth observation, underwater and maritime robotics, autonomous transportation, UAVs, and UGVs, operational environments are challenging. It is typically remote, partially observable, bandwidth-limited, safety-constrained, or difficult, impossible, and/or expensive to reproduce. These conditions affect both engineering-time and runtime concerns: the software controlling and coordinating these systems is difficult to specify, validate, monitor, evolve, and certify, while at runtime uncertainty can jeopardize operational safety and mission success, when operating under limited human supervision.

The growing role of AI in and for mission-critical systems further amplifies the engineering of such systems. On the one hand, AI is embedded in such systems to enable perception, planning, adaptation, autonomy, and decision support. On the other hand, AI-based techniques are increasingly used to engineer such systems, for example through test generation, simulation-based testing, predictive monitoring, and anomaly detection. However, when AI becomes part of, or is used to engineer, mission-critical autonomous systems, the main challenge is not simply to adopt AI, but to make it analyzable, monitorable, and governable under the operational constraints of critical domains. This setting calls for software engineering approaches, architectures, tools, and runtime solutions suited to AI-enabled mission-critical autonomous systems operating in remote, uncertain, and resource-constrained environments.

CASE2Space 2027 invites researchers and practitioners to submit contributions on software engineering approaches, architectures, methods, tools, runtime mechanisms, and practical solutions for mission-critical, autonomous, and AI-enabled systems.

Topics

Topics of interest include, but are not limited to:

• Requirements, specification, modeling, and design of mission-critical autonomous systems
• Software engineering under partial observability, limited communication, limited field access, remote operation, and resource constraints
• Verification, validation, testing, and certification of autonomous, robotic, and AI-enabled critical systems
• Simulation-based engineering, scenario-based testing, and virtual validation environments
• Runtime monitoring, runtime assurance, predictive monitoring, and anomaly detection
• AI-based techniques for engineering critical systems, including test generation, analysis, monitoring, and maintenance
• Engineering AI components for critical systems, including perception, planning, decision-making, and adaptation
• Explainability, traceability, analyzability, and governance of AI-enabled critical systems
• Model-based engineering, model-driven development, and formal methods for autonomous and critical systems
• Digital twins for mission support, operations, manufacturing, and system evolution
• Empirical studies, datasets, benchmarks, and tools for engineering mission-critical autonomous systems
• Applications in space, Earth observation, underwater and maritime robotics, autonomous transportation, UAVs, UGVs, and related domains
• Industrial experience reports and practitioner problem statements

Submissions

Submission types:

• Regular papers (up to 8 pages + references): research contributions, empirical studies, methods, tools, and substantial experience reports on software engineering for mission-critical and autonomous systems. Regular papers should clearly describe the problem tackled, the relevant state of the art, the proposed contribution, and the scientific or practical benefits.
• Short papers (up to 5 pages + references): position papers, emerging ideas, preliminary results, case studies, exemplars, and industrial problem statements that articulate a concrete challenge, motivate its relevance, and outline possible research or engineering directions.
• Extended abstracts (up to 2 pages + references): already published or mature research results to be presented and discussed within the workshop community, industry reports, lessons learned from practice, and open challenges from industrial or mission-critical domains. Extended abstracts are meant to stimulate discussion and do not need to present a complete research contribution.

All submissions must be written in English and conform to the IEEE conference proceedings template, specified in the IEEE Conference Proceedings Formatting Guidelines (title in 24pt font and full text in 10pt type, LaTeX users must use \documentclass[10pt,conference]{IEEEtran} without including the compsoc or compsocconf options).

Each paper will be reviewed by at least three program committee members. The reviews will be single-blind. Accepted regular and short papers will be published in the IEEE workshop proceedings in accordance with ICSE 2027 policies. Extended abstracts will not be included in the workshop proceedings.

The official publication date of the workshop proceedings is the date the proceedings are made available by IEEE. This date may be up to two weeks prior to the first day of ICSE 2027. The official publication date affects the deadline for any patent filings related to published work.