Call for Papers: Special Issue on Taking Flight: Software for Small Uncrewed Aerial Systems

Small uncrewed aerial systems (sUAS) are increasingly transforming domains such as disaster response, environmental monitoring, precision agriculture, and infrastructure inspection. As their presence grows and missions become more complex, these systems are evolving from isolated devices into networked, autonomous swarms. This shift introduces unprecedented challenges for software engineering, particularly in designing reliable, adaptable, and safe sUAS platforms capable of operating in dynamic, mission-critical, and ethically sensitive environments.

Beyond technical challenges, the growing autonomy of aerial systems raises critical concerns for software engineers and society alike, including dual-use risks, privacy, accountability, sustainability, and regulatory compliance. Addressing these challenges demands rigorous engineering methods that span the full software life cycle, from eliciting requirements and architecting dependable systems, to testing under diverse operational conditions, deploying in critical contexts, and assuring trustworthy runtime behavior under uncertainty.

For software practitioners, sUAS represent a unique intersection of embedded, cyber-physical, and AI-enabled systems. This special issue aims to advance the engineering of trustworthy, adaptive, and responsible software for sUAS, inviting contributions that combine scientific insight with practical relevance. We especially welcome papers that demonstrate tangible improvements in software quality, reliability, assurance, and societal impact.

We seek submissions addressing both foundational and emerging challenges, emphasizing methods, practices, and case studies that unite research and real-world application to advance the state of practice in this rapidly evolving field.

Topics of interest include, but are not limited to:

• Requirements engineering for sUAS command, control, and mission planning
• Software architecture for modularity, resilience, and adaptation
• Verification, validation, and simulation of sUAS flight software
• Digital twins, runtime monitoring, and adaptive assurance mechanisms
• Testing and integration in uncertain or adversarial environments
• Human–machine teaming and operator-in-the-loop control
• Certification, traceability, and safety assurance for adaptive or ML-enabled flight systems
• Ethical, legal, and societal implications of autonomous aerial software
• Responsible AI, Data governance, and privacy in sUAS sensing and analytics
• Benchmarking, reproducibility, and open datasets for sUAS software evaluation
• Cross-cutting concerns such as AI assurance, software sustainability, supply chain security, and trustworthy autonomy

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Submission Types

We encourage submissions that bridge research and practice, including:

• Research articles presenting novel software engineering techniques, tools, frameworks, or empirical studies evaluated in the context of sUAS
• Technical experience reports and industrial case studies reflecting on deployed sUAS, integration challenges, or lessons learned
• Tutorials providing clear, structured guidance on methods, architectures, or assurance strategies for trustworthy sUAS.

Viewpoints articulating pressing technical, ethical, or certification dilemmas, or outlining future research directions and grand challenges

Submission Instructions:

For author information and guidelines on submission criteria, visit the IEEE Software Author Information page. Please submit papers through the IEEE Author Portal system, and be sure to select the special issue or special section name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the IEEE Author Portal. If requested, abstracts should be sent by email to the guest editors directly.

In addition to submitting your paper to IEEE Software, you are also encouraged to upload the data related to your paper to IEEE DataPort. IEEE DataPort is IEEE's data platform that supports the storage and publishing of datasets while also providing access to thousands of research datasets. Uploading your dataset to IEEE DataPort will strengthen your paper and will support research reproducibility. Your paper and the dataset can be linked, providing a good opportunity for you to increase the number of citations you receive. Data can be uploaded to IEEE DataPort prior to submitting your paper or concurrent with the paper submission.