This work presents the first characterization study of open-source satellite software, examining its ecosystem and development practices, revealing a highly heterogeneous and task-specialized ecosystem with 66 programming languages and diverse implementation strategies.
Abstract
Satellites have become fundamental components of modern technological systems, supporting critical infrastructure in communication, navigation, Earth observation, and scientific research. As space exploration advances and demand for satellite-enabled services grows, reliance on complex, heterogeneous satellite software continues to increase. A systematic understanding of the satellite software landscape is therefore increasingly important, yet existing studies still lack a comprehensive empirical examination. To address this gap, we present the first characterization study of open-source satellite software, examining its ecosystem and development practices. We mine and analyze 22,286 satellite-related GitHub projects through three research questions on popularity trends (RQ1), software goals (RQ2), and development practices (RQ3). First, we characterize the temporal evolution of projects and active developers, revealing increasing popularity. Second, through manual inspection of 646 projects, we construct a taxonomy of 43 software-goal categories spanning conceptual design, datasets, system implementation, simulation, testing, and tools. Third, we conduct an in-depth analysis of projects with source code, revealing a highly heterogeneous and task-specialized ecosystem with 66 programming languages and diverse implementation strategies. Finally, we summarize key findings and derive actionable implications for satellite developers and researchers.
A systematic mapping study of Green SE research published between 2010 and 2024 indicates that SE conferences host the majority of energy-related literature, and optimization and benchmarking emerged as the most prevalent research types.
Max Hort, Maria Kechagia, Federica Sarro· 0 citations
A quality evaluation model and method tailored for WMS, encompassing four critical dimensions: query and retrieval, map display, thematic services, and productization services, is proposed, demonstrating the model’s efficacy in quantifying service quality, aligning closely with real-world user experiences.
Wen-Li Han, J. Ge, Li-Bo Zhang et al.· The International Archives o...· 0 citations
It is demonstrated that multiple architectural views, continuous monitoring, domain-driven decomposition, and AI-assisted design techniques contribute significantly to improving scalability, maintainability, adaptability, and long-term software sustainability.
A large-scale empirical study of mainstream open-source agent frameworks from an engineering perspective, providing empirical evidence linking framework design choices to engineering risks and highlighting the need for stronger guidance and support in agent framework development.
Yibo Zhai, Junjun Si, Yan Wang et al.· SIGSOFT FSE Companion· 0 citations
It is revealed that feature branches in open-source projects are long-lived, with a median lifespan exceeding two years, diverging from the short, agile iterations typically employed in software development.
Nitish Patkar, Aimen Fahmi, Timo Kehrer et al.· Empirical Software Engineeri...· 0 citations
It is argued that future progress depends less on incremental accuracy gains than on reproducible multi-source workflows, explicit uncertainty, trustworthy and explainable geospatial artificial intelligence, privacy-preserving governance, interoperable standards and evaluation in the institutions that ultimately use th...
Yashvardhan Singh, Divya Singh, Sakshi Shukla et al.· Advances in Research· 0 citations
Related blog posts
Microsoft Research Blog· microsoft.comOct 12, 2026
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026
Writing as a participant and researcher, PhD student JS Tan SM ’22 has co-authored a new book about the rise of tech worker protests and the employer backlash that followed.
MIT News · Artificial Intelligence· news.mit.eduOct 2, 2026
Writing as a participant and researcher, PhD student JS Tan SM ’22 has co-authored a new book about the rise of tech worker protests and the employer backlash that followed.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.