Software and Systems Modeling

Aims & Scope

Software and Systems Modeling (SoSyM) is a bi-monthly international journal (published in English) that focuses on theoretical and practical issues pertaining to the development and application of modeling languages and techniques for software, as well as engineered and natural systems and processes. The aim of the journal is to publish high-quality works that (1) further understanding of the theoretical and foundational underpinnings of modeling languages and techniques, (2) present rigorous analyses of modeling experiences, and (3) introduce scalable modeling techniques and processes that facilitate rigorous and efficient development and understanding of software and systems. SoSyM encompasses several communities involving modeling languages and techniques, such as Model-Driven Engineering, Modeling and Simulation, or Data Engineering. The journal is unique in its emphasis on theoretical foundations of modeling languages and techniques, and on rigorous analyses of "real-world" modeling experiences. The balance of theoretical works and works based on in-depth analyses of experiences offers insights to researchers that can inform future investigations into better modeling languages and techniques, and provides modeling practitioners with a deeper understanding of modeling languages and techniques that can lead to more effective application. The journal targets researchers, practitioners and students who have a vested interest in results generated by high-quality modeling research and by rigorously analyzed modeling experiences. We invite authors to submit papers that discuss and analyze research challenges and experiences pertaining to software and system modeling languages, techniques, tools, practices and other facets. The following are some of the topic areas that are of special interest, but the journal publishes on a wide range of software and systems modeling concerns: Domain-specific models and modeling standards Model-based testing techniques Model-based simulation techniques Formal syntax and semantics of modeling languages such as the UML Rigorous model-based analysis Model composition, refinement and transformation Software Language Engineering Modeling Languages in Science and Engineering Language Adaptation and Composition Metamodeling techniques Measuring quality of models and languages Ontological approaches to model engineering Generating test and code artifacts from models Model synthesis Methodology Model development tool environments Modeling Cyberphysical Systems Data intensive modeling Derivation of explicit models from data Case studies and experience reports with significant modeling lessons learned Comparative analyses of modeling languages and techniques Scientific assessment of modeling practices Use of AI methods for model-based development tasks and techniques Modeling methods that include agentic-AI co-workers AI-assisted modeling tools AI-assisted software modeling languages

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Source: OpenAlex · Note: citations accumulate over time so older years appear higher

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