SOFSEM 2018 := Call for Papers
Tracks & Topics
SOFSEM 2018 consists of three tracks covering major sub-areas of computer science: the traditional track on Foundations of Computer Science and two tracks devoted to leading developments in the areas Software Engineering: Methods, Tools, Applications and Data, Information and Knowledge Engineering. Original contributions are welcome, presenting new research results in the theory and practice of computer science in each sub-area of SOFSEM 2018. Each track has its own program chair and program committee for peer review and feedback to authors. Please select the appropriate track of SOFSEM 2018 for your contribution.
SOFSEM 2018 tracks:
- Foundations of Computer Science
Track Co-Chairs: Jan van Leeuwen, Utrecht University, The Netherlands, and Jiri Wiedermann, Academy of Sciences of the Czech Republic, Czech Republic - Software Engineering: Advanced Methods, Tools, Applications (SEMAT)
Track Chair: Stefan Biffl, TU Wien, Austria - Data, Information and Knowledge Engineering
Track Chair: Ladjel Bellatreche, ISAE-ENSMA, France
Foundations of Computer Science
The track is devoted to the recognized core areas of foundational computer science including the theories and application of algorithms and their complexity, automata and languages, computability, data analytics, formal models, intelligent systems, programming semantics, science-inspired computing and foundations of information and software systems. Original contributions showing the value of fundamental research in areas like artificial intelligence and data science are welcome as well.
Topics include (but are not limited to):
- algorithms (incl. game-theoretic, geometric, network, graph, parametrized, exact, approximation, randomized, evolutionary and online algorithms)
- automata, languages, and rewriting systems
- bio-inspired computing
- combinatorial optimization and simulation
- complexity theory (incl. computational, descriptional, fine-grained, and parametrized complexity)
- computability and decidability
- cryptographic algorithms and security
- data structures
- experimental algorithmics
- formal models of systems (incl. concurrent, hybrid, reactive, mobile, timed, and stochastic processes and systems)
- foundations of agent systems and artificial intelligence
- graphs and networks
- machine learning
- non-classical models of computing (incl. computing by nature, cellular automata, neural computing, cognitive computing, nano-computing, self-assembly)
- parallel and distributed computing
- physics of computation
- quantum computation and quantum information
- theory of databases, semi-structured data, and finite model theory
- theory of programming languages
Software Engineering: Advanced Methods, Tools, Applications (SEMAT)
Software is the source of most of the value added in modern software-intensive systems, such as process-centered information systems, web-based systems, mobile systems, games, or intelligent technical systems. The size, complexity, and criticality of software-intensive systems require innovative and economic approaches for their development and evolution. In today's competitive world, software quality is a key to the success and stability of organizations.
The SEMAT track presents and discusses the research of novel and innovative methods and technologies to software engineering, including both software product and development process aspects. Methods and tools that support the improvement of software processes and products aim at significantly increasing both the quality of software-intensive systems and the productivity of software development.
The SEMAT track will bring together researchers and practitioners to share SEMAT innovations and experiences.
Topics of interest include, but are not limited to:
Methods and tools for better software processes
- Process modeling, composition, and enactment/simulation
- Agile/lean development
- User-centered development
- Method engineering
- Quality assurance, inspections, testing
Software architecture of complex software-intensive systems
- Architecture, components, services
- Software reuse, product lines, and software ecosystems
Model-based software engineering methods and tools
- Model-based development
- Model transformations
- Model versioning
- Model and meta-model co-evolution
- Model-based testing
Data-driven improvement of methods, models, and tools
- Quantitative models for development processes and products
- Continuous delivery/integration and DevOps, software process and product evolution with feedback from operation
- Legacy modernization/migration
- Model mining techniques
- Repository mining
- Empirical studies and experimental approaches
Methods and tools for software engineering applications, including the areas
- Process-centered information systems
- Web-based systems
- Mobile systems
- Game development
- Intelligent technical systems (Internet of Things)
In particular, we encourage submissions demonstrating the benefits or limitations of SEMAT approaches through case studies, experiments, and quantitative data.
Data, Information and Knowledge Engineering
The track is devoted to all aspects of eliciting, acquiring, modeling, storing, and managing data, information, and knowledge. Contributions concerning all steps in the development of data and knowledge-intensive systems – theoretical foundations, design, implementation and maintenance techniques – are welcome.
Topics include, but are not limited to:
- Big Data storage, processing and analytics,
- business process modeling, automation, and management
- data and information modeling,
- data and information semantics,
- data integration, data cleaning,
- data intensive applications,
- data warehousing,
- data mining, knowledge discovery and machine learning,
- data privacy and security,
- information retrieval,
- intelligent agents, multi-agent systems,
- knowledge modeling and processing,
- knowledge acquisition and engineering,
- linked data and open data,
- mobile data and information,
- multimedia, spatial, and temporal data and knowledge,
- parallel and distributed data platforms
- probabilistic databases, uncertainty and approximate querying,
- query and natural language processing,
- provenance and trust in data management and knowledge engineering,
- stream data management,
- web and semantic web data and knowledge engineering.
Submission
Authors are encouraged to submit their manuscripts to https://easychair.org/conferences/?conf=sofsem2018.
Further information:
