International Conference on Formal Structures for Computation and Deduction
摘要截稿: 2019-02-08
全文截稿: 2019-02-11
开会时间: 2019-06-24
会议难度:
CCF分类: C类
会议地点: DORTMUND, GERMANY
Overview
FSCD (http://fscd-conference.org/) covers all aspects of formal structures for computation and deduction from theoretical foundations to applications. Building on two communities, RTA (Rewriting Techniques and Applications) and TLCA (Typed Lambda Calculi and Applications), FSCD embraces their core topics and broadens their scope to closely related areas in logics, models of computation (e.g. quantum computing, probabilistic computing, homotopy type theory), semantics and verification in new challenging areas (e.g. blockchain protocols or deep learning algorithms).
Suggested, but not exclusive, list of topics for submission are:
1. Calculi:
• Rewriting systems
• Lambda calculus
• Concurrent calculi
• Logics
• Type theory
• Homotopy type theory
• Logical frameworks
• Quantum calculi
2. Methods in Computation and Deduction:
• Type systems
• Induction and coinduction
• Matching, unification, completion, and orderings
• Strategies
• Tree automata
• Model checking
• Proof search and theorem proving
• Constraint solving and decision procedures
3. Semantics:
• Operational semantics
• Abstract machines
• Game Semantics
• Domain theory
• Categorical models
• Quantitative models
4. Algorithmic Analysis and Transformations of Formal Systems:
• Type inference and type checking
• Abstract interpretation
• Complexity analysis and implicit computational complexity
• Checking termination, confluence, derivational complexity and related properties
• Symbolic computation
5. Tools and Applications:
• Programming and proof environments
• Verification tools
• Proof assistants and interactive theorem provers
• Applications in industry (e.g. design and verification of critical systems)
• Applications in other sciences (e.g. biology)
6. Semantics and verification in new challenging areas:
• Certification
• Security
• Blockchain protocols
• Data bases
• Deep learning and machine learning algorithms
• Planning, . . .