会议信息

MEMOCODE 2026: ACM-IEEE International Symposium on Formal Methods and Models for System Design

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MEMOCODE
截稿日期:
2026-05-04
通知日期:
2026-07-10
会议日期:
2026-10-08
会议地点:
Barcelona, Spain
届数:
24
CCF: C   ICORE: C   浏览: 28976   关注: 0   参加: 0

征稿

MEMOCODE 2026 (ACM-IEEE International Symposium on Formal Methods and Models for System Design) is a CCF C / ICORE C conference held in Barcelona, Spain on 2026-10-08. The paper submission deadline is 2026-05-04. Acceptance notifications are sent on 2026-07-10.

Topics of Interest MEMOCODE solicits research papers on formal methods in system design that address the foundations, engineering methods, tools, or experimental case studies. Research areas of interest include, but are not limited to, the following: Modeling Languages, Methods, and Tools Programming languages and models; software and system modeling languages; architecture and high-level hardware description languages; synchronous languages; timing models; logical execution time (LET); model synthesis methods; model transformation methods; compilation methods. Formal Methods and Tools Correct-by-construction methods; compilers and synthesis tools; contract-based design and verification; static, dynamic, and type theoretic analysis; verification; validation; probabilistic model checking; test generation; refinement-based and compositional approaches to design and verification. Models and Methods for Developing Critical Systems Fault-tolerant systems; security-critical and safety-critical systems; cyber-physical systems; hybrid systems; autonomous systems; self-adapting systems; systems that merge humans, artificial intelligence, and cyber-physical systems; societal-scale cyber-physical systems, such as connected vehicles and smart grids. Quantitative/Qualitative Reasoning Power/performance/cost/latency estimation methods; system models for quantitative design space exploration. Formal Methods and Models in Practice Design case studies; empirical case studies. AI for Critical Systems AI modelling; AI-assisted reasoning; AI-guided verification; AI-assisted testing; verification of AI systems; combining AI with classical methods.
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