会议信息

SPIN 2026: International SPIN Symposium on Model Checking of Software

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截稿日期:
2026-01-15
通知日期:
2026-03-05
会议日期:
2026-04-15
会议地点:
Torino, Italy
届数:
32
CCF: C   浏览: 34113   关注: 15   参加: 3

征稿

SPIN 2026 (International SPIN Symposium on Model Checking of Software) is a CCF C conference held in Torino, Italy on 2026-04-15. The paper submission deadline is 2026-01-15. Acceptance notifications are sent on 2026-03-05.

The SPIN symposium aims at bringing together researchers and practitioners interested in automated tool-based techniques for the analysis of software as well as models of software, for the purpose of verification and validation. The symposium specifically focuses on concurrent software but does not exclude the analysis of sequential software. Submissions are solicited on theoretical results, novel algorithms, tool development, and empirical evaluation. The SPIN symposium originated as a workshop focusing on explicit state model checking, specifically as related to the SPIN model checker. However, over the years it has evolved to a broadly-scoped symposium for software analysis using any automated techniques, including model checking, automated theorem proving, and symbolic execution. An overview of the previous SPIN symposia (and early workshops) can be found at: https://spinroot.com/spin/Workshops/. Previous Proceedings of SPIN can be found at Springer’s website. Topics Topics of interest include, but are not limited to: Formal verification techniques for automated analysis of (concurrent) software/hardware, including: Model checking Deductive verification Automated theorem proving, including SAT and SMT Abstraction and symbolic execution techniques Static analysis and abstract interpretation Modular and compositional verification techniques Verification of timed, probabilistic, hybrid, and quantum systems Automated testing using advanced analysis techniques Program synthesis Derivation of specifications, test cases etc. via formal analysis Formal specification languages, temporal logic, design-by-contract Formal analysis of learned and learning systems Formal and Hybrid Methods in Artificial Intelligence Verification of Spatial and Spatio-Temporal Systems Any combination of the above Application and/or engineering of verification tools, including: Case studies of interesting systems or with interesting results Implementation of novel verification tools Benchmarks and comparative studies for verification tools Verification tools using modern hardware, e.g.: multi-core CPU, GPU, TPU, cloud, and quantum
由 Dou Sun 最后更新于

录用率

平均录用率: 45.6% 9 年间 (2000–2008).

年份提交数录用数录用率(%)
2008381847.4%
2007311445.2%
2006441943.2%
2005451533.3%
2004481939.6%
2003301446.7%
2002201050%
2001261350%
2000311754.8%

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相关期刊

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