This book constitutes the refereed proceedings of the 29th International Symposium on Model Checking Software, SPIN 2023, held in Paris, France, during April 2627, 2023.
The 9 full papers and 2 short papers included in this book were carefully reviewed and selected from 21 submissions. They were organized in topical sections as follows: binary decision diagrams, concurrency, testing, synthesis, explicit-state model checking.

Klappentext

Binary Decision Diagrams.- Efficient Implementation of LIMDDs for Quantum Circuit\ Simulation.- ParaGnosis: A Tool for Parallel Knowledge Compilation.- Concurrency.- Model Checking Futexes.- Sound Concurrent Traces for Online Monitoring.- Testing.- Efficient Trace Generation for Rare-Event Analysis in Chemical Reaction Networks.- Accelerating black box testing with light-weight learning.- Synthesis.- WikiCoder: Learning to Write Knowledge-Powered Code.- Provable Correct and Adaptive Simplex Architecture for Bounded-Liveness Properties.- Explicit-state Model Checking.- Elimination of Detached Regions in Dependency Graph Verification.- Potency-Based Heuristic Search with Randomness for Explicit Model Checking.- GPUexplore 3.0: GPU Accelerated State Space Exploration for Concurrent Systems with Data.

Inhalt
Binary Decision Diagrams .- Efficient Implementation of LIMDDs for Quantum Circuit\ Simulation.- ParaGnosis: A Tool for Parallel Knowledge Compilation.- Concurrency .- Model Checking Futexes.- Sound Concurrent Traces for Online Monitoring.- Testing .- Efficient Trace Generation for Rare-Event Analysis in Chemical Reaction Networks.- Accelerating black box testing with light-weight learning.- Synthesis .- WikiCoder: Learning to Write Knowledge-Powered Code.- Provable Correct and Adaptive Simplex Architecture for Bounded-Liveness Properties.- Explicit-state Model Checking .- Elimination of Detached Regions in Dependency Graph Verification.- Potency-Based Heuristic Search with Randomness for Explicit Model Checking.- GPUexplore 3.0: GPU Accelerated State Space Exploration for Concurrent Systems with Data.