Theoretical Aspects of Software Engineering de Cristina David

Theoretical Aspects of Software Engineering: 17th International Symposium, TASE 2023, Bristol, UK, July 4–6, 2023, Proceedings: Lecture Notes in Computer Science, cartea 13931

Cristina David

Meng Sun

en Limba Engleză Paperback – 28 iun 2023

This book constitutes the proceedings of the 17th International Conference on Theoretical Aspects of Software Engineering, TASE 2023, held in Bristol, UK, July 4–6, 2023.

The 19 full papers and 2 short papers included in this book were carefully reviewed and selected from 49 submissions. They cover the following areas: distributed and concurrent systems; cyber-physical systems; embedded and real-time systems; object-oriented systems; quantum computing; formal verification and program semantics; static analysis; formal methods; verification and testing for AI systems; and AI for formal methods.

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Cuprins

Systems with Runtime Assurance Architectures.- Continuation-Passing Style into Static Single Assignment Form.- Framework based on Reinforcement Learning.- Decomposing Synthesized Strategies for Reactive Multi-agent Reinforcement Learning.- Based Embedded Software Design.- Probabilistic Contracts Using Timed Automata.- Asynchronous test equivalence over timed processes.- Protocol Conformance with Choreographic PlusCal.- Verifying Chips Design at RTL Level.- Maximizing Reachability Probabilities in Rectangular Automata with Random Clocks.- A hierarchical spatial logic for knowledge sharing and fusion in intelligent connected vehicle cooperation.- VeriLin: A Linearizability Checker for Large-Scale Concurrent Objects.- Identifying Minimal Changes in the Zone Abstract Domain.- idDL2DL - Interval syntax to DL.- Safety Verification for Neural Networks Based on Set-boundary Analysis.- Approximately learning quantum automata.- View-Based Axiomatic Reasoning for PSO.- Resource Sensitive Workflow Models.- MTCD: An Efficient Cloning Detection Technique Based on Method Table.- Stepwise development of paraconsistent processes.- Detecting API-Misuse based on Pattern Mining via API Usage Graph with Parameters.