Static Analysis (eBook, PDF)

31st International Symposium, SAS 2024, Pasadena, CA, USA, October 20-22, 2024, Proceedings
Redaktion: Giacobazzi, Roberto; Gorla, Alessandra

• Format: PDF

Produktbeschreibung

This book constitutes the refereed proceedings of the 31st International Static Analysis Symposium, SAS 2024, held in Pasadena, CA, USA, in October 2024.

Static analysis is widely recognized as a fundamental tool for program verification, bug detection, compiler optimization, program understanding, and software maintenance. The papers presented in this book deal with theoretical, practical and application advances in this area.

The 18 papers included here were carefully reviewed and selected from 45 submissions.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 464
• Erscheinungstermin: 20. Januar 2025
• Englisch
• ISBN-13: 9783031747762
• Artikelnr.: 72890134

Inhaltsangabe

Static Analysis of Quantum Programs.- Trace Partitioning as an Optimization Problem.- On the Role of Cognizance in Responsibility.- Lift-offline: Instruction Lifter Generators.- Full Control-Flow Sensitivity for Definitional Interpreters.- Synthesizing Abstract Transformers for Reduced-Product Domains.- Abstract Interpretation of ReLU Neural Networks with Optimizable Polynomial Relaxations.- Should We Balance? Towards Formal Verification of the Linux Kernel Scheduler.- GoGuard: Efficient Static Blocking Bug Detection for Go.- Verification of programs with ADTs using Shallow Horn Clauses.- Quantitative Static Timing Analysis.- Under-approximating Memory Abstractions.- Robustness Verification of Multi-Label Neural Network Classifiers.- An Order Theory Framework of Recurrence Equations for Static Cost Analysis - Dynamic Inference of Non-Linear Inequality Invariants.- Fixing Latent Unsound Abstract Operators in the eBPF Verifier of the Linux Kernel.- ConstraintFlow: A Declarative DSL for Easy Development of DNN Certifiers.- BinSub: The Simple Essence of Polymorphic Type Inference for Machine Code.- Verifying components of Arm® Confidential Computing Architecture with ESBMC.