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NASA Formal Methods

Overview of attention for book
Cover of 'NASA Formal Methods'

Table of Contents

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    Book Overview
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    Chapter 1 Learning-Based Testing of an Industrial Measurement Device
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    Chapter 2 $$\textsf {ML}_{\nu }$$ : A Distributed Real-Time Modal Logic
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    Chapter 3 Local Reasoning for Parameterized First Order Protocols
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    Chapter 4 Generation of Signals Under Temporal Constraints for CPS Testing
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    Chapter 5 Traffic Management for Urban Air Mobility
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    Chapter 6 Towards Full Proof Automation in Frama-C Using Auto-active Verification
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    Chapter 7 Using Standard Typing Algorithms Incrementally
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    Chapter 8 Using Binary Analysis Frameworks: The Case for BAP and angr
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    Chapter 9 Automated Backend Selection for ProB Using Deep Learning
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    Chapter 10 Optimizing a Verified SAT Solver
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    Chapter 11 Model Checking of Verilog RTL Using IC3 with Syntax-Guided Abstraction
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    Chapter 12 Towards a Two-Layer Framework for Verifying Autonomous Vehicles
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    Chapter 13 Clausal Proofs of Mutilated Chessboards
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    Chapter 14 Practical Causal Models for Cyber-Physical Systems
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    Chapter 15 Extracting and Optimizing Formally Verified Code for Systems Programming
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    Chapter 16 Structured Synthesis for Probabilistic Systems
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    Chapter 17 Design and Runtime Verification Side-by-Side in eTrice
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    Chapter 18 Data Independence for Software Transactional Memory
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    Chapter 19 Transaction Protocol Verification with Labeled Synchronization Logic
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    Chapter 20 Symbolic Model Checking of Weighted PCTL Using Dependency Graphs
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    Chapter 21 Composing Symmetry Propagation and Effective Symmetry Breaking for SAT Solving
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    Chapter 22 Formal Methods Assisted Training of Safe Reinforcement Learning Agents
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    Chapter 23 Formalizing CNF SAT Symmetry Breaking in PVS
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    Chapter 24 Fly-by-Logic: A Tool for Unmanned Aircraft System Fleet Planning Using Temporal Logic
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    Chapter 25 A Mixed Real and Floating-Point Solver
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    Chapter 26 Online Parametric Timed Pattern Matching with Automata-Based Skipping
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Title
NASA Formal Methods
Published by
Springer International Publishing, August 2019
DOI 10.1007/978-3-030-20652-9
ISBNs
978-3-03-020651-2, 978-3-03-020652-9
Editors

Badger, Julia M., Rozier, Kristin Yvonne

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 25%
Professor 1 25%
Student > Ph. D. Student 1 25%
Student > Bachelor 1 25%
Readers by discipline Count As %
Computer Science 2 50%
Unspecified 1 25%
Decision Sciences 1 25%