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Computing and Software Science
Runtime Verification Past Experiences and Future Projections
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Author(s):
Klaus Havelund
,
Giles Reger
,
Grigore Roşu
Publication date
(Online):
October 05 2019
Publisher:
Springer International Publishing
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An Overview of AspectJ
Gregor Kiczales
,
Erik Hilsdale
,
Jim Hugunin
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(2001)
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Model checking JAVA programs using JAVA PathFinder
Klaus Havelund
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Thomas Pressburger
(2000)
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The Temporal Rover and the ATG Rover
Doron Drusinsky
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Book Chapter
Publication date (Print):
2019
Publication date (Online):
October 05 2019
Pages
: 532-562
DOI:
10.1007/978-3-319-91908-9_25
SO-VID:
7de9da94-b062-4680-b94b-329e91ff25a7
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Book chapters
pp. 3
Computation and Complexity
pp. 9
Some Estimated Likelihoods for Computational Complexity
pp. 27
Computing in Combinatorial Optimization
pp. 48
Computational Social Choice: The First Ten Years and Beyond
pp. 66
Geometric Optimization Revisited
pp. 85
10 Reasons to Get Interested in Graph Drawing
pp. 105
Sublinear-Time Algorithms for Approximating Graph Parameters
pp. 123
Dynamic Erdős-Rényi Graphs
pp. 141
Wireless Network Algorithmics
pp. 161
Green Computing Algorithmics
pp. 184
Brain Computation: A Computer Science Perspective
pp. 200
Rating Computer Science via Chess
pp. 217
Knowledge Harvesting: Achievements and Challenges
pp. 239
Methods, Languages and Tools for Future System Development
pp. 250
The Next 7000 Programming Languages
pp. 283
Multi-Mode DAE Models - Challenges, Theory and Implementation
pp. 311
Language-Driven Engineering: From General-Purpose to Purpose-Specific Languages
pp. 345
Deductive Software Verification: From Pen-and-Paper Proofs to Industrial Tools
pp. 374
Static Analysis for Proactive Security
pp. 393
Software Architecture of Modern Model Checkers
pp. 420
The 10,000 Facets of MDP Model Checking
pp. 452
Continuous-Time Models for System Design and Analysis
pp. 478
Statistical Model Checking
pp. 505
Automated Software Test Generation: Some Challenges, Solutions, and Recent Advances
pp. 532
Runtime Verification Past Experiences and Future Projections
pp. 563
Combining Black-Box and White-Box Techniques for Learning Register Automata
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