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Computer Aided Verification

29th International Conference, CAV 2017, Heidelberg, Germany, July 24-28, 2017, Proceedings, Part I

  • Conference proceedings
  • © 2017

Overview

Editors:
  1. Rupak Majumdar

    1. Max Planck Institute for Software Systems, Kaiserslautern, Germany

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  2. Viktor Kunčak

    1. School of Computer and Communication Sciences, EPFL - IC - LARA, Lausanne, Switzerland

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10426)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Included in the following conference series:

Conference proceedings info: CAV 2017.

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Table of contents (29 papers)

  1. Front Matter

    Pages I-XIX
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  2. Invited Contributions

    1. Front Matter

      Pages 1-1
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    2. Safety Verification of Deep Neural Networks

      • Xiaowei Huang, Marta Kwiatkowska, Sen Wang, Min Wu
      Pages 3-29

    3. Program Verification Under Weak Memory Consistency Using Separation Logic

      • Viktor Vafeiadis
      Pages 30-46

    4. The Power of Symbolic Automata and Transducers

      • Loris D’Antoni, Margus Veanes
      Pages 47-67

    5. Maximum Satisfiability in Software Analysis: Applications and Techniques

      • Xujie Si, Xin Zhang, Radu Grigore, Mayur Naik
      Pages 68-94

  3. Probabilistic Systems

    1. Front Matter

      Pages 95-95
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    2. Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks

      • Guy Katz, Clark Barrett, David L. Dill, Kyle Julian, Mykel J. Kochenderfer
      Pages 97-117

    3. Automated Recurrence Analysis for Almost-Linear Expected-Runtime Bounds

      • Krishnendu Chatterjee, Hongfei Fu, Aniket Murhekar
      Pages 118-139

    4. Markov Automata with Multiple Objectives

      • Tim Quatmann, Sebastian Junges, Joost-Pieter Katoen
      Pages 140-159

    5. Ensuring the Reliability of Your Model Checker: Interval Iteration for Markov Decision Processes

      • Christel Baier, Joachim Klein, Linda Leuschner, David Parker, Sascha Wunderlich
      Pages 160-180

    6. Repairing Decision-Making Programs Under Uncertainty

      • Aws Albarghouthi, Loris D’Antoni, Samuel Drews
      Pages 181-200

    7. Value Iteration for Long-Run Average Reward in Markov Decision Processes

      • Pranav Ashok, Krishnendu Chatterjee, Przemysław Daca, Jan Křetínský, Tobias Meggendorfer
      Pages 201-221

  4. Data Driven Techniques

    1. Front Matter

      Pages 223-223
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    2. STLInspector: STL Validation with Guarantees

      • Hendrik Roehm, Thomas Heinz, Eva Charlotte Mayer
      Pages 225-232

    3. Learning a Static Analyzer from Data

      • Pavol Bielik, Veselin Raychev, Martin Vechev
      Pages 233-253

    4. Synthesis with Abstract Examples

      • Dana Drachsler-Cohen, Sharon Shoham, Eran Yahav
      Pages 254-278

    5. Data-Driven Synthesis of Full Probabilistic Programs

      • Sarah Chasins, Phitchaya Mangpo Phothilimthana
      Pages 279-304

    6. Logical Clustering and Learning for Time-Series Data

      • Marcell Vazquez-Chanlatte, Jyotirmoy V. Deshmukh, Xiaoqing Jin, Sanjit A. Seshia
      Pages 305-325

  5. Runtime Verification

    1. Front Matter

      Pages 327-327
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Other volumes

  1. Computer Aided Verification

  2. Computer Aided Verification

Keywords

About this book

The two-volume set LNCS 10426 and LNCS 10427 constitutes the refereed proceedings of the 29th International Conference on Computer Aided Verification, CAV 2017, held in Heidelberg, Germany, in July 2017.

The total of 50 full and 7 short papers presented  together with 5 keynotes and tutorials in the proceedings was carefully reviewed and selected from 191 submissions. 

The CAV conference series is dedicated to the advancement of the theory and practice of computer-aided formal analysis of hardware and software systems. The conference covers the spectrum from theoretical results to concrete applications, with an emphasis on practical verification tools and the algorithms and techniques that are needed for their implementation.

Editors and Affiliations

  • Max Planck Institute for Software Systems, Kaiserslautern, Germany

    Rupak Majumdar

  • School of Computer and Communication Sciences, EPFL - IC - LARA, Lausanne, Switzerland

    Viktor Kunčak

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