Data Abstraction: A General Framework to Handle Program Verification of Data Structures

被引:1
|
作者
Braine, Julien [1 ,3 ]
Gonnord, Laure [2 ,3 ]
Monniaux, David [4 ]
机构
[1] ENS Lyon, Lyon, France
[2] Univ Claude Bernard Lyon 1, Villeurbanne, France
[3] Univ Lyon, INRIA, ENS Lyon, LIP,CNRS, Lyon, France
[4] Univ Grenoble Alpes, CNRS, Grenoble INP, Inst Engn,VERIMAG, Grenoble, France
来源
STATIC ANALYSIS, SAS 2021 | 2021年 / 12913卷
关键词
Static analysis; Horn clauses; Abstraction;
D O I
10.1007/978-3-030-88806-0_11
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Proving properties on programs accessing data structures such as arrays often requires universally quantified invariants, e.g., "all elements below index i are nonzero". In this article, we propose a general data abstraction scheme operating on Horn formulas, into which we recast previously published abstractions. We show that our instantiation scheme is relatively complete: the generated purely scalar Horn clauses have a solution (inductive invariants) if and only if the original problem has one expressible by the abstraction.
引用
收藏
页码:215 / 235
页数:21
相关论文
共 50 条
  • [1] The NESTOR Framework: How to Handle Hierarchical Data Structures
    Ferro, Nicola
    Silvello, Gianmaria
    [J]. RESEARCH AND ADVANCED TECHNOLOGY FOR DIGITAL LIBRARIES, PROCEEDINGS, 2009, 5714 : 215 - 226
  • [2] A Network Data Abstraction Method for Data Set Verification
    Cho, Jaeik
    Choi, Kyuwon
    Shon, Taeshik
    Moon, Jongsub
    [J]. SECURE AND TRUST COMPUTING, DATA MANAGEMENT, AND APPLICATIONS, 2011, 186 : 54 - +
  • [3] Verification of Statecharts Using Data Abstraction
    Helke, Steffen
    Kammueller, Florian
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2016, 7 (01) : 571 - 583
  • [4] A general framework for adaptive processing of data structures
    Frasconi, P
    Gori, M
    Sperduti, A
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 1998, 9 (05): : 768 - 786
  • [5] General framework for adaptive processing of data structures
    Universita di Firenze, Firenze, Italy
    [J]. IEEE Trans Neural Networks, 5 (768-786):
  • [6] A Framework to Handle Data Heterogeneity Contextual to Medical Big Data
    Sindhu, C. S.
    Hegde, Nagaratna P.
    [J]. 2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH (ICCIC), 2015, : 338 - 344
  • [7] Tensors: An abstraction for general data processing
    Koutsoukos, Dimitrios
    Nakandala, Supun
    Karanasos, Konstantinos
    Saur, Karla
    Alonso, Gustavo
    Interlandi, Matteo
    [J]. PROCEEDINGS OF THE VLDB ENDOWMENT, 2021, 14 (10): : 1797 - 1804
  • [8] Predicate Abstraction for Linked Data Structures
    Bakst, Alexander
    Jhala, Ranjit
    [J]. VERIFICATION, MODEL CHECKING, AND ABSTRACT INTERPRETATION, VMCAI 2016, 2016, 9583 : 65 - 84
  • [9] USING A DATABASE PROGRAM TO HANDLE QUALITATIVE DATA
    BURNARD, P
    [J]. NURSE EDUCATION TODAY, 1994, 14 (03) : 228 - 231
  • [10] Combining Control and Data Abstraction in the Verification of Hybrid Systems
    Briand, Xavier
    Jeannet, Bertrand
    [J]. IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2010, 29 (10) : 1481 - 1494