## Combining theorem proving with static analysis for data structure consistency (2004)

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Venue: | In International Workshop on Software Verification and Validation (SVV 2004 |

Citations: | 22 - 16 self |

### BibTeX

@INPROCEEDINGS{Zee04combiningtheorem,

author = {Karen Zee and Patrick Lam and Viktor Kuncak and Martin Rinard},

title = {Combining theorem proving with static analysis for data structure consistency},

booktitle = {In International Workshop on Software Verification and Validation (SVV 2004},

year = {2004}

}

### OpenURL

### Abstract

Abstract We describe an approach for combining theorem proving techniques with static analysis to analyze data structure consistency for programs that manipulate heterogeneous data structures. Our system uses interactive theorem proving and shape analysis to verify that data structure implementations conform to set interfaces. A simpler static analysis then uses the verified set interfaces to verify properties that characterize how shared objects participate in multiple data structures. We have successfully applied this technique to several programs and found that theorem proving within circumscribed regions of the program combined with static analysis enables the verification of large-scale program properties.

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Citation Context ...and combine the decision procedures for different properties using NelsonOppen techniques [29,32] and their generalizations such as [36–38]. Theorem provers based on these principles include Simplify =-=[9]-=-, Verifun [11], and CVC [34]. Our system can take advantage of combined decision procedures, but also allows specialized analyses that use customized internal representations of dataflow facts. 8 Conc... |

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Citation Context ...onjunction with other plugins. We identified data structures that implement dynamically changing sets as good candidates upon which to focus theorem proving effort. Using the ideas of data refinement =-=[8,16]-=-, we can naturally specify the preconditions and postconditions on such data structures using formulas in the boolean algebra of sets. We can verify once and for all that the data structure implementa... |

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Citation Context ...onjunction with other plugins. We identified data structures that implement dynamically changing sets as good candidates upon which to focus theorem proving effort. Using the ideas of data refinement =-=[8,16]-=-, we can naturally specify the preconditions and postconditions on such data structures using formulas in the boolean algebra of sets. We can verify once and for all that the data structure implementa... |

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Citation Context ...he decision procedures for different properties using NelsonOppen techniques [29,32] and their generalizations such as [36–38]. Theorem provers based on these principles include Simplify [9], Verifun =-=[11]-=-, and CVC [34]. Our system can take advantage of combined decision procedures, but also allows specialized analyses that use customized internal representations of dataflow facts. 8 Concluding Remarks... |

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Citation Context ...d, theorem proving techniques can in principle verify arbitrarily complicated consistency properties; this statement especially applies to interactive theorem provers such as Isabelle [31] and Athena =-=[1]-=- that allow writing general mathematical statements about program state. The difficulty in using theorem proving tools is that their application may require manual effort and familiarity with their be... |

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Citation Context ...n then carries out a dataflow analysis over boolean formulas for each procedure, updating set contents after procedure calls and flag field mutations. The flag plugin uses the MONA decision procedure =-=[18]-=- as well as a range of formula simplifications [23] to perform operations on these boolean formulas. The PALE analysis plugin [27] implements a shape analysis that can verify detailed properties of co... |

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Citation Context ...ions of Decidable Theories. One possible alternative to combining analyses is to use a single analysis engine and combine the decision procedures for different properties using NelsonOppen techniques =-=[29,32]-=- and their generalizations such as [36–38]. Theorem provers based on these principles include Simplify [9], Verifun [11], and CVC [34]. Our system can take advantage of combined decision procedures, b... |

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Citation Context ...dule. Free variables of these formulas denote abstract sets declared in specification sections. The expressive power of such formulas is the first-order theory of boolean algebras, which is decidable =-=[19,26]-=-. The decidability of the specification language ensures that analysis plugins can precisely propagate the specified relations between the abstract sets. 3.3 Analysis Overview The analysis of a module... |

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Citation Context ... theorem provers include Athena [1] and HOL [30]. The ACL2 [17] system can apply theorem-proving and term rewriting techniques to verify properties of large-scale systems, among them software systems =-=[28]-=-. Combinations of Decidable Theories. One possible alternative to combining analyses is to use a single analysis engine and combine the decision procedures for different properties using NelsonOppen t... |

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Citation Context ...(p in InList) modifies InList ensures InList’ = InList + p; proc remove(p : Process) requires p in InList modifies InList ensures InList’ = InList - p; Figure 4: Running List Specification Module gin =-=[23]-=- to verify the conformance of the linked list to the set interface in Figure 4. 2.3 Scheduler Module Figure 5 presents the Scheduler implementation module. This module contributes a status field to Pr... |

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Citation Context ...ng fields while allowing modules to share objects. When the program creates an object with format T, the newly-created object contains the fields contributed to format T by all modules in the program =-=[6]-=-. A simple type checker for the implementation language statically ensures that each module accesses only fields that it has contributed to an object. Note that no analysis plugin needs the full layou... |

14 |
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Citation Context ...dule. Free variables of these formulas denote abstract sets declared in specification sections. The expressive power of such formulas is the first-order theory of boolean algebras, which is decidable =-=[19,26]-=-. The decidability of the specification language ensures that analysis plugins can precisely propagate the specified relations between the abstract sets. 3.3 Analysis Overview The analysis of a module... |

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10 | On modular pluggable analyses using set interfaces
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Citation Context ... means practical. The specification of a procedure is derived from the abstract requires, modifies, and ensures clauses using the definitions of abstract sets as well as the representation invariants =-=[21]-=-. We also require that a procedure never violate the preconditions of its callees. Figure 10 illustrates our analysis of the Scheduler module from our example: to ensure that Scheduler meets its speci... |

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Uber m"ogligkeiten im relativkalk"ul
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Citation Context ...dule. Free variables of these formulas denote abstract sets declared in specification sections. The expressive power of such formulas is the first-order theory of boolean algebras, which is decidable =-=[19, 26]-=-. The decidability of the specification language ensures that analysis plugins can precisely propagate the specified relations between the abstract sets. 3.3 Analysis Overview The analysis of a module... |

1 | Verifying set interfaces based on object field values - Lam, Kuncak, et al. - 2005 |