More Flexible Object Invariants with Less Specification Overhead

Huster, Stefan; Heckeler, Patrick; Eichelberger, Hanno; Ruf, Jürgen; Burg, Sebastian; Kropf, Thomas

doi:10.1007/978-3-319-10431-7_25

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…On exit, re-validation is only needed for the intersection. Later work [25] generates the sets automatically from visibility modifiers. [3] addresses invariant issues in a language with contracts treating inter-object relations as first-class citizens.…”

Section: Previous Workmentioning

confidence: 99%

The concept of class invariant in object-oriented programming

Meyer¹,

Arkadova²,

Kogtenkov³

2021

Preprint

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Class invariants -consistency constraints preserved by every operation on objects of a given type -are fundamental to building and understanding object-oriented programs. They should also be a key help in verifying them, but turn out instead to raise major verification challenges which have prompted a significant literature with, until now, no widely accepted solution. The present work introduces a general proof rule meant to address invariant-related issues and allow verification tools benefit from invariants.It first clarifies the notion of invariant and identify the three problems: callbacks, furtive access and reference leak. As an example, the 2016 Ethereum DAO bug, in which $50 million were stolen, resulted from a callback invalidating an invariant.The discussion starts with a "Simple Model" and an associated proof rule, demonstrating its soundness. It then removes one by one the three assumptions of the Simple Model, each removal bringing up one of the three issues, and introduces the corresponding adaptation to the proof rule. The final version of the rule can tackle tricky examples, including "challenge problems" listed in the literature.

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Section: Previous Workmentioning

confidence: 99%

The concept of class invariant in object-oriented programming

Meyer¹,

Arkadova²,

Kogtenkov³

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…We apply Microsoft Code Contracts as formal verification framework and IntelliTest as automatic test case generation framework. To get detailed POG information, we have implemented our own POG generator based on [3] and [13]. The results are summarised in Table 2.…”

Section: Case Studiesmentioning

confidence: 99%

Using Robustness Testing to Handle Incomplete Verification Results When Combining Verification and Testing Techniques

Huster

Ströbele

Ruf

et al. 2017

Testing Software and Systems

Self Cite

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Modular verification and dynamic testing techniques are often combined to validate complex software systems. Formal verification is used to cover all input spaces and program paths. However, due to the high complexity of modern software systems, they might not achieve complete verification results. Dynamic testing techniques can easily be applied to any type of software. Current approaches use them to handle incomplete verification results by validating unverified sections. This way of combining verification and testing ignores the fact that tests can only be used to show the presence of errors, but not their absence. Undiscovered errors pose the risk to trigger further errors in vulnerable code sections. Vulnerable sections are modularly verified, but depend on the guarantees of the tested code. We include robustness testing to analyse the influence of undiscovered errors. The generated robustness tests simulate failed guarantees within the tested code. The triggered response to those simulated errors helps the developer in adding additional error handling code. This makes the system more robust against undiscovered errors and guards it against uncontrolled crashes and unexpected behaviour in case of software failures. In the second part of this paper, we introduce a reference-architecture to generate and apply robustness tests. This architecture has been applied to multiple case studies and helped to identify potential errors yet undiscovered by generated test cases.

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The Concept of Class Invariant in Object-oriented Programming

Meyer,

Arkadova,

Kogtenkov

2024

Form. Asp. Comput.

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Class invariants — consistency constraints preserved by every operation on objects of a given type — are fundamental to building, understanding and verifying object-oriented programs. For verification, however, they raise difficulties, which have not yet received a generally accepted solution. The present work introduces a proof rule meant to address these issues and allow verification tools to benefit from invariants. It clarifies the notion of invariant and identifies the three associated problems: callbacks, furtive access and reference leak. As an example, the 2016 Ethereum DAO bug, in which $50 million were stolen, resulted from a callback invalidating an invariant. The discussion starts with a simplified model of computation and an associated proof rule, demonstrating its soundness. It then removes one by one the three simplifying assumptions, each removal raising one of the three issues, and leading to a corresponding adaptation to the proof rule. The final version of the rule can tackle tricky examples, including “challenge problems” listed in the literature.

show abstract

More Flexible Object Invariants with Less Specification Overhead

Cited by 3 publications

References 11 publications

The concept of class invariant in object-oriented programming

The concept of class invariant in object-oriented programming

Using Robustness Testing to Handle Incomplete Verification Results When Combining Verification and Testing Techniques

The Concept of Class Invariant in Object-oriented Programming

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