Formally Validating Translations of Programs into an Intermediate Verification Language

المفاهيم الأساسية

The core message of this paper is to present a novel methodology for automatically generating formal proofs that validate the soundness of front-end translations from a source language (e.g. Viper) to an intermediate verification language (e.g. Boogie) used in practical program verification tools.

الملخص

The paper presents a methodology for formally validating the soundness of front-end translations used in practical program verification tools. The key points are:

Existing work on ensuring front-end soundness is based on idealized implementations, leaving a large gap to the actual translations used in practice. The authors bridge this gap by developing an approach to formally validate the front-end soundness of translations used in existing, practical verifier implementations.

The authors develop a general methodology for the automatic validation of front-end translations based on forward simulation proofs. This methodology is presented for the translation from Viper to Boogie, which exhibits key challenges such as the semantic gap between the languages, diverse translations, and non-locality of translation checks.

The authors instrument the existing Viper-to-Boogie implementation to automatically generate Isabelle proofs justifying the soundness of the translation. These generated proofs can be checked independently in Isabelle, ensuring front-end soundness of the Viper verifier.

The evaluation demonstrates the effectiveness of the approach by generating and checking proofs fully automatically for a diverse set of Viper programs.

As part of the work, the authors provide the first approach to formally deal with a restricted version of Boogie's polymorphic maps.

الإحصائيات

None.

اقتباسات

None.

الرؤى الأساسية المستخلصة من

Towards Trustworthy Automated Program Verifiers

by Gaur... في arxiv.org 04-05-2024

https://arxiv.org/pdf/2404.03614.pdf

استفسارات أعمق

How could this methodology be extended to handle other advanced language features beyond the core subset considered, such as loops, recursive functions, and more complex resource assertions?

To extend this methodology to handle advanced language features, such as loops, recursive functions, and complex resource assertions, several steps can be taken:

Formal Semantics Development: First and foremost, formal semantics for these advanced language features need to be developed. This involves defining the operational semantics for loops, recursive functions, and complex resource assertions in both the source language (e.g., Viper) and the target language (e.g., Boogie).

Decomposition and Abstraction: Similar to the approach taken for the core subset, the methodology can be extended by decomposing the translation of these advanced features into smaller, more manageable components. By abstracting the translation process into generic simulation judgments, the methodology can handle the complexity of these features more effectively.

Instantiation and Validation: Once the formal semantics are in place, the generic simulation judgments can be instantiated to handle the specific translation rules for loops, recursive functions, and complex resource assertions. These instantiations can then be validated through automated proof generation, similar to the approach outlined in the context provided.

Contextual Hypotheses: For more complex features like loops and recursion, contextual hypotheses can be introduced to track dependencies and ensure soundness across different parts of the translation. This will help in handling non-local checks and ensuring the correctness of the translation process.

By following these steps and building upon the existing methodology, the validation process can be extended to cover a broader range of language features, making the automated program verification tool more robust and trustworthy.

How could the insights from this work on front-end translation validation be leveraged to improve the overall trustworthiness of program verification toolchains, beyond just the front-end translation component?

The insights gained from the front-end translation validation methodology can be leveraged to enhance the overall trustworthiness of program verification toolchains in several ways:

End-to-End Soundness: By ensuring the soundness of the front-end translation process, the methodology sets a strong foundation for the entire program verification toolchain. Extending this validation approach to cover the back-end verification components, such as SMT solvers and proof obligation generators, can provide end-to-end soundness guarantees for the toolchain.

Modularity and Maintainability: The decomposition strategies and generic simulation judgments used in the methodology can be applied to other components of the verification toolchain. By modularizing the verification process and abstracting common proof patterns, the toolchain can be more maintainable and adaptable to changes in the underlying technologies.

Validation Automation: The automated proof generation techniques developed for front-end translation validation can be extended to other parts of the toolchain. By automating the validation process for different components, the toolchain can be more reliable and efficient in ensuring the correctness of program verifications.

Cross-Language Compatibility: The methodology can be adapted to handle translations between different intermediate verification languages, not just Viper and Boogie. By generalizing the approach to accommodate diverse languages and verification logics, the toolchain can support a wider range of programming languages and verification requirements.

By applying the insights and techniques from front-end translation validation to other components of the program verification toolchain, the overall trustworthiness and reliability of the toolchain can be significantly improved.

How could the challenges in applying this methodology to front-end translations for other intermediate verification languages, such as Why3, beyond the Boogie case study presented?

Extending the methodology to handle front-end translations for other intermediate verification languages, such as Why3, presents several challenges:

Semantic Variability: Different intermediate verification languages may have unique features and semantics that require specific handling during the translation process. Adapting the methodology to accommodate the semantic differences between Viper and Why3, for example, would require a thorough understanding of the specific language constructs and verification logics involved.

Diverse Translations: Each intermediate verification language may have its own set of translation rules and optimization techniques. Ensuring the soundness of these diverse translations while maintaining modularity and abstraction in the validation process can be challenging.

Non-Local Dependencies: Handling non-local checks and dependencies across different parts of the translation process becomes more complex when dealing with multiple intermediate verification languages. Ensuring that the validation methodology can track and validate these dependencies effectively is crucial for soundness.

Toolchain Integration: Integrating the methodology with existing verification toolchains that use different intermediate verification languages may require additional effort in terms of tool compatibility, data exchange formats, and validation workflows. Ensuring seamless integration and interoperability across different languages is essential for the success of the validation process.

Addressing these challenges would involve a comprehensive analysis of the specific features and requirements of the target intermediate verification language, as well as the development of tailored validation strategies to ensure the soundness and reliability of the front-end translations for languages like Why3.