RPP: Automatic Proof of Relational Properties by Self-Composition

Self-composition provides a powerful theoretical approach to prove relational properties, i.e. properties relating several program executions, that has been applied to compare two runs of one or similar programs (in secure dataflow properties, code transformations, etc.). This tool demo paper presents RPP, an original implementation of self-composition for specification and verification of relational properties in C programs in the FRAMA-C platform. We consider a very general notion of relational properties invoking any finite number of function calls of possibly dissimilar functions with possible nested calls. The new tool allows the user to specify a relational property, to prove it in a completely automatic way using classic deductive verification, and to use it as a hypothesis in the proof of other properties that may rely on it

Relational Symbolic Execution

Symbolic execution is a classical program analysis technique used to show that programs satisfy or violate given specifications. In this work we generalize symbolic execution to support program analysis for relational specifications in the form of relational properties - these are properties about two runs of two programs on related inputs, or about two executions of a single program on related inputs. Relational properties are useful to formalize notions in security and privacy, and to reason about program optimizations. We design a relational symbolic execution engine, named RelSym which supports interactive refutation, as well as proving of relational properties for programs written in a language with arrays and for-like loops

Fifty years of Hoare's Logic

We present a history of Hoare's logic.Comment: 79 pages. To appear in Formal Aspects of Computin

Deductive verification of cryptographic software

We apply state-of-the art deductive verification tools to check security-relevant properties of cryptographic software, including safety, absence of error propagation, and correctness with respect to reference implementations. We also develop techniques to help us in our task, focusing on methods oriented towards increased levels of automation, in scenarios where there are clear obvious limits to such automation. These techniques allow us to integrate automatic proof tools with an interactive proof assistant, where the latter is used off-line to prove once-and-for-all fundamental lemmas about properties of programs. The techniques developed have independent interest for practical deductive verification in general.Fundação para a Ciência e a Tecnologia (FCT

Thirty-seven years of relational Hoare logic: remarks on its principles and history

Relational Hoare logics extend the applicability of modular, deductive verification to encompass important 2-run properties including dependency requirements such as confidentiality and program relations such as equivalence or similarity between program versions. A considerable number of recent works introduce different relational Hoare logics without yet converging on a core set of proof rules. This paper looks backwards to little known early work. This brings to light some principles that clarify and organize the rules as well as suggesting a new rule and a new notion of completeness.Comment: A version appears in proceedings of ISOLA 2020. Version2: fix typos, minor clarifications, add a citation. Version3: copy edits, add citations on completeness. Version 4: minor corrections. Version 5: restore missing precond in loop rul

Proving Differential Privacy with Shadow Execution

Recent work on formal verification of differential privacy shows a trend toward usability and expressiveness -- generating a correctness proof of sophisticated algorithm while minimizing the annotation burden on programmers. Sometimes, combining those two requires substantial changes to program logics: one recent paper is able to verify Report Noisy Max automatically, but it involves a complex verification system using customized program logics and verifiers. In this paper, we propose a new proof technique, called shadow execution, and embed it into a language called ShadowDP. ShadowDP uses shadow execution to generate proofs of differential privacy with very few programmer annotations and without relying on customized logics and verifiers. In addition to verifying Report Noisy Max, we show that it can verify a new variant of Sparse Vector that reports the gap between some noisy query answers and the noisy threshold. Moreover, ShadowDP reduces the complexity of verification: for all of the algorithms we have evaluated, type checking and verification in total takes at most 3 seconds, while prior work takes minutes on the same algorithms.Comment: 23 pages, 12 figures, PLDI'1