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This paper presents verification-guided development (VGD), a software engineering process we used to build Cedar, a new policy language for expressive, fast, safe, and analyzable authorization. Developing a system with VGD involves writing an executable model of the system and mechanically proving properties about the model; writing production code for the system and using differential random testing (DRT) to check that the production code matches the model; and using property-based testing (PBT) to check properties of unmodeled parts of the production code. Using VGD for Cedar, we can build fast, idiomatic production code, prove our model correct, and find and fix subtle implementation bugs that evade code reviews and unit testing. While carrying out proofs, we found and fixed 4 bugs in Cedar's policy validator, and DRT and PBT helped us find and fix 21 additional bugs in various parts of Cedar.

Cedar is a new authorization policy language designed to be ergonomic, fast, safe, and analyzable. Rather than embed authorization logic in an application's code, developers can write that logic as Cedar policies and delegate access decisions to Cedar's evaluation engine. Cedar's simple and intuitive syntax supports common authorization use-cases with readable policies, naturally leveraging concepts from role-based, attribute-based, and relation-based access control models. Cedar's policy structure enables access requests to be decided quickly. Cedar's policy validator leverages optional typing to help policy writers avoid mistakes, but not get in their way. Cedar's design has been finely balanced to allow for a sound and complete logical encoding, which enables precise policy analysis, e.g., to ensure that when refactoring a set of policies, the authorized permissions do not change. We have modeled Cedar in the Lean programming language, and used Lean's proof assistant to prove important properties of Cedar's design. We have implemented Cedar in Rust, and released it open-source. Comparing Cedar to two open-source languages, OpenFGA and Rego, we find (subjectively) that Cedar has equally or more readable policies, but (objectively) performs far better.

In this article, the dynamics and complexity of a noise induced blood flow system have been investigated. Changes in the dynamics have been recognized by measuring the periodicity over significant parameters. Chaotic as well as non-chaotic regimes have also been classified. Further, dynamical complexity has been studied by phase space based weighted entropy. Numerical results show a strong correlation between the dynamics and complexity of the noise induced system. The correlation has been confirmed by a cross-correlation analysis.

Testing-based methodologies like fuzzing are able to analyze complex software which is not amenable to traditional formal approaches like verification, model checking, and abstract interpretation. Despite enormous success at exposing countless security vulnerabilities in many popular software projects, applications of testing-based approaches have mainly targeted checking traditional safety properties like memory safety. While unquestionably important, this class of properties does not precisely characterize other important security aspects such as information leakage, e.g., through side channels. In this work we extend testing-based software analysis methodologies to two-safety properties, which enables the precise discovery of information leaks in complex software. In particular, we present the ct-fuzz tool, which lends coverage-guided greybox fuzzers the ability to detect two-safety property violations. Our approach is capable of exposing violations to any two-safety property expressed as equality between two program traces. Empirically, we demonstrate that ct-fuzz swiftly reveals timing leaks in popular cryptographic implementations.