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Darius Foo

Publications and source records attributed to Darius Foo.

4 recordsLinked to original sources

Type Safety via Hoare Logic with Separation and Pure Types

Type safety has traditionally rested on carefully crafted type systems, under the motto "well-typed programs cannot go wrong". Modern demands push type systems past this basic guarantee: toward memory safety (e.g., Rust), stronger data-structure invariants (e.g., GADTs), and broader typability (e.g., MLstruct). The motto absorbs each such property by enlarging the set of states deemed "wrong", but collapses them into one binary verdict: heap ownership, flow-sensitive changes to a variable's type, and the gap between a recoverable and a fatal error are relational, stateful facts about intermediate states that one verdict cannot tell apart. Worse, each demand typically brings its own extension, making it hard to say what each guarantees or how they combine. Floyd-Hoare logic supplies a unified foundation. We present a framework for type-safety verification built from four ingredients: (i) case specifications for path-sensitive typing; (ii) separation types, inspired by separation logic, for flow-sensitive type mutation and must-aliasing; (iii) a disciplined distinction between Err (runtime error values our types track) and Abrt (compile-time errors), yielding the refined motto well-typed programs must never abort; and (iv) type predicates for data-structure invariants. Since all four are ordinary types in one Boolean algebra rather than separate extensions, the framework subsumes both GADTs and liquid types within one type logic, spanning weak specifications that tolerate Err to strong ones that eliminate it. Subtyping reduces to one decidable emptiness test, so a single lightweight procedure serves the whole framework with no SMT oracle in its trusted base. We formalise the Hoare rules and prove soundness in a machine-checked Lean mechanisation; by proof reflection it yields a self-certifying type-checker, evaluated on a benchmark suite.

cs.PL

Staged Specification Logic for Verifying Higher-Order Imperative Programs (Technical Report)

Higher-order functions and imperative states are language features supported by many mainstream languages. Their combination is expressive and useful, but complicates specification and reasoning, due to the use of yet-to-be-instantiated function parameters. One inherent limitation of existing specification mechanisms is its reliance on only two stages: an initial stage to denote the precondition at the start of the method and a final stage to capture the postcondition. Such two-stage specifications force abstract properties to be imposed on unknown function parameters, leading to less precise specifications for higher-order methods. To overcome this limitation, we introduce a novel extension to Hoare logic that supports multiple stages for a call-by-value higher-order language with ML-like local references. Multiple stages allow the behavior of unknown function-type parameters to be captured abstractly as uninterpreted relations; and can also model the repetitive behavior of each recursion as a separate stage. In this paper, we define our staged logic with its semantics, prove its soundness and develop a new automated higher-order verifier, called Heifer, for a core ML-like language.

cs.PL

Tracing OCaml Programs

This presentation will cover a framework for application-level tracing of OCaml programs. We outline a solution to the main technical challenge, which is being able to log typed values with lower overhead and maintenance burden than existing approaches. We then demonstrate the tools we have built around this for visualizing and exploring executions.

cs.PL

The Dynamics of Software Composition Analysis

Developers today use significant amounts of open source code, surfacing the need for ways to automatically audit and upgrade library dependencies, and giving rise to the subfield of Software Composition Analysis (SCA). SCA products are concerned with three tasks: discovering dependencies, checking the reachability of vulnerable code for false positive elimination, and automated remediation. The latter two tasks rely on call graphs of application and library code to check whether vulnerability-specific sinks identified in libraries are used by applications. However, statically-constructed call graphs introduce both false positives and false negatives on real-world projects. In this paper, we develop a novel, modular means of combining call graphs derived from both static and dynamic analysis to improve the performance of false positive elimination. Our experiments indicate significant performance improvements.

cs.SE