We propose a new semantics for shared-memory parallel programs that gives strong guarantees even in the presence of data races. Our local data race freedom property guarantees that all data-race-free portions of programs exhibit sequential semantics. We provide a straightforward operational semantics and an equivalent axiomatic model, and evaluate an implementation for the OCaml programming language. Our evaluation demonstrates that it is possible to balance a comprehensible memory model with a reasonable (no overhead on x86,~0.6% on ARM) sequential performance trade-off in a mainstream programming language.

We present a type system combining subtyping and ML-style parametric polymorphism. Unlike previous work, our system supports type inference and has compact principal types. We demonstrate this system in the minimal language MLsub, which types a strict superset of core ML programs. This is made possible by keeping a strict separation between the types used to describe inputs and those used to describe outputs, and extending the classical unification algorithm to handle subtyping constraints between these input and output types. Principal types are kept compact by type simplification, which exploits deep connections between subtyping and the algebra of regular languages. An implementation is available online.

Describing a problem using classical linear algebra is a very well-known problem-solving technique. If your question can be formulated as a question about real or complex matrices, then the answer can often be found by standard techniques. It's less well-known that very similar techniques still apply where instead of real or complex numbers we have a closed semiring, which is a structure with some analogue of addition and multiplication that need not support subtraction or division. We define a typeclass in Haskell for describing closed semirings, and implement a few functions for manipulating matrices and polynomials over them. We then show how these functions can be used to calculate transitive closures, find shortest or longest or widest paths in a graph, analyse the data flow of imperative programs, optimally pack knapsacks, and perform discrete event simulations, all by just providing an appropriate underlying closed semiring.