Stream processing is mainstream (again): Widely-used stream libraries are now available for virtually all modern OO and functional languages, from Java to C# to Scala to OCaml to Haskell. Yet expressivity and performance are still lacking. For instance, the popular, well-optimized Java 8 streams do not support the zip operator and are still an order of magnitude slower than hand-written loops.

Streaming libraries have become ubiquitous in object-oriented languages, with recent offerings in Java, C#, and Scala. All such libraries, however, suffer in terms of extensibility: there is no way to change the semantics of a streaming pipeline (e.g., to fuse filter operators, to perform computations lazily, to log operations) without changes to the library code. Furthermore, in some languages it is not even possible to add new operators (e.g., a zip operator, in addition to the standard map, filter, etc.) without changing the library. We address such extensibility shortcomings with a new design for streaming libraries. The architecture underlying this design borrows heavily from Oliveira and Cook's object algebra solution to the expression problem, extended with a design that exposes the push/pull character of the iteration, and an encoding of higher-kinded polymorphism. We apply our design to Java and show that the addition of full extensibility is accompanied by high performance, matching or exceeding that of the original, highly-optimized Java streams library.

As cloud computing and big data gain prominence in today's economic landscape, the challenge of effectively articulating complex algorithms in distributed environments becomes ever more important. In this paper we describe MBrace; a novel programming model/framework for performing large scale computation in the cloud. Based on the .NET software stack, it utilizes the power of the F# programming language. MBrace introduces a declarative style for specifying and composing parallelism patterns, in what is known as cloud workflows or a cloud monad. MBrace is also a distributed execution runtime that handles orchestration of cloud workflows in the data centre.