Commercial Users of Functional Programming (CUFP) is a yearly workshop that is aimed at the community of software developers who use functional programming in real-world settings. This scribe report covers the talks that were delivered at the 2011 workshop, which was held in association with ICFP in Tokyo. The goal of the report is to give the reader a sense of what went on, rather than to reproduce the full details of the talks. Videos and slides from all the talks are available online at http://cufp.org .

Jane Street Capital is a successful proprietary trading company that has shifted from developing software in mainstream programming languages to developing software almost entirely in OCaml, a statically typed functional programming language that has only modest industrial use. The scope of the enterprise is small but growing: Jane Street now has over 20 OCaml programmers that have collectively written hundreds of thousands of lines of OCaml code. OCaml is used for building everything from trading systems to research infrastructure to user interfaces to systems administration tools. This talk will discuss the motivations behind Jane Street's adoption of OCaml, and why we think that statically typed functional programming languages are such a good fit for the world of trading and finance.

Abstract Jane Street Capital is a successful proprietary trading company that uses OCaml as its primary development language. We have over twenty OCaml programmers and hundreds of thousands of lines of OCaml code. We use OCaml for a wide range of tasks: critical trading systems, quantitative research, systems software, and system administration. We value OCaml because it allows us to rapidly produce readable, correct, efficient code to solve complex problems, and to change that code quickly to adapt to a changing world. We believe that using OCaml gives us a significant advantage over competitors that use languages like VB, Perl, C++, C#, or Java. It also makes finding and hiring high-quality software developers easier than with mainstream languages. We have invested deeply in OCaml and intend to use OCaml and grow our team of functional programmers for the foreseeable future.

We consider the problem of efficiently reconciling two similar sets held by different hosts while minimizing the communication complexity, which we call the set reconciliation problem. We describe an approach to set reconciliation based on a polynomial encoding of sets. The resulting protocols exhibit tractable computational complexity and nearly optimal communication complexity when the sets being reconciled are sparse. Also, these protocols can be adapted to work over a broadcast channel, allowing many clients to reconcile with one host based on a single broadcast, even if each client is missing a different subset.

There are many methods for making a multicast protocol “reliable.” At one end of the spectrum, a reliable multicast protocol might offer tomicity guarantees, such as all-or-nothing delivery, delivery ordering, and perhaps additional properties such as virtually synchronous addressing. At the other are protocols that use local repair to overcome transient packet loss in the network, offering “best effort” reliability. Yet none of this prior work has treated stability of multicast delivery as a basic reliability property, such as might be needed in an internet radio, television, or conferencing application. This article looks at reliability with a new goal: development of a multicast protocol which is reliable in a sense that can be rigorously quantified and includes throughput stability guarantees. We characterize this new protocol as a “bimodal multicast” in reference to its reliability model, which corresponds to a family of bimodal probability distributions. Here, we introduce the protocol, provide a theoretical analysis of its behavior, review experimental results, and discuss some candidate applications. These confirm that bimodal multicast is reliable, scalable, and that the protocol provides remarkably stable delivery throughput.

This paper addresses the problem of sending an MPEG-encoded video stream over a channel of limited bandwidth. When there is insufficient bandwidth available for the rate at which the sequence was encoded, some data must be dropped. In this paper we give fast algorithms to determine a prioritization of the data that optimizes the visual quality of the received video sequence in the sense that the maximum gap of unplayable frames is minimized. Our results are obtained in a new model of encoded video data that is applicable to MPEG and other encoding technologies. The model identifies a certain key relationship between the play order and dependence order of frames that allows fast determination of optimal send orders by dynamic programming.