25 years ago I published "Why Functional Programming Matters", a manifesto for FP--but the subject is much older than that!

As software becomes more and more complex, it is more and more important to structure it well. Well-structured software is easy to write, easy to debug, and provides a collection of modules that can be re-used to reduce future programming costs. Conventional languages place conceptual limits on the way problems can be modularised. Functional languages push those limits back. In this paper we show that two features of functional languages in particular, higher-order functions and lazy evaluation, can contribute greatly to modularity. As examples, we manipulate lists and trees, program several numerical algorithms, and implement the alpha-beta heuristic (an algorithm from Artificial Intelligence used in game-playing programs). Since modularity is the key to successful programming, functional languages are vitally important to the real world.

In this talk we'll take a deep dive into history to revisit our personal selection of highlights.

Erlang is in many ways quite old though many of the problems for which it used are quite modern. The Erlang language and system was designed around a set of requirements for telecom systems. They were distributed, massively concurrent systems which had to scale with demand, be capable of handling massive peak loads and never fail. The Erlang concurrency and error-handling model was developed around these requirements. We will describe the development of the language and the design of systems based on the Erlang showing how well the functional paradigm suits attacking these types of problems. We will also look at the further development with the introduction of new languages in the Erlang environment - the Erlang ecosystem.

Dyalog is a modern, array-first, multi-paradigm programming language, which supports functional, object-oriented and imperative programming based on an APL language kernel. During the morning and early afternoon, we will explore the fundamentals of functional programming in APL. At the end of the day, Dyalog CXO Morten Kromberg will round off with an application development session, showing how a simple application with a HTML5/JS front-end and a RESTful web service can be used to deliver the power of APL to end users, or as embeddable components for other application tools. The "hands on" sections of the workshop can be followed under Mac OS X, Linux, or Microsoft Windows.

Julia is a programming language for data science and numerical computing. Julia is a high-level, high-performance dynamic language, it uses just-in-time compilation to provide fast machine code - dynamic code runs at about half the speed of C, and orders of magnitude faster than traditional numerical computing tools.

Julia borrows two main ideas from Lisp lore:

1. Multiple-dispatch: a method is identified by a name and the types of all of its arguments (traditional OOP only uses the type of a single argument) multiple-dispatch allows for a natural programming model suitable for mathematics and general purpose programming. Interestingly, the same feature is responsible for Julia's ability to generate really fast machine code.
2. Macros: Julia has syntax that is familiar to users of other technical computing environments, however, Julia expressions are homoiconic -- Julia code can be represented as Julia data structures, and transformed from one form to another via hygienic macros. There are some very interesting uses of macros to create domain-specific languages for effective programming. 

The streaming of data in a purely functional language is a fascinating problem that have been extensively explored over the years.

In this talk we'll first briefly outline historical solutions to the problem and discuss their advantages and disadvantages,
we will then follow with a practical introduction to the great `machines` library from Edward Kmett.

We will see how the library usage compare to other players in the ecosystem (pipes, conduit, ...),
and walk through real world examples giving us a chance to write our own combinators and understand some of the internals.