@stuarthalloway is a founder and President of Cognitect (formerly Relevance). He is a Clojure committer, and a developer of the
Datomic database.

Stuart has spoken at a variety of industry events, including StrangeLoop, Clojure/conj, EuroClojure, ClojureWest, SpeakerConf, QCon, GOTO, OSCON, RailsConf, RubyConf, JavaOne, and NFJS.

Stuart has written a number of books and technical articles. Of these,
he is most proud of Programming Clojure.

Agility & Robustness: Clojure spec

You can program with high agility and end up with a robust, maintainable program. This talk will show you how to use Clojure and the new spec library to write programs that behave as expected, meet operational requirements, and have the flexibility to accommodate change.

With Clojure, you can rapidly develop robust and reusable programs using

Clojure’s new spec library augments these approaches. Developing with spec is declarative, predicative, layered, robust, and integrated with Clojure.

spec is declarative. As with type systems in static languages, spec lets you make declarative statements that communicate and document data, function arguments, and returns.

spec is predicative. You can declare predicates about data, about function arguments and returns, and even function semantics. This overlaps not only with type systems, but also with validations that are often done with costly bespoke tests and runtime checks.

spec is layered. Spec does not require any specific workflow or program shape, and in particular is compatible with iterative and incremental development.

spec supports robust programs via automatic generative testing. Given specifications, spec can write generative tests for you, generating a volume of tests limited only by your CPU time, not by what you are able to write and maintain by hand.

spec is fully integrated with Clojure. As you develop your program, you have interactive access to spec-driven documentation, validation, destructuring, conformance checking, sample data, testing, and program

Datomic, and How We Built It

Datomic is a database of flexible, time-based facts, supporting queries and joins, with elastic scalability and ACID transactions. Datomic queries run your application process, giving you both declarative and navigational access to your data. Datomic facts (“datoms”) are time-aware and distributed to all system peers, enabling OLTP, analytics, and detailed auditing in real time from a
single system.

In this talk, I will begin with an overview of Datomic, covering the problems that it is intended to solve and how its data model, transaction model, query model, and deployment model work together to
solve those problems. I will then use Datomic to illustrate more general points about designing and implementing production software, and where I believe our industry is headed. Key points include:

  • the pragmatic adoption of functional programming
  • how dynamic languages fare in mission- and performance- critical settings
  • the importance of data, and the perils of OO
  • the irony of git, or why developers give themselves better databases than they give their customers
  • perception, coordination, and reducing the barriers to scale
  • human values: courage, pragmatism, and patience