Towards "annex", a Fact Based Dependency System

  • Mark Hibberd
September 06, 2014 2:00 - 2:25 PM

Abstract

Knowledge is not static. Yet when dealing with program artifacts, we choose to seal off what we know at the point in time when we know the least. This is wrong.

Context is important. Yet when defining dependencies on artifacts, instead of directly specify the query we want (and hence embedding its context), we manually translate our request into antiquated notions of meta-data, encoded as a number, embedded in a string. Yes, semantic versioning is wrong.

Reproducibility is essential. Yet most existing dependency systems force a trade off of rigour and reproducibility against flexibility and ease of use. This is not necessary.

Drawing on well understood foundations from datalog and deductive databases, and utilizing functional programming fundamentals, "annex" takes a different view on how to manage artifacts. We should be able to ask: "Give me the latest binary compatible versions of X with no known CVE"; or, "Give me the last stable builds of my dependencies that have been tested in IE 9, Chrome and Firefox"; or in a more general context outside of dependency resolution, queries such as "What platforms has build x of my library been tested on?" provide a useful understanding of the current state of artifacts; and finally, it should be possible to phrase all of these questions with a first class notion of time, for example "Give me the same dependencies when I last asked this query".

This talk will start by walking through the concepts behind "annex", before taking a deeper look at the design and implementation (in Haskell). We will look at how its functional underpinnings give rise to very desirable properties for a cross-language dependency system. These properties include: trivial distribution and caching; guaranteed reproducibility with minimal context; predictable performance; and interestingly, how steadfastly holding to functional programming principles contributes to being able to deliver a humane user experience in the face of complexity.