Daniel is actively seeking opportunities to speak at Tech Conferences or meetups. Subjects range from code methodologies and readability to specific technologies. Below are some examples of previous talks as well as any programmed future appearances.
The Nitty GittyThurs 5th Sep 2019 - Async Brighton
Git is not complicated, but it is complex (and confusing). In this talk, I explain the basic building blocks of git: commits, blobs, trees and refs. I then build up, past branches and merges to remotes and re-bases in an attempt to demystify the tool we all rely on.
Readable code - Available without PrescriptionFri 22nd Nov 2019 - HalfStack Conference London
This talk tells the story of a revolution in the world of linguistics and how we can apply it to software development. Everyone agrees on the importance of readable code, but no-one can agree on how to write it. Are code comments evil or vital? Is it better to be terse or explicit? There are many conflicting rules out there, and they all feel a little arbitrary.
Grammar is also full of rules, and not all rules are the same. "Prescriptive" rules are hard to follow. "Descriptive" rules are intuitive. With the help of Shakespeare, Noam Chomsky and some little green men, we will learn the dangers of prescriptive rules, and discover how an amateur online scientific experiment could help us write readable code.
Useable, Grammatical and Readable CodeThurs 6th Dec 2018 - Async Brighton
As software developers, we all know that we need to make our code more readable - but how exactly? There is not a lot of literature out there on the subject, and what there is can be very dogmatic and contradictory. In this talk, I attempt to tackle the issue by learning from the worlds of Linguistics and UX, which have successfully solved similar problems. I present the initial findings from my readability experiment at howreadable.com.
Slides available on Speaker deck
Random ThoughtsFri 6th July 2018 - Brighton Ruby
How a single line of Ruby code, the flip of a coin and some bad luck lead to an understanding of how random numbers really work, and why fairness isn’t always the best policy.