Impacting Climate Change As Technologists & Building Reactive State Machines




Impacting Climate Change as Technologists & Building Reactive State Machines

4 September 2019

New York

Added 01-Jan-1970

Impacting Climate Change as Technologist

Andrew McWilliams - Founding member of

What can a technology professional do to confront the global crisis of climate change? Sometimes it can feel so distant, it doesn't get talked about. And yet, the world's leading scientists tell us that without massive, sustained transformation of society, we are teetering on the brink of global catastrophe. The truth is that there is a great deal people in tech can do, right now, from their current positions -- and they ARE doing it in collaboration with their peers around the globe.

In this talk, Andrew will share the activities of the community, which helps technology professionals to meet, discuss, learn & leverage our skillsets and positions into positive action. He will explain current projects and activities, and show how if you want to, you can get involved help make them happen.

Embracing Reactive Data and View State

Ivan - Senior Software Engineer

At a fundamental level, every programming problem boils down to state management - analyze a problem at hand and map it to a variable or two. Then make a function which changes one of those variables and maybe returns a new one. Repeat that a few times and you have a computer program. After a while (say a couple of years) of working on that program you end up with a LOT of variables that can change in a not so predictable or obvious manner, usually because the state itself is implicit, making it increasingly difficult to build new things or fix old ones.

This talk will discuss how making the state explicit allows you to model any application process, simple or complex, in the form of a finite state machine that's easy to understand, behaves in a predictable manner, can easily be tested and even mathematically proven to work as expected. At Noom we use RxSwift a lot to model both data and processes, so for this case, we made use of a small library called RxFeedback. This allowed us to build reactive state machines that are simple to integrate and quite easy to use - once you get over the initial learning curve.

Ivan is a Senior Software Engineer at Noom and is currently working on the Apps Team as an iOS developer. His team focuses on building mobile apps that provide users with the best possible user experience. He is a huge fan of ReactiveX and functional programming, believing this is how software should be written everywhere.