ScalaUA-2020 Abstracts

Alexander Merritt – ONNX-Scala: Typeful, Functional Deep Learning Model Inference (+)
  The talk opens by providing a sketch of machine learning and how it relates to functional programming. We subsequently introduce ONNX and motivate the use of an interchange format and a dedicated serving/prediction layer for production. Next we cover ONNX-Scala's design goals and features, discussing backends, the generated fine-grained API, and model code generation. Along the way we compare an ONNX model visualization with the representation of the model in ONNX-Scala. This is followed by a discussion of the type-safe/functional features offered by ONNX-Scala and some remarks on future directions.
Anatolii Kmetiuk – An argument against functional programming
  In this talk, I’d like to discuss purely functional paradigm of programming and why it does not matter when it comes to writing sane code.
Artur Skowronski – Landscape after a battle – what’s left of Blockchain tooling
  It is well known that during the gold rush, the best money gets shovel sellers. In our industry, it's a similar thing - during the "Blockchain Gold Rush" a lot of developer's tooling emerged to suit the demand. Now, when we can say that the dust finally settled, let's do a bit of post-mortem and check what is a current landscape of Blockchain tooling industry. Are there any "shovels" that stood the trial of time?
Avi Levi – Domain Driven Design In practice
  Domain-Driven Design is a topic that is buzzing around for a long time. In this talk, we will take a real-life example and we will show a practical approach for implementing Domain Driven Design pattern using Akka actors & Scala.
Ayush Mittal – Effectful* programming in Scala
  Functional Programming (FP) languages are about "purity". A pure function is referentially transparent and has no side effects. However, any enterprise application software must perform side effects like read from database or upload to an Amazon S3 bucket. It appears that the only way to make a code that performs side-effects referentially transparent is to not run it! In this talk, we look at the principle of "first-class effects". They are effects that don’t break referential transparency and allow users to model side effects in a functional style.