We'll discuss how to use strongly typed functional programming to build a typesafe and highly declarative DSL to generate SQL, that allows better abstractions and minimises runtime errors. We'll focus on type systems, and build an intuition for row types and how it guarantees correctness for SQL. I'll cover some parts of actual SQL generation.

A similar talk was given at IIIT Delhi earlier, however that was more geared towards beginners to Functional Programming (link below). I plan to give a more intermediate level talk this time.

We take a dive into probabilistic programming, beginning with a high-level explanation of what probabilistic programming is. We then continue to see how to use the monad-bayes library for performing tasks such as regression in a bayesian formalism. We also look into the implementation of the library, which involves performing an interesting sampling method (markov-chain-monte-carlo) on a very unique space (the space of computational traces of the program). We finally end with next-steps for the haskell community to improve in the probablistic programming space, ala pyro for python

Here is our tiny re-implementation of monad-bayes, boiled down to the essentials: https://github.com/bollu/shakuni

Paper on which the talk is based on: http://mlg.eng.cam.ac.uk/pub/pdf/SciGhaGor15.pdf

Sky BML (Beat/Meet/Lose) is a streaming system that produces real time Competitive Intelligence about our Lodging Supply.

This competitive information is being used, among others, for Market Managers to negotiate with hotels for better rates and avail. Competitiveness is proportional to the share of BML Losses that Expedia incurs. This is why Market Managers focus their energies on minimising losses.

However, it is not easy to understand why losses occur and consequently their resolution takes proportionately long.Our system tries to simplify this and hence accelerate resolution of losses.

To develop this system, we fully leveraged the power of different functional features of Scala and used Structured Spark Streaming as the processing engine in combination with Clustering(for better app supervision and lifecycle management of the nodes).

Similarly, some of the complex challenges are solved very naturally using functional programming features of easily. We had this complex problem of traversing a decision tree (based on conditional expressions) and then evaluating the child nodes(which are also expressions) with different lookup services responsible for mapping the symbols used in Expressions.

I will be discussing in detail on how we tactically use Functional Programming concepts like Implicits, currying, High-Order Functions to get rolling with this problem with ease.

Similarly, I will discuss on the way we have apply OOP principles to handle different kinds of inputs(streaming/batch) with minimal code duplication.

Overall, it will be lot of fun to discuss the way to think about our problems and how our thinking is shaped by different concepts available in Scala.

The type system plays an important role in building type-safe applications that reduce runtime exceptions and developer mistakes. This sophisticated system is leveraged by Scala’s most famous functional libraries, such as Scala-Cats and ScalaZ. This feature-rich system allows implementing pure functional programming on the JVM. It is a beast due to its complex syntax, as it prevents developers from exploring its beautiful aspects like partially applying types in Scala. In this talk, we will tame the beast and use its beauty to solve real-life issues faced during coding. Our examples will be based on generics, constraints, type lambdas, and the kind projector plugin.

The following are the learning objectives of this talk:

1. Practical use cases of the type system using real-life coding.

2. Implementing custom higher kinded types and handling partially applied types via type lambdas and the kind projector plugin.

Rust is a new systems programming language that is garnering a lot attention from higher level programmers alike. It has a strong type system that enables some interesting functional programming patterns. Through this talk, I would like to demonstrate the Zero Cost Functional Abstractions in Systems Programming and Otherwise. The talk assumes intermediate level knowledge of FP principles and basic understanding of Rust Lang.

Real world applications are hard to imagine without side effects such as writing to a DB or UI. IO-monads were introduced into the Haskell language to write programs in a robust way. And we have been using monads in our day to day job without even knowing those are monads such as IEnumerable/IObservable in languages like C#, Java.

This talk is to give a basic understanding about monads and why should we care about that, and a little bit about onion/clean architecture.