Ionic has revolutionized the way web developers make the transition mobile development, but there’s always room to improve and make the lives of new app developers easier. With Ionic 2, we’ve improved upon much of what made Ionic 1 great, while also keeping things simple and reducing the fatigue that developers can feel when learning a new tool. We’ll introduce you to the basic Ionic 2 concepts and build an app live.
This talk describes, step-by-step, how to evolve from today’s vision of agile software development to a truly disciplined agile enterprise. It briefly examines the state of mainstream agile software development and argues for the need for a more disciplined approach to agile delivery that provides a solid foundation from which to scale. It then explores what it means to scale disciplined agile strategies tactically at the project/product level and strategically across your IT organization as a whole. Your disciplined agile IT strategy, along with a lean business strategy, are key enablers of a full-fledged disciplined agile enterprise. The talk ends with advice for how to make this challenging organizational transition.
In this talk we’ll examine Clojure’s approach to data and data transformation, which is built from a foundation of immutable values and persistent collections. Clojure offers several models for transformation of collections – sequences, reducers, and transducers. We’ll compare these to each other and to the status quo to see how the functional approach results in less code, fewer bugs, and greater reuse.
When asked “What’s your architecture?” most people immediately respond with how their software is laid out and what their plans are for improving parts of it. Rarely does anybody really think through their team and organizational architecture, and even more rarely do people understand how that may fundamentally impact how the software gets written and the product that comes out at the end.
Inexpensive wireless microcontrollers are everywhere. This session will look at building wireless sensors on a variety of hardware: the super low cost ESP8266, the Particle Photon and it’s cloud services, and the new Arduino MKR1000. In addition to building connected devices, I’ll discuss some options for collecting, storing, and visualizing the sensor data.
To take full advantage of Java 8’s support for lambdas and interfaces with concrete methods, a lot is changing behind the scenes of the Scala 2.12 compiler! In this session, learn what’s changing.
You can apply agile approaches to your hiring, iterating on everything. You can get feedback as you go, and involve the entire team, including the sourcing. You can teach your recruiters to use a kanban board to track candidates and where they are in the pipeline. You can iterate on the job description (and job ad) based on what you see in candidates. When you involve the entire team, you can create questions and auditions that work for you. You can identify candidates who fit your culture and those who don’t. This session is a timeboxed interactive workshop. Be prepared to experiment and learn. Let’s make your hiring more agile.
Scala is famous in part for having one of the richest type systems of all mainstream programming languages today. Despite its reputation, Scala’s type system remains one of the most under-documented and jargon-heavy aspects of Scala. This talk will turn the academese into English, providing an example-rich tour of Scala’s type system, covering all the things that make people call it “powerful”. This talk isn’t about showcasing a bunch of challenging little logical puzzles with types; on the contrary, this talk is about showing practical uses of Scala’s type system, making it work for you and your users.
Think that C++ is an antiquated language and isn’t worth learning? Think that programming in C++ is too difficult and you’ll spend all of your time debugging segmentation faults and memory leaks? In this talk you’ll find out some of how C++ has changed in C++11, C++14, and beyond in ways that make programmer’s lives easier and allow you to write high-performance, maintainable, and well-designed code.
Spark is becoming a data processing giant, but it leaves much as an exercise for the user. Developers need to write specialized logic to move between batch and streaming modes, manually deal with late or out-of-order data, and explicitly wire complex flows together. This talk looks at how we tackled these problems over a multi-petabyte dataset at Cerner.
