Martin Thompson focuses on the evolution of Java and how it contrasts to C/C++, covering the cultural challenges of pushing the limits of performance and how to collaborate with industry experts and organize teams, which often stands at odds with the culture in many organisations.
Viktor Klang discusses approaches to writing software without building a complex, full of bugs and hard to maintain basecode.
Jacob Rutledge introduces Google Glass, what can be done with it and how to get started programming against it with Android SDK, sharing his own experience with it as a consumer and developer.
Damian Conway discusses what regexes really are, how they actually work, and how programmers can make use of their existing software development skills to construct correct and efficient regexes. *Note: We're not able to use our standard split-screen view to show this, but wanted to bring it to you anyway.*
Jonathan Worthington explains the garbage collection terminology, the trade-offs made by GC designers, and how to write GC-friendly code for better performance.
Domenic Denicola talks about the WHATWG stream specification, uncovering the abstractions used to build web streams and the API around them.
Christopher Simons suggests using SBSE to iterated through multiple possible solutions and select the one that performs the best, offering insight into some available tools and techniques.
In this solutions track talk, sponsored by Oracle, Simon Ritter looks at how Embedded Java and a Raspberry Pi were used to communicate with the diagnostic and management systems of an Audi S3 and process the data, and how JavaFX has been used to provide an in-car information system for less than $200.
Josh Suereth discusses Scala: expressions, abstracting behaviors, FP & OOP, Futures & Promises, libraries with implicit classes and value classes, tracking lexical state with implicit values.
Joe Kuemerle discusses some of the top threats that can break an app along with techniques to improve the design of an application to minimize vulnerabilities and mitigate what cannot be removed.
Roger Orr solves a problem with different levels of complexity trying to answer what the complexity notation actually means and why it is important in practice.