Claudia Doppioslash discusses some of the useful features of Elm, such as time traveling debugger, immutability, union types, type inference and Functional Reactive Programming.
Gerard Sans explains RxJS' data architecture based on reactive programming, exploring Observables API using RxJS koans and unit tests. RxJS 5 focuses on performance and usability.
Alexey Kazakov discusses the latest improvements on JSDT -debugging Node.js and browser applications, JSON editing features, integrations with npm and bower-, and the future of the project.
Marc Khouzam presents best practices for debugging using dynamic printf, reverse debugging, the GDB console, the standalone debugger, a Docker container and connecting CDT to a running GDB session.
Kostis Sagonas introduces the idea of concolic unit testing of Erlang programs and the CutEr tool, how it is different, and how it can be used to identify errors in programs in a fully automatic way.
Seb Rose discusses BDD, what it is good for and what tools can help, common BDD anti-patterns and myths, as well as advice for starting with it.
Aaron Bedra focuses on describing a system as a series of models that can be used to systematically and automatically generate input data and ensure that a code is behaving as expected.
Dave Farley discusses using acceptance testing to work quickly and effectively, building functional coverage for complex enterprise-scale systems, and managing and maintaining those tests.
Sam Adams talks about testing at LMAX Exchange, extending functional tests into live monitoring of production through isolation, and moving fast through incremental delivery, quality and automation.
Mathieu Bastian explores the mechanics of unit, integration, data and performance testing for large, complex data workflows, along with the tools for Hadoop, Pig and Spark.
Pawel Sawicz suggests putting tests to the test by mutating the code to see if the codebase is properly covered by tests and how errors are propagated.
Tammer Saleh talks about the mistakes made building microservices, when microservices are appropriate, where to draw the lines between services, performance issues, testing, debugging, failure, etc.