Claudia Doppioslash discusses some of the useful features of Elm, such as time traveling debugger, immutability, union types, type inference and Functional Reactive Programming.
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.
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.
Tal Weiss shows how you can easily write your own JVM agent to capture accurate performance data for virtually any type of application from Java microservices to reactive actor systems in Scala.
Bryan Cantrill describes the debugging techniques employed at Joyent, and shares real stories from the trenches - and how those painful experiences resulted in better tools and better methodologies.
Laurent Bossavit provides some suggestions on how to bring the fun back into programming by developing new skills such as leprechaun hunting and brain debugging.
Ben Christensen discusses the mental shift from imperative to declarative programming, working with blocking IO such as JDBC and RPC, service composition, debugging and unit testing.
Tal Weiss explores five crucial Java techniques for distributed debugging and some of the pitfalls that make bug resolution much harder, and can even lead to downtime.
The authors introduce Alembic, a new static analysis tool that frees programmers from having to manually move computation to exploit locality in PGAS programs.
The authors show how statistical debugging can be used for diagnosing performance problems, lowing the overhead of run-time performance diagnosis without extending the diagnosis latency.