Sean T. Allen talks about creating repeatable tests using programmatic fault injection, message tracing, and auditing to create a trustworthy system which provides correct results.
Nathan Taylor provides an introduction to the dynamic analysis research space, suggesting integrating these techniques into various internal tools.
Matt Parker examines a number of common problems teams face when using TDD, a deceptively simple practice that requires a good deal of craftsmanship and skill to wield effectively.
Thomissa Comellas shares her experiences developing and rolling out new Disaster Recovery Testing techniques at Dropbox. Tammy Butow shares how her team runs DRTs and has implemented the techniques.
Caitie McCaffrey discusses the strategies for proving a correct system and less strenuous methods of testing, which can help increase our confidence that a system is doing the right thing.
David Xia explains how Helios testing framework drives integration tests and spins up self-contained environments during test runs, increasing Spotify’s code quality and successful deployments.
Fabrizio Romano proposes using TDD to transform business requirements into tests, driving code and tests development in harmony.
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.