Considered to be one of the fastest-growing programming languages used today, Rust is making its way through software development environments such as AdaCore’s GNAT Pro.

AdaCore, a provider of software development and verification tools, recently launched its RecordFlux technology, designed to ease the development and security of binary communication protocols.

On this episode of Embedded Insiders, we’re joined by Paul Butcher, Senior Software Engineer at AdaCore, to discuss how AI can make fuzz testing even more robust through the integration of techniques like symbolic execution and input-to-state correspondence that optimize test data sets against scenarios a system might encounter in the real world

There are many challenges that come with AI testing in safety-critical applications, as well as a variety of processes that can be used to find and fix security vulnerabilities using AI. We interviewed Paul Butcher, Senior Software Engineer at AdaCore Ltd, to discuss the most common security vulnerabilities impacting today's developers when integrating AI and ML in testing processes like fuzz testing, and what solutions AdaCore provides to help combat these concerns.

On average, software engineers spend 20-25 percent of the development lifecycle on testing, and potentially much more when working on safety-critical systems. The worst part may be that your standard unit tests aren’t able to provide 100% code coverage.

AdaCore is one of the leaders in the Ada programming language. Ada has been around for a long time, and is time tested.

AdaCore announced the availability of its new GNAT Dynamic Analysis Suite - a bundle of analysis, testing, verification, and code coverage technologies to help Ada developers build safe, secure software as well as meet internal security and quality procedures.