Code Intelligence: The Future of Productive Development

Code Intelligence: The Future of Productive Development


Self-Learning AI for a Secure Tomorrow

The ever-evolving landscape of software development has made software testing a critical aspect of the process in order to ensure that applications remain robust and secure against cyber threats. However, traditional testing methods have many limitations that may leave applications vulnerable to undiscovered risks.

In the second installment of our DevSecOps Series, our CEO Sergej Dechand discusses the transformative power of using self-learning Artificial Intelligence to enhance dynamic software testing. He will explore the growing impact of AI and how it can help developers build truly secure and stable software, despite a growing threat landscape.

The integration of self-learning AI and LLMs revolutionized the field, not only enabling more comprehensive and accurate assessment of potential vulnerabilities but even more by reducing manual engineering tasks, e.g. writing boilerplate test cases or interface definitions and with this making complex work easier across the entire developer lifecycle. This way, every security engineer and developer can focus on what's important: writing software that matters.

In his talk, Sergej will discuss:

  • How genetic algorithms enable developers to find bugs and vulnerabilities that are off-limits to conventional methods
  • How self-learning AI has been accelerating software testing since way before the likes of ChatGPT
  • How LLMs will enhance software testing even further
  • How AI is making DevSecOps easy