In this episode of the CaSE Podcast, Sven Johann, Alex Heusingfeld, and Heinrich Hartmann dive into the concept of sensitivity points in software architecture, using the recent Volkswagen data leak as a striking example. They explore how seemingly minor architectural decisions and code changes can carry massive implications when balancing trade-offs like data privacy versus functionality.
The trio also discusses the growing impact of AI-assisted development, reflecting on practical experiences with tools like ChatGPT, Cursor, and GitHub Copilot.
Birgitta Böckerler, AI Assistance beyond coding
Cursor IDE
Loveable
Massive data breach at VW
Sensitivity and Trade-Off Points in Software Architecture, chapter 7.2.
Peter Naur, Programming as Theory Building
Chapter Marks:
00:00:00 Intro00:01:57 VW data breach example00:05:45 What is a sensitivity point (SP)?00:13:10 SP: How serious are we with security requirements00:17:05 SP: Different stakeholder needs00:20:33 SP: The problem of getting stakeholders together00:25:46 SP: Applying this concept to data lineage?00:32:30 SP: Protecting critical lines of code00:36:38 SP: Engineering critical code protection00:41:57 AI assistance: it helps, if your are an expert00:45:32 AI: Being successful with a clear mental model and iterations00:54:33 AI: Larger code bases01:01:10 AI: Devil’s advocate and inspiration on design01:09:30 AI: Talking to the LLM for coding and writing01:15:35 AI: Non technical people creating code01:27:50 AI: Wrapping up