KEYNOTE: Residuality Theory in Software Architecture
summary
Argues that modeling systems as interconnected residues makes uncertainty a predictable design input rather than an afterthought, using applied complexity science and random-network experiments that show architectures with certain connectivity survive unexpected events more often. Presents a simple experiment: add nodes and links until a percolation threshold appears, count surviving components, then compare architectures with built-in redundancy and loose coupling. Claims the method is easy to apply, reproducible, and used to steer design decisions under noise from failures, regulation, or pandemics.
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chapters (11)
- 0:00Residuality Theory intro
- 2:08Origins and purpose
- 8:05Core principles
- 13:03Order, system, complexity
- 20:28Light-switch experiment
- 26:06Residuality in design
- 30:11Why residual architectures survive
- 36:04Real-world examples
- 42:25Trade-offs and limits
- 45:31Future of software architecture
- 47:45Conclusion
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