📘 The lecture script: A Theory of Architecture–Application Fit

The lecture notes AISE502: AI in Software Engineering II – Lecture Notes, Core Part: A Theory of Architecture–Application Fit (Dr. Florian Herzog, FH Graubünden, Autumn Semester 2026; five parts, 45 sections, about 212 pages) are the backbone of this module. They develop one coherent theory: software architecture is the set of significant, hard-to-reverse decisions, driven by measurable quality attributes, made by systematically matching an application's requirements profile against the capability profiles of architectural patterns, and validated empirically over the whole software lifecycle.

Part I – Architecture as a Decision Problem (Sections 1–7): the decision problem, the twelve profile dimensions as the shared coordinate system, the requirements profile R(a), the capability profile C(p), the three-stage match fit(a,p), Architecture Decision Records and the measurement of a decision.
Part II – Capability Profiles: The Seven Architectural Patterns (Sections 8–17): layered, modular monolith, hexagonal, microservices, event-driven, pipes-and-filters and serverless – each developed from the real problem that produced it, with its tactics, capability profile and engineering consequences (“build it and study it”); stepping back; outlook on agent orchestration.
Part III – Requirements Profiles: The Ten Application Classes (Sections 18–29): from core banking (C1) to AI-native advisory platforms (C10) – challenges, weighted requirements profiles, hard constraints, and what real systems chose.
Part IV – The Fit: Matching, Decision Procedure, and Measurement (Sections 30–39): three worked matches, the procedure in general, the 7 × 10 matching matrix and its cell rationales, hybrids and evolution paths, the decision procedure, the measurement contract (fitness functions, DORA metrics), Conway's law and team topologies, and the limits of the theory.
Part V – The AI Dimension: Tool and Component (Sections 40–45): AI as a tool in the lifecycle (Axis A) and AI as a non-deterministic runtime component (Axis B), how AI shifts the matrix, agent orchestration as the emergent eighth pattern, and the synthesis of the theory.

How the script is used. Every weekly section names the sections to read before the lecture (reading plan below). The project's design deliverables A1 and A2 use its methods – quality attribute scenarios, utility tree, R(a), the three-stage match, ADR, measurement contract. And it is the open-book material of the written examination: script and own notes on paper, closed internet; the reading for the examination is the whole script, Parts I–V.

⚠️ Living document – the script can change during the semester. The notes are altered and updated along the lecture: corrections, sharper wording and additional examples are worked in as we go, and section or page numbers may shift as a result. The version on this page is always the current one. Re-download it after every announced update and discard older copies – including printed ones you intend to bring to the examination.

📄 Download: AISE502_Vorlesung_Skript.pdf – [link]

Reading plan: which sections belong to which week

Week	Lecture	Script sections
1	Lecture 1: Architecture as a Decision Problem	Part I, Sections 1–2 (Section 2: introduced this week, completed in week 2)
2	Lecture 2: The Twelve Dimensions – and How Requirements Become Measurable	Part I, Sections 2–3 (Section 2: completed this week)
3	Lecture 3: The Supply Side, the Match, and the Decision Record	Part I, Sections 4–6
4	Lecture 4: Patterns I – Layered, Modular Monolith, Hexagonal	Part II, Sections 8–10
5	Lecture 5: Patterns II – Microservices and Event-Driven Architecture	Part II, Sections 11–12
6	Lecture 6: Pipelines, Serverless, the View Across – and Your Class (C10)	Part II, Sections 13–17; Part III, Section 28 (Sections 19–20: preview of the C1/C2 mirror pair only; read in full in week 8)
7	Lecture 7: The Fit, Formally – Three Cases, the Procedure, the Matrix	Part IV, Sections 30–32, 34, 37 (Section 37: introduction only)
8	Lecture 8: Requirements Profiles I – Application Classes C1–C5	Part III, Sections 18–23
9	Lecture 9: Classes C6–C9 – and Ten Profiles Side by Side	Part III, Sections 24–27, 29
10	Lecture 10: The Fit II – Hybrids, Evolution Paths, and the Decision Procedure	Part IV, Sections 35–36, 33
11	Lecture 11: The Fit III – The Measurement Contract, Conway's Law, and the Limits of the Theory	Part IV, Sections 37–39
12	Lecture 12: The AI Dimension I – Axis A Evidence, Axis B Foundations	Part V, Sections 40–42 (Section 42: subsections 42.1–42.5 only)
13	Lecture 13: Threats, the Shifted Matrix, Agent Orchestration – and Synthesis	Part V, Sections 42–45 (Section 42: subsections 42.6–42.7 only)
14	Lecture 14: Synthesis, Presentations, and Architecture Defence	–

Section 7 (Summary: The Red Line) closes Part I and is not assigned to a particular week; Section 28 (C10) is read in week 6 because it is the class of the course project.