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\fancyhead[L]{AISE502 -- AI in Software Engineering II}
\fancyhead[R]{Lecture Notes}
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    {\Huge\bfseries AISE502: AI in Software\\Engineering II\par}
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    {\Large Lecture Notes\par}
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    {\large Core Part: A Theory of Architecture--Application Fit\par}
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    {\large Dr.\ Florian Herzog\par}
    \vspace{0.3cm}
    {\large University of Applied Sciences of the Grisons (FH Graub\"unden), Chur\par}
    \vspace{0.5cm}
    {\large Autumn Semester 2026\par}

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    \begin{abstract}
    These lecture notes form the core of the module AISE502 \emph{AI in Software Engineering II}. They develop a coherent theory of \emph{architecture--application fit}: software architecture is understood as the set of significant, hard-to-reverse decisions, driven by measurable quality attributes, made by systematically matching application requirements profiles against pattern capability profiles, and validated empirically over the entire software lifecycle. \textbf{Part~I} lays the conceptual and methodological foundations: architecture as a decision problem, quality attributes as architectural drivers, measurable quality attribute scenarios, and Architecture Decision Records. \textbf{Part~II} catalogues seven central architectural patterns -- from the layered architecture, the modular monolith and microservices to event-driven, pipeline and serverless architectures -- as capability profiles with their software engineering implications. \textbf{Part~III} characterises ten application classes -- from core banking systems, social media platforms and simulations to the AI-native advisory platform -- as weighted requirements profiles. \textbf{Part~IV} brings both sides together: the fit matrix, the step-by-step decision procedure (utility tree, trade-off analysis, ADR) and the continuous measurement of the decision in operation (fitness functions, DORA metrics, evolution paths). \textbf{Part~V} extends the theory along the AI dimension: AI as a tool in the software lifecycle (Axis~A) and AI as a non-deterministic system component (Axis~B) -- showing that both roles demand the same engineering discipline.

    The methodology applied throughout rests on four principal sources, gratefully acknowledged here: the quality attribute scenarios, architectural tactics, and utility-tree/ATAM decision apparatus of the Software Engineering Institute, as consolidated by \citet{bass2021software}; the architecture-characteristics ratings and trade-off laws of \citet{richards2025fundamentals}; the architectural fitness functions of \citet{ford2022evolutionary}, which turn every decision into a measurable contract; and the empirical delivery-performance research of the DORA programme \citep{forsgren2018accelerate}. The quality vocabulary of the profile dimensions is anchored in ISO/IEC 25010:2023 \citep{iso2023product}.
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