52 lines
5.4 KiB
HTML
52 lines
5.4 KiB
HTML
<!-- ==========================================================================
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AISE502 · Moodle course page · Week 1
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Section title (Edit section → Section name): Week 1: Architecture as a Decision Problem
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Three blocks follow, matching the FHGR section template. Paste each block into the
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corresponding 'Text and media area' (editor → source code view), or all three into one.
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The slide set of lecture 1 is added by the lecturer as a file resource below block 2.
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Generated by src/build_moodle.py from src/content/week_01.json – edit the JSON, not this file.
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========================================================================== -->
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<!-- BLOCK 1 · Learning objectives -->
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<h4>🎯 Learning objectives</h4>
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<ul>
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<li>I can explain, using the four production systems, why no structure dominates and why each failure was a mismatch.</li>
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<li>I know Maxim 1: patterns are neither good nor bad; only the fit is.</li>
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<li>I can explain architecture as hard-to-reverse structural decisions and distinguish it from design and implementation by cost of change.</li>
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<li>I can name the five elements of the framework: R(a), C(p), fit(a,p), ADR, measurement contract.</li>
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<li>I can explain the two AI axes: Axis A (tool in the process), Axis B (runtime component).</li>
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<li>I know the six assumptions A1–A6 and which framework element each one justifies.</li>
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<li>I can derive Maxim 2 – match, document, measure – from assumptions A1, A2, A3 and A5.</li>
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<li>I can explain why the twelve dimensions D1–D12 are recurring, measurable engineering questions in five groups.</li>
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</ul>
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<!-- BLOCK 2 · Theory -->
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<h4>🧑🏫 Theory</h4>
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<p><strong>Lecture 1: Architecture as a Decision Problem</strong> · 2 lessons lecture + 2 lessons exercise<br>
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This lecture introduces the module and frames architecture selection as a decidable matching problem: four production systems, two facts, a five-element framework, six assumptions A1–A6, two maxims.</p>
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<ul>
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<li>Four production systems (Stack Overflow, Monzo, Segment, Prime Video) show two facts: structures differ radically for similar problems, and no structure dominates; the failures were mismatches, not bad patterns.</li>
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<li>Maxim 1: patterns are neither good nor bad; only the fit between a requirements profile and a capability profile is. The decision problem: choose among non-dominated alternatives, expensive to reverse.</li>
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<li>Architecture = the hard-to-reverse structural decisions that determine quality behaviour; design and implementation are cheaper to reverse. ISO/IEC/IEEE 42010:2022 obliges recording decisions with rationale. Two refusals: no fashion, no taste.</li>
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<li>Five framework elements: requirements profile R(a) (demand), capability profile C(p) (supply), the ordinal, non-compensatory fit(a,p), the ADR and the measurement contract; both profiles span the same twelve dimensions.</li>
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<li>AI enters twice: Axis A, a tool in the development process (changing how we decide); Axis B, a runtime component bringing non-determinism, latency and per-call cost (changing what we decide).</li>
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<li>Load-bearing assumptions: A1 architecture = hard-to-reverse decisions (justifies the ADR); A2 everything is a trade-off, dominance does not occur (matching problem); A3 quality attributes, not functionality, drive architecture (twelve dimensions).</li>
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<li>A4 requirements = measurable scenarios (demand-side method); A5 a decision is a hypothesis, continuously tested (measurement contract); A6 AI extends the space, not the method (D12 plus eval harness).</li>
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<li>Maxim 2: architecture selection is matching (A2, A3); the match must be documented and continuously measured (A1, A5). The red line: demand → supply → match → record → test.</li>
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<li>Three observations: engineering questions recur, ask how well rather than what, and each has a number; the twelve dimensions D1–D12 are these questions – grouped in five groups, named, measurable.</li>
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</ul>
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<p>📎 <strong>Materials:</strong> Slide set of Lecture 1 <em>(added below by the lecturer)</em> · Script: Part I – Sections 1 (The Decision Problem) and 2 (The Coordinate System: Twelve Profile Dimensions). Section 2: introduced this week, completed in week 2.</p>
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<!-- BLOCK 3 · Self-study and assignments -->
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<h4>🧑💻 Self-study and assignments</h4>
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<p><strong>📖 Reading before the lecture:</strong> Part I – Sections 1 (The Decision Problem) and 2 (The Coordinate System: Twelve Profile Dimensions). Section 2: introduced this week, completed in week 2.</p>
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<p><strong>🧩 Exercise session:</strong> Project kickoff: form teams, set up repository and tooling including agentic coding tools, build domain understanding, sketch a first ontology and collect raw stakeholder wishes.</p>
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<p><strong>🛠️ Project work this week</strong> · Milestone M1 – Requirements and Ontology (weeks 1–3)</p>
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<ul>
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<li>Form your team and set up the project: repository, environment and agentic coding tools.</li>
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<li>Build domain understanding of the investment domain and sketch a first domain model and ontology.</li>
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<li>Collect raw stakeholder wishes – unfiltered, unweighted; next week they become scenarios, in week 3 your requirements profile (Deliverable A1).</li>
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<li>Study the exercise sheet: the AI-augmented portfolio intelligence platform – prices and news in, deterministic services, an LLM Insight component, a multi-agent advisor, API-first.</li>
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</ul>
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<p><em>No deliverable is due this week.</em></p>
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