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Oleksandr Bezdieniezhnykh e94842d330 [AZ-189] Update coding and testing rules for clarity and consistency

- Revised coding standards to emphasize readability, meaningful comments, and test verification.
- Adjusted test coverage thresholds to 75% for business logic and clarified expectations for test scenarios.
- Enhanced guidelines for handling skipped tests, emphasizing the need for investigation and resolution.
- Updated commit message format and length requirements for better adherence to Git conventions.

Made-with: Cursor

2026-04-17 20:27:28 +03:00

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Comparison & Analysis Frameworks — Reference

General Dimensions (select as needed)

Goal / What problem does it solve
Working mechanism / Process
Input / Output / Boundaries
Advantages / Disadvantages / Trade-offs
Applicable scenarios / Boundary conditions
Cost / Benefit / Risk
Historical evolution / Future trends
Security / Permissions / Controllability

Concept Comparison Specific Dimensions

Definition & essence
Trigger / invocation method
Execution agent
Input/output & type constraints
Determinism & repeatability
Resource & context management
Composition & reuse patterns
Security boundaries & permission control

Decision Support Specific Dimensions

Solution overview
Implementation cost
Maintenance cost
Risk assessment
Expected benefit
Applicable scenarios
Team capability requirements
Migration difficulty

Decomposition Completeness Probes (Completeness Audit Reference)

Used during Step 1's Decomposition Completeness Audit. After generating sub-questions, ask each probe against the current decomposition. If a probe reveals an uncovered area, add a sub-question for it.

Probe	What it catches
What does this cost — in money, time, resources, or trade-offs?	Budget, pricing, licensing, tax, opportunity cost, maintenance burden
What are the hard constraints — physical, legal, regulatory, environmental?	Regulations, certifications, spectrum/frequency rules, export controls, physics limits, IP restrictions
What are the dependencies and assumptions that could break?	Supply chain, vendor lock-in, API stability, single points of failure, standards evolution
What does the operating environment actually look like?	Terrain, weather, connectivity, infrastructure, power, latency, user skill level
What failure modes exist and what happens when they trigger?	Degraded operation, fallback, safety margins, blast radius, recovery time
What do practitioners who solved similar problems say matters most?	Field-tested priorities that don't appear in specs or papers
What changes over time — and what looks stable now but isn't?	Technology roadmaps, regulatory shifts, deprecation risk, scaling effects

2.3 KiB Raw Blame History