Product Requirements Document (PRD)

1. Executive Summary

AppDimens Dynamic is a mathematical scaling engine designed for Android (com.appdimens.dynamic). Its purpose is to map generic UI dimensions (developed against a 300dp or equivalent reference) to physical hardware parameters—scaling elegantly across phones, tablets, and unpredictable foldables.

It encapsulates 14 discrete mathematical scaling strategies (curves), alongside an autonomous Resize/Constraint subsystem that calculates the maximum bounded element size at runtime via binary search.

2. Market Context & Problem Space

Static dp measurements fall apart as device variety increases. A 300dp horizontal card fits perfectly on a classic phone but becomes aggressively small on high-density tablets or wide-screen foldables.

Core Objectives

1. Mathematical Consistency: Provide reproducible scaling curves (Linear, Logarithmic, Factorial/Power).
2. Unified Surface APIs: Symmetrical integration rules for both Jetpack Compose (compose.*) and legacy XML/Views (code.*).
3. High-Frequency Performance: Accommodate zero-allocation hot paths using lock-free architecture for smooth 60FPS and 120FPS rendering algorithms.
4. Hardware Awareness: Adapt directly to Configuration, Display aspect ratios, Multi-Window flags, and Context DPI.

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3. Functional Architecture overview

mindmap
  root((AppDimens Dynamic))
    Mathematical Engine
      Linear & Scaled Defaults
      Logarithmic Deterioration
      Exponential / Power Curves
      Diagonal Vector Paths
    Resize Subsystem
      Binary Constraint Search
      Max Area Fits Predicate
      Zero-GC Floating Arrays
    Consumer Platforms
      Jetpack Compose Wrappers
      Android Virtual Views (XML)
      Pure Kotlin Math Core
    Thread Safe Cache Layer
      ScreenFactors Bypass
      Multi-Window Detection
      Atomic Array Sharding

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4. Feature Requirements (FR)

FR-0: Systemic Foundation & Architecture

• FR-0.1 (Module Separation): Each strategy must exist as an independent computational node. compose.percent cannot import compose.power.
• FR-0.2 (Telemetry & Reading): Raw dimensions must derive directly from android.content.res.Configuration.
• FR-0.3 (Platform Parity): All Compose API nodes (*DpExtensions) must explicitly feature symmetric code equivalents for legacy migration.

FR-1: Dimension Mathematics & Curves

Strategy Class	Mathematical Goal	Expected Consumer Use Case
Scaled (Default)	Linear geometry translation from basic 300dp scale.	Baseline paddings, Standard containers.
Logarithmic	Fast early growth curve with heavy downstream damping.	Text geometries on massive tablets.
Fluid	Breakpoint-based linear interpolation ([320..768]).	Responsive Web-like UI adjustments.
Percent / Space	Absolute device fractional limits (( % \times sw )).	Fixed grid splits, Nav bars.
Interpolated	User-defined N-point vector curves.	Brand-specific interactive scaling.

FR-2: Engine & Subsystem Resize Algorithms

• FR-2.1 (Memory Integrity): Generates constraint step buffers via static pre-allocated FloatArray. No auto-boxing allowed.
• FR-2.2 (Processing): Operates on an asymptotic (\mathcal{O}(\log N)) binary search protocol to match element sizing to physical screen limits.
• FR-2.3 (Bounds & Safety): Respect hardware metrics with ResizeBound.resolveToPx using strict require(density > 0) contracts.

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5. Non-Functional Requirements (NFR)

• NFR-1 (Performance Benchmarking): Memory bypass mechanisms. The system expects that if aspect-ratio scaling is OFF on core types (PERCENT, SCALED), getOrPut reduces to a constant time single-multiply operation.
• NFR-2 (Lock-Free Threading): Uses AtomicLongArray / AtomicIntegerArray implementing a deterministic last-write-wins methodology preventing bottlenecking on ARM64.
• NFR-3 (Minimum Environment): minSdk = 24, Java 17 requirements, enforcing direct Proguard shipping via consumer-rules.pro.
• NFR-4 (Runtime Diagnostics): Engine observability functions remain conditionally gated (diagnosticsEnabled) to eliminate tracing overhead in production applications.

6. Metrics of Success

1. Integration on both Compose/XML environments without memory/GC stuttering.
2. Binary scale operations taking < 15ns median time.
3. Successful scaling to multi-window split structures automatically.