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    joelhooks

    system-design

    joelhooks/system-design
    Coding
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    SKILL.md

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    Principles for building reusable coding systems. Use when designing modules, APIs, CLIs, or any code meant to be used by others. Based on "A Philosophy of Software Design" by John Ousterhout...

    SKILL.md

    System Design

    Principles for building reusable, maintainable coding systems. From "A Philosophy of Software Design" by John Ousterhout.

    Core Principle: Fight Complexity

    Complexity is the root cause of most software problems. It accumulates incrementally—each shortcut adds a little, until the system becomes unmaintainable.

    Complexity defined: Anything that makes software hard to understand or modify.

    Symptoms:

    • Change amplification: simple change requires many modifications
    • Cognitive load: how much you need to know to make a change
    • Unknown unknowns: not obvious what needs to change

    Deep Modules

    The most important design principle: make modules deep.

    ┌─────────────────────────────┐
    │      Simple Interface       │  ← Small surface area
    ├─────────────────────────────┤
    │                             │
    │                             │
    │    Deep Implementation      │  ← Lots of functionality
    │                             │
    │                             │
    └─────────────────────────────┘
    

    Deep module: Simple interface, lots of functionality hidden behind it.

    Shallow module: Complex interface relative to functionality provided. Red flag.

    Examples

    Deep: Unix file I/O - just 5 calls (open, read, write, lseek, close) hide enormous complexity (buffering, caching, device drivers, permissions, journaling).

    Shallow: Java's file reading requires BufferedReader wrapping FileReader wrapping FileInputStream. Interface complexity matches implementation complexity.

    Apply This

    • Prefer fewer methods that do more over many small methods
    • Hide implementation details aggressively
    • A module's interface should be much simpler than its implementation
    • If interface is as complex as implementation, reconsider the abstraction

    Strategic vs Tactical Programming

    Tactical: Get it working now. Each task adds small complexities. Debt accumulates.

    Strategic: Invest time in good design. Slower initially, faster long-term.

    Progress
       │
       │        Strategic ────────────────→
       │       /
       │      /
       │     / Tactical ─────────→
       │    /                    ↘ (slows down)
       │   /
       └──┴─────────────────────────────────→ Time
    

    Rule of thumb: Spend 10-20% of development time on design improvements.

    Working Code Isn't Enough

    "Working code" is not the goal. The goal is a great design that also works. If you're satisfied with "it works," you're programming tactically.

    Information Hiding

    Each module should encapsulate knowledge that other modules don't need.

    Information leakage (red flag): Same knowledge appears in multiple places. If one changes, all must change.

    Temporal decomposition (red flag): Splitting code based on when things happen rather than what information they use. Often causes leakage.

    Apply This

    • Ask: "What knowledge does this module encapsulate?"
    • If the answer is "not much," the module is probably shallow
    • Group code by what it knows, not when it runs
    • Private by default; expose only what's necessary

    Define Errors Out of Existence

    Exceptions add complexity. The best way to handle them: design so they can't happen.

    Instead of:

    function deleteFile(path: string): void {
      if (!exists(path)) throw new FileNotFoundError();
      // delete...
    }
    

    Do:

    function deleteFile(path: string): void {
      // Just delete. If it doesn't exist, goal is achieved.
      // No error to handle.
    }
    

    Apply This

    • Redefine semantics so errors become non-issues
    • Handle edge cases internally rather than exposing them
    • Fewer exceptions = simpler interface = deeper module
    • Ask: "Can I change the definition so this isn't an error?"

    General-Purpose Modules

    Somewhat general-purpose modules are deeper than special-purpose ones.

    Not too general: Don't build a framework when you need a function.

    Not too specific: Don't hardcode assumptions that limit reuse.

    Sweet spot: Solve today's problem in a way that naturally handles tomorrow's.

    Questions to Ask

    1. What is the simplest interface that covers all current needs?
    2. How many situations will this method be used in?
    3. Is this API easy to use for my current needs?

    Pull Complexity Downward

    When complexity is unavoidable, put it in the implementation, not the interface.

    Bad: Expose complexity to all callers. Good: Handle complexity once, internally.

    It's more important for a module to have a simple interface than a simple implementation.

    Example

    Configuration: Instead of requiring callers to configure everything, provide sensible defaults. Handle the complexity of choosing defaults internally.

    Design Twice

    Before implementing, consider at least two different designs. Compare them.

    Benefits:

    • Reveals assumptions you didn't know you were making
    • Often the second design is better
    • Even if first design wins, you understand why

    Don't skip this: "I can't think of another approach" usually means you haven't tried hard enough.

    Red Flags Summary

    Red Flag Symptom
    Shallow module Interface complexity ≈ implementation complexity
    Information leakage Same knowledge in multiple modules
    Temporal decomposition Code split by time, not information
    Overexposure Too many methods/params in interface
    Pass-through methods Method does little except call another
    Repetition Same code pattern appears multiple times
    Special-general mixture General-purpose code mixed with special-purpose
    Conjoined methods Can't understand one without reading another
    Comment repeats code Comment says what code obviously does
    Vague name Name doesn't convey much information

    Applying to CLI/Tool Design

    When building CLIs, plugins, or tools:

    1. Deep commands: Few commands that do a lot, not many shallow ones
    2. Sensible defaults: Work without configuration for common cases
    3. Progressive disclosure: Simple usage first, advanced options available
    4. Consistent interface: Same patterns across all commands
    5. Error elimination: Design so common mistakes are impossible

    Example: Good CLI Design

    # Deep: one command handles the common case well
    swarm setup
    
    # Not shallow: doesn't require 10 flags for basic usage
    # Sensible defaults: picks reasonable models
    # Progressive: advanced users can customize later
    

    Key Takeaways

    1. Complexity is the enemy. Every design decision should reduce it.
    2. Deep modules win. Simple interface, rich functionality.
    3. Hide information. Each module owns specific knowledge.
    4. Define errors away. Change semantics to eliminate edge cases.
    5. Design twice. Always consider alternatives.
    6. Strategic > tactical. Invest in design, not just working code.
    7. Pull complexity down. Implementation absorbs complexity, interface stays simple.
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