How to Write Complex Software - Article Recap

A recap of Grant Slatton's methodology for writing complex software, emphasizing a top-down layered approach with strategic use of benchmarking, stubs, and abstraction to manage complexity effectively.

  • Start with toy programs: Before diving into features, create small driver programs to understand environmental constraints like hardware limitations, disk speed, and CPU throughput.
  • Define feasible boundaries: Micro-benchmarks help define what's actually achievable within your constraints before committing to architectural decisions.
  • Top-down approach: Begin at the top of the stack (UI or API), not at the bottom with low-level infrastructure.
  • Layered design: Design and implement software in distinct, thin layers, each responsible for minimal logic.
  • Delegate complexity: Each layer delegates remaining complexity to the next lower layer, keeping individual layers simple.
  • Perfect domain APIs: As you design one layer, define the API for the next layer down—goal is for each API to be a perfect domain-specific language for its parent.
  • Strategic stubs: When coding each layer, stub out the next lower layer to enable parallel development and faster iteration.
  • Abstract I/O interfaces: Only mock abstract interfaces for parts involving I/O; keep core business logic concrete to maintain clarity.
  • Recursive completion: Recursively complete each layer, cascading downward until the entire stack is built out.
  • When to apply: Most effective for complex, large-scale software (multi-tens/hundreds of thousands of lines of code).
  • Simple projects different: Simpler/small projects (usually <5,000 lines) may benefit more from minimalist organization and fewer abstractions.
  • Project planning: Gather and validate project requirements and feasibility—target audience, needs, market analysis.
  • Requirements specification: Document everything clearly in a Software Requirements Specification (SRS) before starting development.
  • Early design: Design the user experience and interface early (top of stack), establishing what users will interact with.
  • Architecture planning: Carefully plan and structure the software architecture before coding begins to avoid costly refactoring.
  • Incremental iterations: Develop in incremental iterations, following methodologies like Agile or Waterfall as suited to project scope.
  • Clear phases: Ensure testing, deployment, and maintenance phases are clearly defined in the roadmap from the start.
  • Cross-functional teams: Assemble teams including product managers, tech leads, engineers, UI/UX designers, and testers.
  • Communication loops: Encourage communication and iterative feedback loops throughout the entire lifecycle.
  • Balance abstraction: Expect complexity; balance the need for abstraction with performance and maintainability.
  • Early validation: Use benchmarking and prototypes to validate architectural decisions early, before investing in full implementation.
  • Interface investment: Invest time in designing interfaces, architectural boundaries, and testable abstractions that will serve the system long-term.
  • Minimal complexity exposure: Prioritize building layers that expose minimal complexity, delegating tricky logic downward systematically.
  • Abstract I/O only: Only abstract I/O interfaces—not core algorithms or logic—ensuring easier refactoring and increased reliability.
  • Robust methodology: When combined with solid planning and iterative best practices, this provides a robust roadmap from concept to launch.

The full article is available here.