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💻Advanced Design Strategy and Software

Key Software Development Lifecycle Models

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Why This Matters

Software development lifecycle (SDLC) models aren't just abstract frameworks—they're the strategic blueprints that determine whether a project succeeds or fails. In Advanced Design Strategy, you're being tested on your ability to match the right model to the right project context, understanding how factors like requirement stability, risk tolerance, team structure, and delivery timelines influence which approach works best. These models represent fundamentally different philosophies about how software should evolve from concept to deployment.

Don't just memorize the names and steps of each model. Focus on understanding when and why you'd choose one over another. Exam questions will ask you to analyze scenarios and recommend appropriate methodologies, compare trade-offs between flexibility and predictability, or explain how a model's structure addresses specific project risks. Know what problem each model solves, and you'll be ready for anything.


Sequential & Plan-Driven Models

These models prioritize upfront planning, comprehensive documentation, and predictable progression. They assume requirements can be fully defined before development begins and that changes are costly once work starts.

Waterfall Model

  • Linear, phase-gated structure—each phase (requirements → design → implementation → testing → deployment) must complete before the next begins
  • Heavy documentation emphasis makes it ideal for regulated industries or projects requiring audit trails
  • Low change tolerance means it works best when requirements are stable and well-understood from the start

V-Model

  • Verification and validation pairing—every development phase has a corresponding testing phase planned in parallel
  • Early test planning catches defects sooner by designing test cases during requirements and design phases
  • Quality-focused extension of Waterfall suited for safety-critical systems where reliability is non-negotiable

Compare: Waterfall vs. V-Model—both are sequential and documentation-heavy, but V-Model embeds testing planning from day one rather than treating it as a final phase. If asked about improving quality assurance in a plan-driven approach, V-Model is your answer.


Iterative & Risk-Managed Models

These models acknowledge that perfect upfront planning is often impossible. They build in cycles of refinement, allowing teams to learn and adjust as they go.

Iterative Model

  • Repeated development cycles—each iteration produces a working version that can be tested and evaluated
  • Early risk identification through continuous feedback reduces the chance of late-stage surprises
  • Requirement evolution supported as user feedback shapes subsequent iterations

Spiral Model

  • Risk analysis at every cycle—each spiral includes planning, risk assessment, engineering, and evaluation phases
  • Combines iteration with systematic risk management, making it ideal for large, complex, high-uncertainty projects
  • Cost-intensive but thorough—the overhead of repeated risk analysis pays off when failure costs are high

Compare: Iterative vs. Spiral—both use repeated cycles, but Spiral adds formal risk assessment to each iteration. Choose Iterative for moderate uncertainty; choose Spiral when project failure would be catastrophic.


Agile & Adaptive Models

Agile models embrace change as a competitive advantage rather than a threat. They prioritize working software, customer collaboration, and responding to feedback over following a fixed plan.

Agile Model

  • Iterative sprints with continuous feedback—development happens in short cycles with frequent customer input
  • Working software over documentation—functional deliverables matter more than comprehensive paperwork
  • Cross-functional collaboration breaks down silos between developers, testers, and stakeholders

Scrum Framework

  • Time-boxed sprints (typically 2-4 weeks) with defined roles: Scrum Master, Product Owner, Development Team
  • Ceremony-driven structure—daily stand-ups, sprint planning, reviews, and retrospectives create accountability
  • Potentially shippable increment delivered at each sprint's end ensures continuous value delivery

Kanban Method

  • Visual workflow management—tasks move across a Kanban board showing work states (To Do → In Progress → Done)
  • Work-in-progress limits prevent bottlenecks and improve flow efficiency
  • Continuous delivery without fixed iterations—work flows as capacity allows rather than in batches

Compare: Scrum vs. Kanban—both are Agile, but Scrum uses fixed-length sprints while Kanban emphasizes continuous flow. Scrum works better for teams needing structure; Kanban suits teams optimizing existing processes. FRQ tip: If asked about improving team efficiency without major process overhaul, Kanban is often the answer.


Rapid Development & Prototyping Models

These models prioritize speed and user involvement, getting functional software in front of users as quickly as possible. They're built for situations where time-to-market or requirement clarity is the primary constraint.

Rapid Application Development (RAD)

  • Rapid prototyping with user feedback loops—functional prototypes are built quickly for evaluation
  • Reusable components and tools accelerate development by avoiding reinvention
  • Tight deadline optimization makes it ideal when speed matters more than comprehensive planning

Prototyping Model

  • Working models before full development—prototypes clarify requirements and expectations early
  • Requirement discovery tool particularly valuable when stakeholders struggle to articulate needs
  • Iterative refinement based on user input reduces misunderstandings and rework

Incremental Model

  • Modular delivery of functionality—the system is built and deployed in pieces, each adding features
  • Early partial deployment provides value before the complete system is finished
  • Change-friendly architecture allows updates to individual modules without rebuilding everything

Compare: RAD vs. Prototyping—both get working software to users quickly, but RAD aims for production-ready increments while Prototyping creates throwaway models to clarify requirements. Use Prototyping when you don't know what to build; use RAD when you know but need it fast.


Quick Reference Table

ConceptBest Examples
Stable requirements, predictable deliveryWaterfall, V-Model
Quality assurance emphasisV-Model, Spiral
Risk management prioritySpiral
Changing requirements, customer collaborationAgile, Scrum, Kanban
Time-boxed iterations with ceremoniesScrum
Continuous flow without fixed sprintsKanban
Speed and rapid deliveryRAD, Incremental
Requirement discovery and clarificationPrototyping
Gradual refinement through cyclesIterative, Spiral, Incremental

Self-Check Questions

  1. A client has fixed requirements, strict regulatory documentation needs, and zero tolerance for defects. Which two models would you recommend, and why might you choose one over the other?

  2. Compare and contrast Scrum and Kanban: What project characteristics would make you choose one over the other?

  3. Your team is building software for a startup that isn't sure exactly what features users want. Which models prioritize requirement discovery, and how do they differ in their approach?

  4. Explain why Spiral Model is often chosen for aerospace or medical device software despite its higher overhead costs.

  5. An FRQ describes a project with evolving requirements, a six-month deadline, and a need for early stakeholder feedback. Identify which models could work and explain the trade-offs between them.