Introduction: Why Software Development Processes Matter
Choosing the right software development process can make the difference between a project that ships smoothly and one that slips, balloons in cost, or misses the mark. Processes help orchestrate requirements, design, development, testing, and deployment so teams can deliver predictable value. Below is a practical, expanded guide to some popular software development processes —Waterfall and Iterative, including Agile software development and Extreme Programming (XP). You’ll find core concepts, examples, pros and cons, and guidance on when to use each approach.Waterfall: The Classic Linear Model
Waterfall: This is a linear model, whereby the processes followed are to get requirements, analyze requirements, make a design (including High Level Design, Low Level Design), Develop code, Test application, and then deploy. A lot of software projects follow the Waterfall model.Expanded explanation:
The Waterfall model is a sequential Software Development Life Cycle (SDLC) approach. Work flows in ordered phases: requirements → analysis → design → implementation → testing → deployment (and often maintenance).
Each phase is generally completed before the next begins, and changes are controlled through formal change requests.
Common phases and artifacts:
- Requirements: Business Requirements Document (BRD), Software Requirements Specification (SRS), use cases, non-functional requirements (security, performance, availability).
- Analysis: Feasibility study, domain models, risk assessment, effort and cost estimation, project plan.
- Design:
Common phases and artifacts:
- Requirements: Business Requirements Document (BRD), Software Requirements Specification (SRS), use cases, non-functional requirements (security, performance, availability).
- Analysis: Feasibility study, domain models, risk assessment, effort and cost estimation, project plan.
- Design:
- High-Level Design (HLD): System architecture, modules/components, external interfaces.- Low-Level Design (LLD): Detailed class diagrams, database schema, algorithm specifications, API contracts.
- Development: Coding standards, branching strategy, code review, static analysis.
- Testing: Test plan, test cases, system/integration testing, performance testing, and user acceptance testing (UAT).
- Deployment: Release plan, rollback plan, change management, production sign-off, and maintenance/patching.
Strengths of Waterfall:
- Predictability: Clear upfront scope, milestones, and budgets.
- Compliance-friendly: Works well where documentation and approvals are mandatory (e.g., regulated industries).
- Stable contracts: Fixed-scope, fixed-price contracts align with a linear model.
- Clear phase gates: Management can track progress at well-defined checkpoints.
Limitations of Waterfall:
- Late validation: Usability or product-market fit issues surface late, when changes are costly.
- Change friction: Requirements churn disrupts schedules because phases are designed to be completed once.
- Risk of mismatch: If user needs evolve, the final product may not match current expectations.
When Waterfall fits:
- Requirements are stable and well-understood.
- Heavy regulatory or audit needs (e.g., defense, healthcare devices).
- Technology stack and integration points are mature and low-risk.
- Strict procurement and contract frameworks.
Waterfall example scenario:
Imagine a payment clearing system for a bank that must meet regulatory standards. The team spends several months gathering precise requirements from compliance, risk, and operations. Architecture and HLD ensure security, resiliency, and auditability. LLD pins down message formats and reconciliation rules. After development, a rigorous testing phase validates security and performance under peak loads. Deployment is carefully planned with rollback procedures. Waterfall works here because requirements are known and changes are expensive.
Metrics often used in Waterfall:
- Schedule variance and cost variance.
- Requirements stability index (change requests over time).
- Defect density by phase; defect leakage from testing to production.
- Test coverage and traceability matrix completion.
- Agile software development
- Extreme programming
Expanded explanation:
The iterative model delivers value in increments. Instead of locking all requirements upfront, the team builds a small slice end-to-end, gets feedback, and then iterates—improving quality, usability, and scope understanding along the way. Each iteration is a mini project with its own planning, development, testing, and review.
Key benefits:
- Faster feedback: You learn what the customer truly needs before you scale it.
- Risk reduction: Technical and product risks are addressed early with working software.
- Quality improvements: Frequent testing and inspection reduce defect escape rates.
Trade-offs:
- Planning complexity: You need rolling-wave planning and backlog refinement.
- Scope variability: Stakeholders must accept evolving scope details.
- Requires discipline: Without good engineering practices, iteration can devolve into rework.
When Iterative fits:
- Products with uncertain or evolving requirements (e.g., new SaaS features).
- Startups and product teams optimizing for learning speed and user feedback.
- Teams that can deliver small increments frequently.
Iterative example scenario:
A team building a mobile fitness app starts with a small iteration: user sign-up, basic activity tracking, and a simple dashboard. After a two-week iteration, analytics show users want goal-setting more than social features. The next iterations prioritize goals, progress visualizations, and notifications. The app evolves based on real usage and feedback, reducing wasted effort.
Agile Software Development (Iterative in Practice)
Agile is an umbrella of values and practices for iterative delivery. The Agile mindset emphasizes collaboration, customer feedback, responding to change, and delivering working software frequently.
Core Agile elements:
- Backlog-driven development: Work is ordered by value and risk. Items are expressed as user stories with acceptance criteria.
- Time-boxed iterations (often called sprints): Fixed-length cycles (commonly 1–2 weeks) to plan, build, test, and review a set of stories.
- Ceremonies:
- Sprint planning: Select and commit to stories based on capacity.
- Daily stand-up: Quick status and impediment removal.
- Sprint review: Demo to stakeholders; gather feedback.
- Retrospective: Improve the team’s process and technical practices.
- Roles and responsibilities:
- Product Owner: Owns the backlog and priorities; represents the customer.
- Scrum Master or Agile Coach: Facilitates the process and removes impediments.
- Developers/Engineers/QA: Cross-functional team delivering the increment.
- Artifacts and tools:
- Product backlog and sprint backlog.
- Definition of Ready (DoR) and Definition of Done (DoD).
- Burndown charts, cumulative flow diagrams.
Agile strengths:
- Flexibility: Embraces change based on feedback and market shifts.
- Early value: Stakeholders see working software often.
- Continuous improvement: Teams refine process and code quality over time.
Agile considerations:
- Requires stakeholder availability for frequent feedback.
- Needs a supportive culture—empowered teams, sustainable pace.
- Works best with solid engineering practices (CI/CD, automated testing).
Agile example: E-commerce checkout
- Iteration 1: Basic cart, address capture, and payment via one provider.
- Iteration 2: Add promo codes and order confirmation emails.
- Iteration 3: Multi-currency, wallet payments, and performance tuning.
- Stakeholders test each increment, shaping the roadmap based on conversion metrics.
Core XP practices:
- Test-Driven Development (TDD): Write a failing test, write the minimal code to pass, then refactor.
- Pair Programming: Two developers collaborate at one workstation, increasing design quality and knowledge sharing.
- Continuous Integration (CI): Integrate changes frequently with automated builds and tests.
- Simple Design: Build the simplest solution that works; defer complexity until it’s needed.
- Refactoring: Continuously improve code structure without changing external behavior.
- Collective Code Ownership: Any developer can improve any part of the code.
- Small Releases: Ship small, frequent increments to reduce risk.
- On-site Customer: Ready access to domain expertise for rapid feedback.
- Coding Standards and Sustainable Pace: Consistency and maintainable velocity.
XP benefits:
- High quality and low defect rates.
- Rapid feedback at the code and product levels.
- Easier changes due to clean, well-tested code.
XP trade-offs:
- Requires discipline and skill with TDD and pairing.
- Pair programming can feel costly if not well-facilitated.
- Demands a robust test suite and CI pipeline.
XP example: Building an API
- Start with a failing test for a GET /orders endpoint.
- Implement the minimal code to pass the test.
- Refactor to clarify domain objects and error handling.
- Add integration tests for database interactions.
- Pair programming ensures design discussions happen in real time; CI prevents regressions.
- Waterfall: Fixed upfront; change requests are controlled and often costly.
- Iterative: Emergent details; scope is continuously refined.
- Testing: Test plan, test cases, system/integration testing, performance testing, and user acceptance testing (UAT).
- Deployment: Release plan, rollback plan, change management, production sign-off, and maintenance/patching.
Strengths of Waterfall:
- Predictability: Clear upfront scope, milestones, and budgets.
- Compliance-friendly: Works well where documentation and approvals are mandatory (e.g., regulated industries).
- Stable contracts: Fixed-scope, fixed-price contracts align with a linear model.
- Clear phase gates: Management can track progress at well-defined checkpoints.
Limitations of Waterfall:
- Late validation: Usability or product-market fit issues surface late, when changes are costly.
- Change friction: Requirements churn disrupts schedules because phases are designed to be completed once.
- Risk of mismatch: If user needs evolve, the final product may not match current expectations.
When Waterfall fits:
- Requirements are stable and well-understood.
- Heavy regulatory or audit needs (e.g., defense, healthcare devices).
- Technology stack and integration points are mature and low-risk.
- Strict procurement and contract frameworks.
Waterfall example scenario:
Imagine a payment clearing system for a bank that must meet regulatory standards. The team spends several months gathering precise requirements from compliance, risk, and operations. Architecture and HLD ensure security, resiliency, and auditability. LLD pins down message formats and reconciliation rules. After development, a rigorous testing phase validates security and performance under peak loads. Deployment is carefully planned with rollback procedures. Waterfall works here because requirements are known and changes are expensive.
Metrics often used in Waterfall:
- Schedule variance and cost variance.
- Requirements stability index (change requests over time).
- Defect density by phase; defect leakage from testing to production.
- Test coverage and traceability matrix completion.
Iterative Model: Build, Learn, Improve
Iterative model: This is an alternate to the waterfall model. The main difference is to start small, and then keep on iterating by building larger sections of the project. This helps in discovering truly what the customer wants. It is also being used by product companies more frequently now since it leads to eventually lower defects, and keeps the product quality higher. Some techniques using an iterative model are:- Agile software development
- Extreme programming
Expanded explanation:
The iterative model delivers value in increments. Instead of locking all requirements upfront, the team builds a small slice end-to-end, gets feedback, and then iterates—improving quality, usability, and scope understanding along the way. Each iteration is a mini project with its own planning, development, testing, and review.
Key benefits:
- Faster feedback: You learn what the customer truly needs before you scale it.
- Risk reduction: Technical and product risks are addressed early with working software.
- Quality improvements: Frequent testing and inspection reduce defect escape rates.
Trade-offs:
- Planning complexity: You need rolling-wave planning and backlog refinement.
- Scope variability: Stakeholders must accept evolving scope details.
- Requires discipline: Without good engineering practices, iteration can devolve into rework.
When Iterative fits:
- Products with uncertain or evolving requirements (e.g., new SaaS features).
- Startups and product teams optimizing for learning speed and user feedback.
- Teams that can deliver small increments frequently.
Iterative example scenario:
A team building a mobile fitness app starts with a small iteration: user sign-up, basic activity tracking, and a simple dashboard. After a two-week iteration, analytics show users want goal-setting more than social features. The next iterations prioritize goals, progress visualizations, and notifications. The app evolves based on real usage and feedback, reducing wasted effort.
Agile Software Development (Iterative in Practice)
Agile is an umbrella of values and practices for iterative delivery. The Agile mindset emphasizes collaboration, customer feedback, responding to change, and delivering working software frequently.
Core Agile elements:
- Backlog-driven development: Work is ordered by value and risk. Items are expressed as user stories with acceptance criteria.
- Time-boxed iterations (often called sprints): Fixed-length cycles (commonly 1–2 weeks) to plan, build, test, and review a set of stories.
- Ceremonies:
- Sprint planning: Select and commit to stories based on capacity.
- Daily stand-up: Quick status and impediment removal.
- Sprint review: Demo to stakeholders; gather feedback.
- Retrospective: Improve the team’s process and technical practices.
- Roles and responsibilities:
- Product Owner: Owns the backlog and priorities; represents the customer.
- Scrum Master or Agile Coach: Facilitates the process and removes impediments.
- Developers/Engineers/QA: Cross-functional team delivering the increment.
- Artifacts and tools:
- Product backlog and sprint backlog.
- Definition of Ready (DoR) and Definition of Done (DoD).
- Burndown charts, cumulative flow diagrams.
Agile strengths:
- Flexibility: Embraces change based on feedback and market shifts.
- Early value: Stakeholders see working software often.
- Continuous improvement: Teams refine process and code quality over time.
Agile considerations:
- Requires stakeholder availability for frequent feedback.
- Needs a supportive culture—empowered teams, sustainable pace.
- Works best with solid engineering practices (CI/CD, automated testing).
Agile example: E-commerce checkout
- Iteration 1: Basic cart, address capture, and payment via one provider.
- Iteration 2: Add promo codes and order confirmation emails.
- Iteration 3: Multi-currency, wallet payments, and performance tuning.
- Stakeholders test each increment, shaping the roadmap based on conversion metrics.
Extreme Programming (XP): Engineering Excellence for Iterative Teams
XP is an Agile method that focuses deeply on engineering quality. It pairs process with practices that keep code clean and change-friendly.Core XP practices:
- Test-Driven Development (TDD): Write a failing test, write the minimal code to pass, then refactor.
- Pair Programming: Two developers collaborate at one workstation, increasing design quality and knowledge sharing.
- Continuous Integration (CI): Integrate changes frequently with automated builds and tests.
- Simple Design: Build the simplest solution that works; defer complexity until it’s needed.
- Refactoring: Continuously improve code structure without changing external behavior.
- Collective Code Ownership: Any developer can improve any part of the code.
- Small Releases: Ship small, frequent increments to reduce risk.
- On-site Customer: Ready access to domain expertise for rapid feedback.
- Coding Standards and Sustainable Pace: Consistency and maintainable velocity.
XP benefits:
- High quality and low defect rates.
- Rapid feedback at the code and product levels.
- Easier changes due to clean, well-tested code.
XP trade-offs:
- Requires discipline and skill with TDD and pairing.
- Pair programming can feel costly if not well-facilitated.
- Demands a robust test suite and CI pipeline.
XP example: Building an API
- Start with a failing test for a GET /orders endpoint.
- Implement the minimal code to pass the test.
- Refactor to clarify domain objects and error handling.
- Add integration tests for database interactions.
- Pair programming ensures design discussions happen in real time; CI prevents regressions.
Waterfall vs Iterative (Agile/XP): Practical Comparison
Scope management:- Waterfall: Fixed upfront; change requests are controlled and often costly.
- Iterative: Emergent details; scope is continuously refined.
Schedule and cost:
- Waterfall: Predictable if requirements are stable.
- Iterative: Predictable per iteration; total scope can fluctuate with learning.
- Waterfall: Predictable if requirements are stable.
- Iterative: Predictable per iteration; total scope can fluctuate with learning.
Documentation:
- Waterfall: Comprehensive upfront documentation.
- Iterative: “Just enough” documentation, updated continuously.
- Waterfall: Comprehensive upfront documentation.
- Iterative: “Just enough” documentation, updated continuously.
Risk and uncertainty:
- Waterfall: Higher risk if requirements change late.
- Iterative: Risks addressed early with working increments.
- Waterfall: Higher risk if requirements change late.
- Iterative: Risks addressed early with working increments.
Quality:
- Waterfall: Quality concentrated in a dedicated test phase.
- Iterative/XP: Quality built-in through TDD, CI, and frequent testing.
- Waterfall: Quality concentrated in a dedicated test phase.
- Iterative/XP: Quality built-in through TDD, CI, and frequent testing.
Stakeholder engagement:
- Waterfall: Heavy at the beginning and end.
- Iterative: Continuous throughout.
- Stage-Gate + Iterative: Gate reviews for funding and risk with iterative build cycles between gates.
- Iterative Waterfall: Execute each Waterfall phase in smaller chunks; e.g., design and implement per module iteratively.
- Spiral model: Iterative cycles focused on risk analysis; suitable when high-risk elements must be tackled early.
- How stable are the requirements?
- Stable → Waterfall or hybrid with clear phase gates.
- Evolving → Iterative/Agile/XP.
- What are the compliance and audit needs?
- Heavy documentation and approvals → Waterfall or hybrid with strong governance.
- What’s the level of technical risk?
- Unknown tech or complex integrations → Iterative with spikes and early prototypes.
- How fast do we need market feedback?
- Fast learning cycles → Agile or XP.
- What’s team maturity?
- New to Agile engineering? Consider starting with Agile ceremonies and adding XP practices gradually.
- Automate testing: Unit, integration, and end-to-end tests to reduce regression risk.
- Use CI/CD: Automate builds, tests, and deployments for fast, reliable releases.
- Manage requirements with clarity: Whether BRDs or user stories, include acceptance criteria and traceability.
- Keep architecture intentional: HLD and LLD can exist in Agile too; update them iteratively.
- Observe and learn: Add metrics (lead time, defect trends, burn-down, change failure rate) and retrospectives to drive improvement.
- Control changes: In Waterfall, manage change requests rigorously; in Agile, refine the backlog and re-plan continuously.
- Stakeholder engagement: Schedule regular demos or phase reviews; encourage early and honest feedback.
- Build in security and performance: Non-functional requirements should be treated as first-class citizens.
- “Agile means no design or documentation”: Agile values working software, but not at the expense of clarity. Keep design and docs lean and current.
- “XP is only for small teams”: XP practices scale when applied thoughtfully (shared standards, modular architecture, and robust CI).
- “Iterative always faster”: It’s faster to learn, but total time depends on scope, team maturity, and feedback cycles.
- Low-Level Design (LLD): Detailed design of classes, methods, database tables, and algorithms.
- Iterative vs Incremental:
- Iterative: Revisit and refine the same area multiple times.
- Incremental: Add new slices of functionality over time.
- Agile commonly blends both—adding increments and iterating to refine them.
Waterfall approach:
- Requirements: Define all reports, data sources, compliance needs, audit logs, and retention policies.
- HLD/LLD: Data warehouse schema, ETL flows, role-based access with auditing.
- Development: Implement ETL, build dashboard widgets, apply security controls.
- Testing: Validate data correctness, performance under peak usage, and HIPAA compliance artifacts.
- Deployment: Production roll-out with training and handover.
- Outcome: Predictable delivery for a tightly defined scope; best when healthcare policies are fixed.
Iterative/Agile approach:
- Iteration 1: Ingest two critical data sources and deliver two high-value reports.
- Iteration 2: Add filters, drill-downs, and export features based on clinician feedback.
- Iteration 3: Expand data coverage, add alerting, and refine performance.
- Continuous input: Compliance reviews occur each iteration; documentation evolves incrementally.
- Outcome: Early utility for clinicians, flexible adaptation to new reporting needs.
Conclusion: Fit the Process to the Problem
Waterfall excels when certainty, compliance, and predictability are paramount. Iterative approaches—especially Agile and XP—shine when learning, adaptability, and continuous quality matter most. The best teams are not dogmatic; they tailor the process, blend practices, and keep feedback loops short while honoring constraints like compliance and budget.
- User Stories Applied: For Agile Software Development by Mike Cohn (Get this book from Amazon)
- Scrum: The Art of Doing Twice the Work in Half the Time by Jeff Sutherland (Get this book from Amazon).
- Extreme Programming Explained: Embrace Change by Kent Beck (Get this book from Amazon).
- Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin (Get this book from Amazon).
- The Mythical Man-Month by Frederick P. Brooks Jr. (Get this book from Amazon)
- Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation by Jez Humble and David Farley (Get this book from Amazon)
- Lean Software Development: An Agile Toolkit by Mary and Tom Poppendieck (Get this book from Amazon)
- Waterfall: Heavy at the beginning and end.
- Iterative: Continuous throughout.
Hybrid Approaches You’ll See in the Wild
- Water-Scrum-Fall: Waterfall planning and release governance with Agile delivery teams in the middle.- Stage-Gate + Iterative: Gate reviews for funding and risk with iterative build cycles between gates.
- Iterative Waterfall: Execute each Waterfall phase in smaller chunks; e.g., design and implement per module iteratively.
- Spiral model: Iterative cycles focused on risk analysis; suitable when high-risk elements must be tackled early.
Choosing the Right Process: A Simple Decision Guide
Ask these questions:- How stable are the requirements?
- Stable → Waterfall or hybrid with clear phase gates.
- Evolving → Iterative/Agile/XP.
- What are the compliance and audit needs?
- Heavy documentation and approvals → Waterfall or hybrid with strong governance.
- What’s the level of technical risk?
- Unknown tech or complex integrations → Iterative with spikes and early prototypes.
- How fast do we need market feedback?
- Fast learning cycles → Agile or XP.
- What’s team maturity?
- New to Agile engineering? Consider starting with Agile ceremonies and adding XP practices gradually.
Practical Tips to Succeed With Any Model
- Define “done”: Include code complete, peer review, test coverage, security checks, and deployment readiness.- Automate testing: Unit, integration, and end-to-end tests to reduce regression risk.
- Use CI/CD: Automate builds, tests, and deployments for fast, reliable releases.
- Manage requirements with clarity: Whether BRDs or user stories, include acceptance criteria and traceability.
- Keep architecture intentional: HLD and LLD can exist in Agile too; update them iteratively.
- Observe and learn: Add metrics (lead time, defect trends, burn-down, change failure rate) and retrospectives to drive improvement.
- Control changes: In Waterfall, manage change requests rigorously; in Agile, refine the backlog and re-plan continuously.
- Stakeholder engagement: Schedule regular demos or phase reviews; encourage early and honest feedback.
- Build in security and performance: Non-functional requirements should be treated as first-class citizens.
Common Misunderstandings to Avoid
- “Waterfall means no feedback”: Not true. You can incorporate phase reviews, prototypes, and user validation—just expect more paperwork and change control.- “Agile means no design or documentation”: Agile values working software, but not at the expense of clarity. Keep design and docs lean and current.
- “XP is only for small teams”: XP practices scale when applied thoughtfully (shared standards, modular architecture, and robust CI).
- “Iterative always faster”: It’s faster to learn, but total time depends on scope, team maturity, and feedback cycles.
Mini Glossary
- High-Level Design (HLD): Architecture, components, and external interfaces.- Low-Level Design (LLD): Detailed design of classes, methods, database tables, and algorithms.
- Iterative vs Incremental:
- Iterative: Revisit and refine the same area multiple times.
- Incremental: Add new slices of functionality over time.
- Agile commonly blends both—adding increments and iterating to refine them.
End-to-End Example: Applying Both Approaches to the Same Problem
Problem: Build a reporting dashboard for a healthcare provider.Waterfall approach:
- Requirements: Define all reports, data sources, compliance needs, audit logs, and retention policies.
- HLD/LLD: Data warehouse schema, ETL flows, role-based access with auditing.
- Development: Implement ETL, build dashboard widgets, apply security controls.
- Testing: Validate data correctness, performance under peak usage, and HIPAA compliance artifacts.
- Deployment: Production roll-out with training and handover.
- Outcome: Predictable delivery for a tightly defined scope; best when healthcare policies are fixed.
Iterative/Agile approach:
- Iteration 1: Ingest two critical data sources and deliver two high-value reports.
- Iteration 2: Add filters, drill-downs, and export features based on clinician feedback.
- Iteration 3: Expand data coverage, add alerting, and refine performance.
- Continuous input: Compliance reviews occur each iteration; documentation evolves incrementally.
- Outcome: Early utility for clinicians, flexible adaptation to new reporting needs.
Conclusion: Fit the Process to the Problem
Waterfall excels when certainty, compliance, and predictability are paramount. Iterative approaches—especially Agile and XP—shine when learning, adaptability, and continuous quality matter most. The best teams are not dogmatic; they tailor the process, blend practices, and keep feedback loops short while honoring constraints like compliance and budget.
Amazon Books on Software Development Processes (Curated) - Affiliate links (I get a small commission if you buy using these links)
- Agile Estimating and Planning by Mike Cohn (Get this book from Amazon)- User Stories Applied: For Agile Software Development by Mike Cohn (Get this book from Amazon)
- Scrum: The Art of Doing Twice the Work in Half the Time by Jeff Sutherland (Get this book from Amazon).
- Extreme Programming Explained: Embrace Change by Kent Beck (Get this book from Amazon).
- Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin (Get this book from Amazon).
- The Mythical Man-Month by Frederick P. Brooks Jr. (Get this book from Amazon)
- Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation by Jez Humble and David Farley (Get this book from Amazon)
- Lean Software Development: An Agile Toolkit by Mary and Tom Poppendieck (Get this book from Amazon)
YouTube Videos Explaining These Concepts (Suggested)
- Agile vs Waterfall: Pros and Cons- Scrum in 20 mins... (with examples)
- Master Core Scrum Concepts | Sprints, User Stories, Retrospectives Explained
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- Extreme Programming (XP): Agile's Most Disciplined Methodology Explained
- Extreme Programming (XP): Agile's Most Disciplined Methodology Explained
By understanding the strengths and trade-offs of Waterfall and Iterative approaches (including Agile and XP), you can choose a process that aligns with your team’s goals, constraints, and product maturity—and deliver value with confidence.
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