Software Development Life Cycles (SDLC)

An SDLC is a structured process used by the software industry to design, develop, and test high-quality software. The SDLC aims to produce high-quality software that meets or exceeds customer expectations, reaches completion within times and cost estimates.

Stages of SDLC

1. Planning and Requirement Analysis: Defining the project scope and resource requirements.
2. Defining Requirements: Documenting the product requirements and getting them approved by the customer.
3. Designing Software: Developing the architecture and design of the product.
4. Developing Code: The actual writing of the source code.
5. Testing: Verifying that the application contains no bugs and meets the requirements.
6. Deployment and Maintenance: Releasing the product to the market and maintaining it through updates.

SDLC Models

1. Waterfall Model

The Waterfall model is a linear-sequential life cycle model. In a waterfall model, each phase must be completed before the next phase can begin and there is no overlapping in the phases.

Pros: Simple and easy to understand and use. Cons: High risk and uncertainty; not a good model for complex and object-oriented projects.

2. V-Model (Validation and Verification)

An extension of the waterfall model, the V-model associates a testing phase with each development phase.

3. Agile Methodology

Agile is an iterative, incremental approach to software development. It focuses on flexibility, continuous improvement, and rapid delivery.

The Agile Manifesto

• Individuals and interactions over processes and tools.
• Working software over comprehensive documentation.
• Customer collaboration over contract negotiation.
• Responding to change over following a plan.

Implementing an Iterative Process (Pseudo-code)

Imagine we are building a feature in sprints.

def sprint(backlog, duration_weeks=2):
    print(f"Starting {duration_weeks}-week sprint...")
    completed_tasks = []
    for task in backlog:
        if can_complete(task):
            work_on(task)
            completed_tasks.append(task)
    return completed_tasks

project_backlog = ["Login UI", "Database Setup", "Auth Logic", "Profile Page"]
sprint_1_results = sprint(project_backlog[:2])
print(f"Delivered: {sprint_1_results}")

DevOps and Continuous Integration

Modern SDLCs often incorporate DevOps practices. Continuous Integration (CI) involves automatically testing and building the application every time a change is made to the codebase. Continuous Deployment (CD) goes a step further by automatically deploying those changes to production.

Benefits of CI/CD

• Faster time to market.
• Reduced risk of “integration hell”.
• Higher quality through automated testing.

Choosing the Right Model

The choice of an SDLC depends on:

• Complexity of the project.
• Clarity of the requirements.
• The cost of failure.
• The project timeline and budget.

For established projects with well-defined requirements, Waterfall might still be appropriate. However, for most modern web and mobile applications, Agile is the industry standard.