Project Life Cycle and Effort Estimation

Project Life Cycle and Effort Estimation

Project Life Cycle (PLC)

The Project Life Cycle defines the sequence of phases through which a software project passes from start to completion.

Phases of Software Project Life Cycle

Phase	Description
Initiation	Project feasibility & approval
Planning	Scope, schedule, cost, risk planning
Execution	Design, coding, testing
Monitoring & Control	Progress tracking & quality control
Closure	Delivery, documentation, maintenance

Software Project Life Cycle Diagram

Effort Estimation

Effort Estimation is the process of predicting the amount of effort (man-months), time, and cost required to develop a software project.

Importance of Effort Estimation

• Accurate scheduling
• Cost control
• Resource allocation
• Risk reduction

Common Effort Estimation Techniques

Technique	Description
Expert Judgment	Based on experience
Analogy Method	Compare with similar projects
Function Point Analysis	Based on system functionality
Lines of Code (LOC)	Based on code size
COCOMO Model	Mathematical cost estimation

Software Process

A software process is a structured set of activities required to develop a software system.

Core Software Process Activities

Activity	Explanation
Specification	Requirement gathering
Design & Implementation	System architecture & coding
Validation	Testing
Evolution	Maintenance & upgrades

Generic Software Process Model

Software Process Models

A process model provides a framework for organizing software development activities.

Major Software Process Models

Model	Key Features	Suitable For
Waterfall	Sequential phases	Stable requirements
Incremental	Delivered in parts	Medium projects
Spiral	Risk-driven	Large, high-risk
RAD	Rapid development	Time-critical
Agile	Iterative & flexible	Changing requirements

Process Models Comparison Diagram

Choice of Process Models

Selecting the right process model is crucial for project success.

Factors Affecting Choice of Process Model

Factor	Impact
Project Size	Large → Spiral
Requirement Stability	Stable → Waterfall
Risk Level	High → Spiral
Time Constraints	Short → RAD
Customer Involvement	High → Agile

Model Selection Table 

Situation	Recommended Model
Well-defined requirements	Waterfall
Rapid delivery needed	RAD
High risk	Spiral
Frequent changes	Agile

Rapid Application Development (RAD)

RAD is a high-speed development model emphasizing quick prototyping and user feedback.

Characteristics of RAD

• Short development cycles
• Component reuse
• User involvement
• Prototype-based

RAD Phases

Phase	Description
Requirements Planning	Business needs
User Design	Prototyping
Construction	Rapid coding
Cutover	Deployment

RAD Model Diagram

Advantages & Limitations of RAD

Advantages	Limitations
Faster development	Not suitable for large projects
Early user feedback	Needs skilled developers
Reduced cost	High dependency on users

Agile Methods

Agile is an iterative and incremental development approach focused on customer collaboration and adaptability.

Agile Principles

• Working software over documentation
• Customer collaboration
• Responding to change
• Continuous delivery

Popular Agile Methods

Method	Description
Scrum	Sprint-based
XP	Extreme programming
Kanban	Visual workflow
Lean	Waste reduction

Agile Development Cycle

Advantages & Disadvantages of Agile

Advantages	Disadvantages
Flexible requirements	Less documentation
Faster delivery	Needs customer involvement
High quality	Difficult cost estimation

Dynamic System Development Method (DSDM)

DSDM is an Agile framework that focuses on time-boxing and frequent delivery.

Key Features of DSDM

• Time-boxed development
• Active user involvement
• Incremental delivery
• Fitness for business purpose

DSDM Principles

Principle	Explanation
User Involvement	Continuous feedback
Frequent Delivery	Early benefits
Iterative Development	Continuous improvement
Integrated Testing	Quality assurance

DSDM Life Cycle

Phase	Description
Feasibility Study	Project viability
Business Study	Business requirements
Functional Model Iteration	Prototype development
Design & Build Iteration	Final system
Implementation	Deployment

DSDM Life Cycle Diagram

Exam-Focused Key Points (Quick Revision)

• Project Life Cycle defines project phases
• Effort Estimation predicts time, cost, resources
• Software process structures development
• Process models guide execution
• RAD focuses on speed
• Agile supports changing requirements
• DSDM is a disciplined Agile framework

Extreme Programming & Software Estimation

Extreme Programming (XP)

Extreme Programming (XP) is an Agile software development methodology that focuses on high-quality code, frequent releases, and continuous customer involvement.

Key Idea of XP

XP takes best software engineering practices and applies them extremely to improve productivity and quality.

Core Values of XP

Value	Explanation
Communication	Continuous interaction among team members
Simplicity	Design only what is needed
Feedback	Frequent feedback from customers
Courage	Ability to change code when needed
Respect	Mutual respect among team members

Practices of Extreme Programming

Practice	Description
Pair Programming	Two programmers work together
Test-Driven Development (TDD)	Tests written before code
Continuous Integration	Frequent code integration
Refactoring	Improve code structure
Small Releases	Frequent delivery

XP Development Cycle

Advantages & Limitations of XP

Advantages	Limitations
High software quality	Requires constant customer involvement
Early error detection	Not suitable for large teams
Flexible to changes	Needs skilled developers

Managing Interactive Processes

Managing interactive processes refers to handling continuous interaction between developers, users, and stakeholders during software development.

Key Characteristics

• Iterative development
• Frequent feedback
• Continuous improvement

Interactive Process Management Activities

Activity	Description
User Collaboration	Regular meetings and reviews
Incremental Delivery	Deliver software in iterations
Feedback Integration	Modify system based on feedback
Process Adaptation	Adjust plans dynamically

Interactive Process Flow

Basics of Software Estimation

Software estimation predicts the effort, cost, time, and resources required to develop a software system.

Why Software Estimation is Important

• Prevents cost overruns
• Helps project scheduling
• Supports resource planning
• Reduces project risk

Estimation Parameters

Parameter	Unit
Effort	Person-months
Time	Months
Cost	Monetary value
Size	LOC / Function Points

Effort and Cost Estimation Techniques

Effort and cost estimation techniques can be qualitative or quantitative.

Common Estimation Techniques

Technique	Description
Expert Judgment	Based on experience
Analogy Method	Compare with similar projects
Top-Down Estimation	Estimate whole project first
Bottom-Up Estimation	Estimate each module
Algorithmic Models	Mathematical formulas

Estimation Techniques Comparison

Technique	Accuracy	Complexity
Expert Judgment	Medium	Low
Analogy	Medium	Medium
Bottom-Up	High	High
Algorithmic	High	Medium

COSMIC Full Function Points (FFP)

COSMIC (Common Software Measurement International Consortium) is a functional size measurement technique used to estimate software size.

Key Concept

COSMIC measures functional user requirements independent of technology.

COSMIC Measurement Components

Component	Description
Entry (E)	Data entering system
Exit (X)	Data leaving system
Read (R)	Data retrieved
Write (W)	Data stored

COSMIC Size Formula

COSMIC Size = E + X + R + W

(Unit: COSMIC Function Points – CFP)

COSMIC Measurement Diagram

Advantages of COSMIC

Advantage	Reason
Technology independent	Works for modern systems
Accurate sizing	Suitable for Agile
Standardized	International standard

COCOMO II (Constructive Cost Model II)

COCOMO II is an algorithmic cost estimation model used to estimate effort and schedule of software projects.

Basic Effort Estimation Formula

Effort = A × (Size)^B × ∏ Cost Drivers

Where:

• Size = Function Points or LOC
• A, B = Constants
• Cost Drivers = Effort multipliers

COCOMO II Sub-Models

Model	Usage
Application Composition	Early prototyping
Early Design	Rough architecture
Post-Architecture	Detailed estimation

Cost Drivers Categories

Category	Examples
Product	Complexity
Platform	Hardware constraints
Personnel	Skill level
Project	Tools & schedule

COCOMO II Model Diagram

Parametric Productivity Model

A Parametric Productivity Model uses mathematical equations to relate software size, effort, and productivity.

General Formula

Productivity = Output / Input

In software projects:

Productivity = Function Points / Person-Months

Characteristics of Parametric Models

Feature	Description
Data-Driven	Based on historical data
Quantitative	Uses equations
Repeatable	Produces consistent results

Examples of Parametric Models

• COCOMO II
• SLIM
• SEER-SEM

Exam-Focused Short Notes (Quick Revision)

• XP emphasizes testing, simplicity, and feedback
• Interactive processes rely on continuous collaboration
• Software estimation predicts effort and cost
• COSMIC FFP measures functional size
• COCOMO II estimates effort using cost drivers
• Parametric models use mathematical equations