Software Engineering - 2022

 

Section-A (Very Short Answer Type Questions)

Note: Each answer should be within 75 words.

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1. What is feasibility study? What are the contents we should contain in the feasibility report?

A feasibility study is an analysis of how practical and viable a proposed project or system is. It assesses whether the project is technically, economically, legally, and operationally feasible.

Contents of a Feasibility Report:

1. Technical Feasibility: Evaluates hardware and software requirements.
2. Economic Feasibility: Assesses cost-benefit analysis.
3. Legal Feasibility: Ensures compliance with laws.
4. Operational Feasibility: Determines whether the system meets user needs.
5. Schedule Feasibility: Estimates project timeline.

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2. Differentiate between verification and validation.

Aspect	Verification	Validation
Definition	Ensures the software meets specifications.	Ensures the software meets user requirements.
Focus	Process-oriented	Product-oriented
Performed When	Before development/testing	After development/testing
Methods	Reviews, walkthroughs, inspections	Testing, user acceptance testing (UAT)
Example	Checking if a design document follows guidelines	Checking if the final software works correctly

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3. Explain Agile methodology in short.

Agile methodology is a software development approach that focuses on incremental, iterative development. It promotes collaboration, flexibility, and customer feedback. Agile follows frameworks like Scrum, Kanban, and XP (Extreme Programming).

Key Features of Agile:

• Divides the project into small iterations called sprints.
• Encourages continuous feedback and adaptation.
• Uses daily stand-up meetings to discuss progress.
• Prioritizes working software over extensive documentation.

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4. Is it possible to estimate software size before coding? Justify your answer with a suitable example.

Yes, software size estimation is possible before coding using methods like Function Point Analysis (FPA) and Lines of Code (LOC).

Example:

If a banking system is being developed, developers can estimate:

• The number of screens, transactions, and reports required.
• The complexity of each module.
• The estimated effort required based on past projects.

This helps in budgeting, scheduling, and resource allocation.

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5. Compare Development Testing with Regression Testing.

Aspect	Development Testing	Regression Testing
Definition	Performed during development to catch early defects.	Performed after changes to ensure existing features work.
Purpose	Identifies bugs in new code.	Ensures updates don’t break the system.
When Used	During coding and unit testing.	After modifications or bug fixes.
Example	Unit testing, integration testing.	Running old test cases after updates.

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Section-B (Short Answer Type Questions)

Note: Each answer should not exceed 200 words.

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6. How does "Project Risk" factor affect the spiral model of software development?

Introduction

The spiral model is a risk-driven software development approach that combines iterative development with systematic risk analysis. Project risk plays a crucial role in each phase of the spiral model.

Impact of Project Risk on the Spiral Model

1. Risk Identification in Each Iteration

   • At the beginning of each spiral cycle, risks like cost overruns, technology failures, or requirement changes are identified and assessed.

2. Risk Mitigation Planning

   • The model includes risk mitigation strategies such as prototyping, feasibility studies, and alternative solutions before moving to the next phase.

3. Cost and Resource Management

   • High-risk projects may require extra budget, time, or resources, which can alter the project timeline.

4. Early Error Detection

   • Since the spiral model focuses on continuous refinement, risks are minimized before major investments are made.

5. Flexibility in Development

   • Unlike rigid models (e.g., Waterfall), the Spiral model allows adaptation based on risks detected at each phase.

Conclusion

Project risk directly influences budget, time, and project feasibility in the spiral model. By proactively identifying and handling risks, the model ensures better project success rates.

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7. What is the difference between SRS document and design document? What are the contents of both the documents?

SRS (Software Requirements Specification) vs. Design Document

Aspect	SRS Document	Design Document
Purpose	Defines "what" the system should do.	Defines "how" the system will be built.
Focus	Requirements and functionalities.	Architecture, modules, and implementation details.
Users	Stakeholders, clients, developers.	Developers, designers, architects.

Contents of an SRS Document:

1. Introduction – Purpose, scope, and objectives.
2. Functional Requirements – Features and functionalities.
3. Non-Functional Requirements – Performance, security, scalability.
4. System Models – Diagrams, flowcharts.

Contents of a Design Document:

1. System Architecture – High-level structure of the software.
2. Module Design – Details about individual components.
3. Database Design – Schema, entity relationships.
4. Interface Design – UI/UX, APIs, external interactions.

Conclusion

The SRS document is used for defining system requirements, while the design document focuses on technical implementation.

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8. What are the characteristics to be considered for the selection of a life cycle model? Explain clearly.

Introduction

A Software Development Life Cycle (SDLC) model provides a structured approach to software development. Choosing the right model depends on several factors.

Key Characteristics for Selecting an SDLC Model

1. Project Size and Complexity

   • Small projects → Agile or RAD (Rapid Application Development).
   • Large, complex projects → Spiral or V-Model.

2. Customer Involvement

   • Frequent feedback needed? → Agile Model.
   • Fixed requirements? → Waterfall Model.

3. Flexibility and Changes

   • Highly adaptable? → Agile, Incremental.
   • Rigid process? → Waterfall, V-Model.

4. Project Risk

   • High-risk projects? → Spiral Model (risk-driven approach).
   • Low-risk projects? → Waterfall Model.

5. Time Constraints

   • Quick delivery? → RAD, Agile.
   • Long-term project? → Spiral, Waterfall.

6. Budget Considerations

   • Limited budget? → Waterfall (fixed costs).
   • Flexible budget? → Spiral, Agile.

Conclusion

Selecting an SDLC model depends on project complexity, budget, risk, and customer requirements. Choosing the right model ensures efficient software development.

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Section-C (Long Answer Type Questions) 

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Section-C (Long Answer Type Questions)

Note: Each answer requires a detailed explanation and carries 15 marks.

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9. Define module coupling and explain different types of coupling in detail.

Introduction

In software engineering, module coupling refers to the degree of dependency between two modules. Lower coupling is preferred as it enhances maintainability and modularity.

Types of Coupling

1. Content Coupling (Highest Coupling)

   • One module directly modifies the data or logic of another module.
   • Example: Module A changes a variable inside Module B.
   • Disadvantage: Difficult to maintain.

2. Common Coupling

   • Multiple modules share global data.
   • Example: Several functions access a common global variable.
   • Disadvantage: Changes in data affect multiple modules.

3. Control Coupling

   • One module controls another by passing control variables.
   • Example: Module A sends a flag to Module B to change its behavior.
   • Disadvantage: Reduces reusability.

4. Stamp Coupling (Data Structure Coupling)

   • Modules share complex data structures but use only part of the data.
   • Example: Passing an entire object when only a few attributes are needed.
   • Disadvantage: Increases dependency on data structure.

5. Data Coupling (Best Practice)

   • Modules communicate by passing only required data.
   • Example: Function calls with necessary parameters.
   • Advantage: Improves modularity and maintainability.

6. Message Coupling (Lowest Coupling)

   • Modules interact using message passing (e.g., APIs, microservices).
   • Example: A web application using REST APIs.
   • Advantage: Highly flexible and scalable.

Conclusion

The goal is to reduce coupling for better maintainability. Data and message coupling are ideal, while content and common coupling should be avoided.

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10. Describe in detail the complete software maintenance process.

Introduction

Software maintenance involves modifying and updating software after deployment to correct issues, improve performance, or adapt to new requirements.

Types of Software Maintenance

1. Corrective Maintenance

   • Fixing bugs, errors, or defects in the software.
   • Example: Fixing a crash in an e-commerce website.

2. Adaptive Maintenance

   • Updating the software due to environmental changes (e.g., OS updates).
   • Example: Adapting a Windows 7 application to Windows 11.

3. Perfective Maintenance

   • Enhancing performance or adding new features.
   • Example: Improving the loading speed of a mobile app.

4. Preventive Maintenance

   • Future-proofing software by refactoring code or restructuring databases.
   • Example: Optimizing code to prevent performance bottlenecks.

Software Maintenance Process

1. Problem Identification

   • Detecting issues through feedback, monitoring, or user complaints.

2. Analysis & Planning

   • Assessing the impact, estimating cost, and planning implementation.

3. Implementation

   • Coding, testing, and integrating the changes.

4. Testing & Deployment

   • Validating changes with regression testing before deployment.

5. Documentation & Review

   • Updating manuals, code documentation, and maintaining logs.

Conclusion

Software maintenance is essential for sustainability and efficiency. It ensures that the software remains functional, secure, and up-to-date.

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11. Explain all levels of the COCOMO model. Assume that the size of an organic software product has been estimated to be 32,000 lines of code. Determine the effort required to develop the software product and the nominal development time.

Introduction

The COCOMO (Constructive Cost Model) is used to estimate effort, cost, and time for software development based on the number of lines of code (LOC).

Levels of COCOMO Model

1. Basic COCOMO

   • Estimates effort using a simple formula based on LOC.

2. Intermediate COCOMO

   • Considers additional factors like complexity, experience, and technology.

3. Detailed COCOMO

   • Analyzes components individually for accurate estimation.

COCOMO Formula (Basic Model):

$$\text{Effort (E)} = a \times (\text{KLOC})^b$$ $$\text{Time (T)} = c \times (\text{Effort})^d$$

For an Organic Software Product,

• a = 2.4, b = 1.05, c = 2.5, d = 0.38

Given:

• LOC = 32,000
• KLOC = 32 (since 1 KLOC = 1,000 LOC)

Effort Calculation:

$$E = 2.4 \times (32)^{1.05} = 91.27 \text{ Person-Months}$$

Development Time Calculation:

$$T = 2.5 \times (91.27)^{0.38} = 14.35 \text{ Months}$$

Conclusion

For an organic software project of 32,000 LOC, the effort required is 91.27 person-months, and the nominal development time is 14.35 months.

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 Question 12: Rapid Application Development (RAD) Model.

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Rapid Application Development (RAD) Model - Detailed Explanation

1. Introduction

The Rapid Application Development (RAD) model is a software development methodology that emphasizes quick development, user involvement, and iterative prototyping. It was introduced in the 1990s by James Martin to overcome the limitations of traditional models like Waterfall, which required long planning and development cycles.

2. Key Features of RAD Model

• Fast Development: Short development cycles (30-90 days).
• Prototyping: A working model is developed early for feedback.
• User Involvement: Customers and end-users participate actively.
• Component Reusability: Pre-built modules reduce development time.
• Iterative Process: Continuous improvements based on feedback.

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3. Phases of the RAD Model

The RAD model consists of four major phases:

Phase 1: Requirement Planning

✔ Identifies high-level business needs.
✔ Stakeholders (clients, developers, users) collaborate.
✔ Focuses on core system requirements instead of detailed documentation.

🔹 Example: A bank needs an online loan application system. Instead of detailing everything, key functionalities (loan form, approval process) are discussed.

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Phase 2: User Design (Prototyping)

✔ Develops prototypes based on user feedback.
✔ Uses Graphical User Interface (GUI) mockups and interactive models.
✔ Feedback loops ensure that user expectations are met.

🔹 Example: A retail company wants a POS (Point of Sale) system. Developers create an initial interface for adding products and checkout. Users provide feedback, and the interface is refined.

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Phase 3: Construction (Development and Testing)

✔ Developers build functional components in small iterations.
✔ Uses reusable components to speed up the process.
✔ Parallel development teams work on different modules.
✔ Testing is conducted alongside development.

🔹 Example: In a food delivery app, developers simultaneously build modules like order placement, tracking, and payment integration, rather than sequentially.

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Phase 4: Cutover (Deployment and Implementation)

✔ The final software version is deployed.
✔ Minor refinements based on final user feedback.
✔ Users are trained and system is launched.
✔ Maintenance and support continue.

🔹 Example: A healthcare app is deployed in hospitals after final approvals and training sessions.

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4. Advantages of RAD Model

🚀 Faster Development

• RAD significantly reduces development time by 40-60% compared to traditional methods.

👥 High User Involvement

• Users can see the system evolving and suggest changes early.

🔄 Iterative Prototyping

• Eliminates misunderstandings about system requirements.

🔧 Flexible to Changes

• Developers can modify features easily based on feedback.

♻ Reusability of Components

• Pre-built modules lower cost and effort.

🛠 Early Testing and Bug Fixing

• Continuous testing ensures a stable final product.

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5. Disadvantages of RAD Model

❌ Requires Active User Participation

• If users are unavailable, the development process can slow down.

❌ Not Suitable for Large-Scale Systems

• Complex projects requiring deep planning (e.g., military software) do not fit well.

❌ High Skilled Developers Needed

• Requires experienced designers and developers who can quickly adapt to changes.

❌ Not Suitable for High-Security Applications

• Systems like banking software need more rigorous planning and security testing.

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6. When to Use the RAD Model?

✔ When a project needs to be delivered quickly.
✔ When frequent changes are expected.
✔ When user feedback is critical.
✔ When the system can be built using existing reusable components.
✔ When budget allows for rapid prototyping.

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7. Real-Life Examples of RAD Model

🔹 E-commerce Website Development

• Online stores like Amazon and Flipkart use RAD for new features (e.g., AI-based recommendations).

🔹 Mobile App Development

• Apps like Instagram, Uber use RAD to quickly test and implement new features.

🔹 Startups and MVP (Minimum Viable Product)

• Startups use RAD to launch beta versions for early customer feedback.

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8. Comparison: RAD vs. Traditional Models

Feature	RAD Model	Waterfall Model
Development Speed	Very Fast	Slow
User Involvement	High	Low
Flexibility	High	Low
Prototyping	Yes	No
Best For	Dynamic, fast-changing projects	Large, structured projects

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9. Conclusion

The RAD model is ideal for fast-paced, user-driven development. It allows quick prototyping, flexible iterations, and continuous feedback. However, it requires skilled developers and is not suited for large or security-critical projects. When applied correctly, RAD can significantly reduce time-to-market while maintaining high user satisfaction.

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Question 13 (i): Limitations of the Waterfall Model

1. Introduction

The Waterfall Model is a linear-sequential approach where each phase must be completed before moving to the next. It is widely used for structured projects but has several limitations, especially in modern software development.

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2. Limitations of the Waterfall Model

1️⃣ Rigid and Inflexible Structure

• Once a phase is completed, going back is difficult and expensive.
• If requirements change mid-development, modifications require restarting the project.
• Example: If a banking application needs an additional security feature after the design phase, it cannot be incorporated easily.

2️⃣ Late Testing Stage

• Testing is done only after development is completed.
• Bugs detected late in the cycle are costly and time-consuming to fix.
• Example: A hospital management system detects data security issues after full development, leading to major rework.

3️⃣ Poor Adaptability to Changing Requirements

• Businesses evolve, and new requirements emerge, but the Waterfall model does not support changes easily.
• Example: An e-commerce website initially planned for desktop users only but later needed a mobile version. Waterfall would require redoing major parts.

4️⃣ Slow Delivery Process

• Users do not get a working version until the entire project is complete.
• Clients cannot see progress or give feedback until late in the process.
• Example: A logistics company waits months for a fully developed tracking system instead of getting a basic version early.

5️⃣ High Risk and Uncertainty

• If mistakes happen early, they remain undetected until later stages.
• Example: A travel booking system with a faulty database design will only face problems during testing, leading to major failures.

6️⃣ Requires Detailed Documentation

• Developers must follow strict documentation before coding begins.
• This increases project complexity and delays development.
• Example: A startup with limited resources struggles to maintain hundreds of pages of technical documents.

7️⃣ Minimal User Involvement

• Clients or users only see the final product after completion, leading to dissatisfaction.
• Example: A university software project might be designed differently than expected because faculty members were not consulted during development.

8️⃣ Not Suitable for Large or Complex Projects

• Large projects need constant modifications, which the Waterfall model does not support.
• Example: A national healthcare database project requiring multiple updates cannot be efficiently handled using Waterfall.

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Question 13 (ii): How Iterative Models Overcome These Limitations?

1. Introduction

To overcome the limitations of Waterfall, modern methodologies like Iterative, Agile, Spiral, and RAD (Rapid Application Development) models are used. These models support flexibility, user involvement, and faster delivery.

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2. Solutions Provided by Iterative Models

1️⃣ Flexibility in Changes

✔ Iterative Models (like Agile & Spiral) allow changes at any stage.
✔ New requirements can be incorporated without redoing the entire project.
✔ Example: In Agile development, an e-commerce website can add a wishlist feature even after the first release.

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2️⃣ Continuous Testing

✔ Testing happens in every cycle instead of only at the end.
✔ Issues are identified and fixed early, reducing risks.
✔ Example: In Scrum (Agile framework), developers test every feature as soon as it's built, ensuring reliability.

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3️⃣ Early and Frequent Deliveries

✔ Working software is delivered in phases (increments) rather than waiting for the full product.
✔ Users get a basic version early, which is improved over time.
✔ Example: A food delivery app first launches basic order placement, then adds GPS tracking and payment gateways in future updates.

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4️⃣ Higher User Involvement

✔ Clients participate in every development cycle, ensuring the product meets their expectations.
✔ Example: A hospital management system allows doctors to review the interface early and suggest improvements before the final version.

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5️⃣ Lower Risk and Uncertainty

✔ Problems are identified early through regular feedback and iterations.
✔ Developers can adapt the project plan based on test results and stakeholder inputs.
✔ Example: If a mobile banking app finds performance issues in early tests, they can optimize it before full deployment.

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6️⃣ Less Documentation Overhead

✔ Agile focuses on working software over excessive documentation.
✔ Time is spent developing instead of writing long technical reports.
✔ Example: A startup developing a new AI chatbot focuses on building features rather than lengthy documentation.

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7️⃣ Suitable for Large and Complex Projects

✔ Complex systems are developed module by module, reducing overall complexity.
✔ Example: A smart city project (IoT-based traffic system) is built in phases, ensuring smooth implementation.

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3. Comparison Table: Waterfall vs. Iterative Models

Feature	Waterfall Model	Iterative Models (Agile, RAD, Spiral)
Flexibility	Low	High
Testing	Only at the end	Continuous testing
User Involvement	Minimal	High
Delivery Speed	Slow	Fast
Handling Large Projects	Difficult	Suitable for complex projects
Adaptability to Change	Poor	Excellent

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4. Real-World Example: How Agile Replaced Waterfall

🔹 Case Study: Microsoft Office 365 Development

• Earlier: Used the Waterfall model, leading to slow releases and high costs.
• Now: Uses Agile, allowing frequent updates and better customer feedback.

🔹 Case Study: Facebook Mobile App

• Waterfall Model Limitation: Slow feature updates.
• Iterative Approach: Features like dark mode and marketplace were introduced gradually.

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5. Conclusion

Waterfall was effective in the early days of software development but has major drawbacks, especially for modern, dynamic applications.

Iterative models like Agile, Spiral, and RAD overcome these issues by offering:
✅ Continuous testing and feedback
✅ Faster, incremental deliveries
✅ Flexibility for changes
✅ Better user satisfaction

Thus, modern software development favors iterative approaches over the rigid Waterfall model.

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